Meaning of Each Level of Recommendation Score
\\n\\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\\n\\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\nFeel free to share this news on social media and help us mark this memorable moment!
\\n\\n\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/237"}},components:[{type:"htmlEditorComponent",content:'
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\nIntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\n\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\nFeel free to share this news on social media and help us mark this memorable moment!
\n\n\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"10548",leadTitle:null,fullTitle:"Lean Manufacturing",title:"Lean Manufacturing",subtitle:null,reviewType:"peer-reviewed",abstract:"Lean manufacturing is a process used in production to maximize efficiency and minimize waste by considering sustainability and the environment. This book presents a comprehensive overview of lean manufacturing in various enterprises, including manufacturing, construction, and the fabric and textile industry, among others. Chapters cover such topics as barriers to lean manufacturing, enterprise modeling, lean practices and circular economies, and more.",isbn:"978-1-83969-150-8",printIsbn:"978-1-83969-149-2",pdfIsbn:"978-1-83969-151-5",doi:"10.5772/intechopen.92922",price:119,priceEur:129,priceUsd:155,slug:"lean-manufacturing",numberOfPages:244,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"7409b2acd5150a93004300800918b736",bookSignature:"Karmen Pažek",publishedDate:"November 3rd 2021",coverURL:"https://cdn.intechopen.com/books/images_new/10548.jpg",numberOfDownloads:4070,numberOfWosCitations:0,numberOfCrossrefCitations:4,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:4,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:8,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 20th 2020",dateEndSecondStepPublish:"November 17th 2020",dateEndThirdStepPublish:"January 16th 2021",dateEndFourthStepPublish:"April 6th 2021",dateEndFifthStepPublish:"June 5th 2021",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"179642",title:"Prof.",name:"Karmen",middleName:null,surname:"Pažek",slug:"karmen-pazek",fullName:"Karmen Pažek",profilePictureURL:"https://mts.intechopen.com/storage/users/179642/images/system/179642.jpg",biography:"Karmen Pažek was born in 1976. She graduated from the Faculty of Agriculture, University of Maribor, Slovenia, in 2000. In 2001 she was employed at the same faculty as an assistant for the field of grassland management. Between 2000 and 2003, she enrolled in the master\\'s study program in Agriculture Economics at the same faculty, and in 2003 she received her master\\'s degree. In the same year, she enrolled in a doctoral study in Agriculture Economics at the Faculty of Agriculture and obtained the status of a research assistant. In 2006 she successfully completed her Ph.D. in Agriculture Economics.\n\n\n\nSince 2006 she has been habilitated at the University of Maribor, and Life Sciences (she has been a full professor since 2016) for the field of Farm management. She holds several courses at all levels of study. She is currently the head of the 1st-degree study Agriculture Economics and Rural Development and the Vice Dean for Education.\n\n\n\nHer research includes the development of decision support tools and systems for farm management (simulation modeling, multicriteria decision analysis, option models, risk management), the economics of agricultural production, and other modern methods of operational research.",institutionString:"University of Maribor",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Maribor",institutionURL:null,country:{name:"Slovenia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1360",title:"Production Engineering",slug:"technology-industrial-engineering-production-engineering"}],chapters:[{id:"76130",title:"Application of Lean in a Small and Medium Enterprise",doi:"10.5772/intechopen.97059",slug:"application-of-lean-in-a-small-and-medium-enterprise",totalDownloads:241,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Application of lean principles in manufacturing as well as services has been revolutionizing the operations for more than five decades. Many large as well as small enterprises have implemented lean and reported benefits in both direct and indirect activities of business. Due to advent of digital technologies and better understanding of process improvement approaches made lean much more effective across many sectors. In this chapter, we highlight various elements of lean and its application to a small enterprise in food processing sector in India. We draw some useful insights based on the implementation of lean and challenges faced by SMEs.",signatures:"Venkataramanaiah Saddikuti, Saketh Saddikuti Venkat and Ganesh Babu Shanmugam",downloadPdfUrl:"/chapter/pdf-download/76130",previewPdfUrl:"/chapter/pdf-preview/76130",authors:[{id:"292211",title:"Associate Prof.",name:"Venkataramanaiah",surname:"Saddikuti",slug:"venkataramanaiah-saddikuti",fullName:"Venkataramanaiah Saddikuti"},{id:"337430",title:"Mr.",name:"Saketh",surname:"Saddikuti Venkat",slug:"saketh-saddikuti-venkat",fullName:"Saketh Saddikuti Venkat"},{id:"349737",title:"Mr.",name:"Ganesh Babu",surname:"Shanmugam",slug:"ganesh-babu-shanmugam",fullName:"Ganesh Babu Shanmugam"}],corrections:null},{id:"75200",title:"Lean and Kaizen: The Past and the Future of the Methodologies",doi:"10.5772/intechopen.96169",slug:"lean-and-kaizen-the-past-and-the-future-of-the-methodologies",totalDownloads:417,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Lean and Kaizen improvement methodologies have been in the entrepreneurship spotlight for a long time. They can be adopted by any kind of enterprise, and they succeed in producing better long-term results, improving their performance, but most important, influencing the philosophy of the organizations implemented. In this research, many case studies and success stories of companies implementing Kaizen or/and Lean methodologies, or even the new Lean Kaizen methodology, will be introduced. We attempt to evaluate the performance of Lean and Kaizen implemented companies and distinguish the elements that made the difference. Maybe, it is some specific tool, or an aspect in the culture that was enhanced, since the implementation of these business process improvement methodologies. Finally, thoughts and estimations will be presented, regarding the future of these methodologies, in the unstable and rapidly changing economic environment.",signatures:"Vasileios Ismyrlis",downloadPdfUrl:"/chapter/pdf-download/75200",previewPdfUrl:"/chapter/pdf-preview/75200",authors:[{id:"190036",title:"Dr.",name:"Vasileios",surname:"Ismyrlis",slug:"vasileios-ismyrlis",fullName:"Vasileios Ismyrlis"}],corrections:null},{id:"76432",title:"Introduction to Lean Waste and Lean Tools",doi:"10.5772/intechopen.97573",slug:"introduction-to-lean-waste-and-lean-tools",totalDownloads:325,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In the turbulent and complex business environments, many Indian SMEs are facing stiff competition in the domestic as well as in the global market from their multinational counterpart. The concept of lean has gained prominence due to the fact that the resource based competitive advantages are no longer sufficient in this economy. Hence, lean is no longer merely an option but rather a core necessity for engineering industries situated in any part of the globe, if they have to compete successfully. Lean Manufacturing (LM) which provides new opportunities to create and retain greater value from the employee of the industry based on their core business competencies. The challenge of capturing, organizing, and disseminating throughout the aggregate business unit is a huge responsibility of the top management. The success of any industry depends on how well it can manage its resources and translate in to action. The adoption of lean manufacturing through effective lean practices depends on interpretations of past experiences and present information resides in the industry. Generally, in an industry, some tangible and intangible factors exist in the form of non-value adding activities which hinder the smooth lean implementation are known as lean manufacturing barriers (LMBs).",signatures:"Shyam Sunder Sharma and Rahul Khatri",downloadPdfUrl:"/chapter/pdf-download/76432",previewPdfUrl:"/chapter/pdf-preview/76432",authors:[{id:"311981",title:"Dr.",name:"Shyam Sunder",surname:"Sharma",slug:"shyam-sunder-sharma",fullName:"Shyam Sunder Sharma"},{id:"338090",title:"Mr.",name:"Rahul",surname:"Khatri",slug:"rahul-khatri",fullName:"Rahul Khatri"}],corrections:null},{id:"76093",title:"Effect of Lean Practices on Organizational Performance",doi:"10.5772/intechopen.96482",slug:"effect-of-lean-practices-on-organizational-performance",totalDownloads:164,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The study focuses on the analysis of the direct effect of Lean Manufacturing (LM) practices on operational performance in manufacturing industry. A model for evaluating the effect of LM is developed taking into consideration as a fundamental variable that affects the causal relationship between LM practices and operational performance. A structural equation model was proposed and investigated across the manufacturing industry in India. A structured survey questionnaire was used to collect empirical data from 400 Indian companies. A total of 203 usable responses were obtained giving a response rate of 53%. The data was analyzed using SPSS- AMOS software. The results revealed that LM practices directly and positively affected operational performance. The results indicated that the structural equation model remained invariant across the Industry. The study provides further evidence to managers and practitioner on the effect of LM practices on operational performance in developing countries like India.",signatures:"Lokpriya Mohanrao Gaikwad and Vivek K. Sunnapwar",downloadPdfUrl:"/chapter/pdf-download/76093",previewPdfUrl:"/chapter/pdf-preview/76093",authors:[{id:"246830",title:"Prof.",name:"Lokpriya Mohanrao",surname:"Gaikwad",slug:"lokpriya-mohanrao-gaikwad",fullName:"Lokpriya Mohanrao Gaikwad"},{id:"251857",title:"Dr.",name:"Vivek K.",surname:"Sunnapwar",slug:"vivek-k.-sunnapwar",fullName:"Vivek K. Sunnapwar"}],corrections:null},{id:"75353",title:"Enhancement of Textile Supply Chain Performance through Optimal Capacity Planning",doi:"10.5772/intechopen.96292",slug:"enhancement-of-textile-supply-chain-performance-through-optimal-capacity-planning",totalDownloads:273,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Manufacturing companies in the textile and apparel field face stiff competition due to the globalization of trade between suppliers, producers and customers. To meet this challenge, they need to be efficient by adopting new lean manufacturing approaches and new analysis and management tools leading to more flexible and agile production and distribution processes. For the textile and apparel industry, where products’ life cycle is short due to fashion changes, a new integrated approach of production and distribution planning is needed. Based on linear programming techniques and integrating subcontracting activities, our approach takes into account the characteristics of demand, including its short life cycle, seasonality and fashion effect. For these reasons, a sequential approach is adopted, combining tactical and operational decision levels for production and distribution activities, in order to satisfy customer needs at lower cost by reacting quickly to changes and delivering on time. The deployed approach is structured according to the DMAIC lean tool. Validated on real instances, this approach proves its efficiency by achieving cost reduction when internal production capacity is adequately and efficiently planned.",signatures:"Imen Safra and Kaouther Ghachem",downloadPdfUrl:"/chapter/pdf-download/75353",previewPdfUrl:"/chapter/pdf-preview/75353",authors:[{id:"336845",title:"Assistant Prof.",name:"safra",surname:"Imen",slug:"safra-imen",fullName:"safra Imen"},{id:"345868",title:"Dr.",name:"Kaouther",surname:"Ghachem",slug:"kaouther-ghachem",fullName:"Kaouther Ghachem"}],corrections:null},{id:"75657",title:"From Lean Manufacturing to Lean Construction: How Principles, Tools, and Techniques Evolved",doi:"10.5772/intechopen.96191",slug:"from-lean-manufacturing-to-lean-construction-how-principles-tools-and-techniques-evolved",totalDownloads:342,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Lean manufacturing first emerged in the automotive industry. However, low productivity and low efficiency in production are major problems for the majority of industries relying on a heavy workforce. Being one of these, the construction industry suffers from low productivity rates along with inefficient work practices. To prevent those, the industry has shifted its focus from the traditional approach to a more innovative one, which is called Lean construction. Lean construction aims to maximize value while minimizing waste. Therefore, it intends to create safer, smoother, and more efficient processes to eliminate waste. This chapter focuses on Lean construction and highlights the generic Lean tools and techniques practiced in the construction industry indicating its historical journey from Lean manufacturing. The chapter aims to raise awareness towards the efficiency of Lean methods in the construction industry with respect to practices observed in manufacturing.",signatures:"Sevilay Demirkesen",downloadPdfUrl:"/chapter/pdf-download/75657",previewPdfUrl:"/chapter/pdf-preview/75657",authors:[{id:"338001",title:"Assistant Prof.",name:"Sevilay",surname:"Demirkesen",slug:"sevilay-demirkesen",fullName:"Sevilay Demirkesen"}],corrections:null},{id:"75939",title:"Model-Based Enterprise Continuous Improvement",doi:"10.5772/intechopen.96856",slug:"model-based-enterprise-continuous-improvement",totalDownloads:253,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The enterprise reengineering based on enterprise modelling is usually carried out within the framework of conventional projects. This leads to relatively long projects that are not compatible with a highly variable economic environment. The objective of the evolution management presented here is to use enterprise modelling and all the benefits it brings in a framework that allows for more continuous improvement than is generally observed. The proposed architecture is made up of three levels: a strategic level based on performance measurement, a tactical level that manages system migration and is based on enterprise models, and an operational level consisting of managing a portfolio of evolution projects. Together, these allow a shorter set of projects to be carried out, while remaining coherent and aligned with the company’s strategy. This approach puts enterprise modelling methods and continuous improvement/Lean management approaches into perspective, allowing complementarities and opening up interesting perspectives concerning enterprise re-engineering methods.",signatures:"Bruno Vallespir and Anne Zouggar-Amrani",downloadPdfUrl:"/chapter/pdf-download/75939",previewPdfUrl:"/chapter/pdf-preview/75939",authors:[{id:"345188",title:"Prof.",name:"Bruno",surname:"Vallespir",slug:"bruno-vallespir",fullName:"Bruno Vallespir"},{id:"348617",title:"Dr.",name:"Anne",surname:"Zougar-Amrani",slug:"anne-zougar-amrani",fullName:"Anne Zougar-Amrani"}],corrections:null},{id:"75617",title:"Single Minute Exchange of Dies: Classical Tool of Lean Manufacturing",doi:"10.5772/intechopen.96665",slug:"single-minute-exchange-of-dies-classical-tool-of-lean-manufacturing",totalDownloads:311,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Effective utilization of the resources is the need of an hour particularly when it comes to the manufacturing industry. It is having a paramount importance to have a proper utilization of the resources, on the same line in any manufacturing industries to reduce the setup time is also one of the ways to do so. Single Minute Exchange of Dies (SMED) is one of the classical method which is normally used to reduce the setup time. In this technique complete videography of the existing changeover is done and then by analyzing it waste activities identified and other improvement plant has been done in each iteration. The chapter also showcases the SMED technique applications in a gear industry. Remarkable resources and results have been achieved through the implementation of classical tool of Lean manufacturing is made.",signatures:"Yash Dave",downloadPdfUrl:"/chapter/pdf-download/75617",previewPdfUrl:"/chapter/pdf-preview/75617",authors:[{id:"338618",title:"Dr.",name:"Yash",surname:"Dave",slug:"yash-dave",fullName:"Yash Dave"}],corrections:null},{id:"75408",title:"Lean Manufacturing as a Strategy for Continuous Improvement in Organizations",doi:"10.5772/intechopen.96427",slug:"lean-manufacturing-as-a-strategy-for-continuous-improvement-in-organizations",totalDownloads:359,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The implementation of lean manufacturing is one of the most discussed and studied topics in management; references are at the business, educational and public levels. However, the changes faced in the fourth industrial revolution generate challenges that will only encounter solution through innovative efforts and industrial improvements as well as a radical change in our way of interacting. In the current revolution, there are digital changes that cause ruptures in social, economic and political aspects, and the administrative process is part of it, this chapter proposes to analyze the implementation of lean manufacturing in the process of continuous improvement in business organizations through a literary review of the implementation of tools.",signatures:"María Marcela Solís-Quinteros, Carolina Zayas-Márquez, Luis Alfredo Ávila-López and Teresa Carrillo-Gutirrez",downloadPdfUrl:"/chapter/pdf-download/75408",previewPdfUrl:"/chapter/pdf-preview/75408",authors:[{id:"281004",title:"Dr.",name:"María Marcela",surname:"Solís-Quinteros",slug:"maria-marcela-solis-quinteros",fullName:"María Marcela Solís-Quinteros"},{id:"343581",title:"Dr.",name:"Luis Alfredo",surname:"Avila-Lopez",slug:"luis-alfredo-avila-lopez",fullName:"Luis Alfredo Avila-Lopez"},{id:"343697",title:"Dr.",name:"Carolina",surname:"Zayas-Márquez",slug:"carolina-zayas-marquez",fullName:"Carolina Zayas-Márquez"},{id:"343698",title:"Dr.",name:"Teresa",surname:"Carrillo-Gutiérrez",slug:"teresa-carrillo-gutierrez",fullName:"Teresa Carrillo-Gutiérrez"}],corrections:null},{id:"74769",title:"Development of Integrated Lean Six Sigma-Baldrige Framework for Manufacturing Waste Minimization: A Case of NAS Foods Plc",doi:"10.5772/intechopen.95279",slug:"development-of-integrated-lean-six-sigma-baldrige-framework-for-manufacturing-waste-minimization-a-c",totalDownloads:375,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"The aim of this study objective is to develop an integrated constant quality improvement model so as to minimize unwanted biscuit processing industry wastes. The method used was lean- six- sigma elements to define measure and improve unwanted process company wastes. In other word, Baldrige with six-sigma were created to define, measure and improve management perspectives. The tasks were integrated using both quantitative and qualitative analyzing tools implementing mixed strategies. The result was improved by using FMEA analysis was carried out at each stage of the existing process used to determine the failure of the process and to analyses and improve the production quality. The SPSS software was also used. In the finding section, the correlation and regression analysis has shown that there is strong relationship between each variance. There are different wastes that identified in six sigma (DMAIC) on NAS food Plc as a result; the value of waste ratio indicated is 36.7%. This show non-lean of the food industry is practiced. The defect of the company also calculated and defect per million are 67,308. This shows that the biscuit production has a production capability with a failure of 67,308 every 1000,000 productions it high failure rate. The contribution of the paper has indicated that there are limited studies were conducted so far to implement waste minimization tools like six-sigma, lean and MBNQA framework approach integration for food processing industry.",signatures:"Kassu Jilcha Sileyew and Selamawit Gebreyohanis",downloadPdfUrl:"/chapter/pdf-download/74769",previewPdfUrl:"/chapter/pdf-preview/74769",authors:[{id:"292841",title:"Ph.D.",name:"Kassu",surname:"Jilcha Sileyew",slug:"kassu-jilcha-sileyew",fullName:"Kassu Jilcha Sileyew"},{id:"338417",title:"Ms.",name:"Selamawit",surname:"Gebreyohanis",slug:"selamawit-gebreyohanis",fullName:"Selamawit Gebreyohanis"}],corrections:null},{id:"75149",title:"Analysis, an Anathema: Is That a Fervent Diatribe of Lean?",doi:"10.5772/intechopen.96166",slug:"analysis-an-anathema-is-that-a-fervent-diatribe-of-lean-",totalDownloads:242,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Should there be an understanding that rigor in analysis must be out-of-bounds for Lean initiatives? Will this rigor not facilitate a benchmarking of Lean initiatives? Why not a Lean initiative cause-consequence assessment not performed for building future fault tolerance? The effectiveness of a company’s strategy is critical to its success or failure. Lean strategy seems to be claimed as a widely recognized factor for business success and competitive advantage. However, empirical evidences do not promote the idea that Lean has delivered results every time. Study results indicate that success or failure of lean initiatives strongly depends on how companies approach it and on whether company has created their own curated philosophy towards Lean. Then, success is not dependent alone on a strategy, but on how daily operations are aligned to strategy. This chapter aims to address the above questions and a greater number of questions that we experience on a day-to-day basis with regard to Lean applications in the real world. Chapter Learning Objectives: Understanding Lean, Lean failure modes, and Lean initiative precautions.",signatures:"Sajit Jacob and Krishnamurthy Kothandaraman",downloadPdfUrl:"/chapter/pdf-download/75149",previewPdfUrl:"/chapter/pdf-preview/75149",authors:[{id:"299036",title:"Mr.",name:"Sajit",surname:"Jacob",slug:"sajit-jacob",fullName:"Sajit Jacob"},{id:"299213",title:"Dr.",name:"Krishnamurthy",surname:"Kothandaraman",slug:"krishnamurthy-kothandaraman",fullName:"Krishnamurthy Kothandaraman"}],corrections:null},{id:"76883",title:"Lean Manufacturing towards Green Manufacturing Practices and Its Implementation in SME’s",doi:"10.5772/intechopen.97389",slug:"lean-manufacturing-towards-green-manufacturing-practices-and-its-implementation-in-sme-s",totalDownloads:223,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The manufacturing SMEs are facing the burden of non-equilibrium of the supply–demand chain along with the global change in the climate. Several SMEs are looking for a substitute that can create a balance between performance and the environment. In spite of numerous studies related to green and lean that has been evolved, none of them is able to clearly define the spheres of green and lean. Here in this chapter, there is an exploration of advancement of lean and green manufacturing and its impact on other sectors. It also highlights the methodology adopted in implementing the same. This chapter recognizes the commonalities between lean and green approaches, the collaboration and impact, techniques involved. Also, the impediments and perplexities confronted by the manufacturing sector are examined. Further, this gives a better understanding of the challenges before implementing lean with green. This chapter also recognizes possible gaps in the literature that will help to eliminate the barrier toward this Neo manufacturing.",signatures:"J.P. Rishi",downloadPdfUrl:"/chapter/pdf-download/76883",previewPdfUrl:"/chapter/pdf-preview/76883",authors:[{id:"339553",title:"Dr.",name:"J.P.",surname:"Rishi",slug:"j.p.-rishi",fullName:"J.P. Rishi"}],corrections:null},{id:"75839",title:"Lean Manufacturing Practices and Environmental Performance",doi:"10.5772/intechopen.96973",slug:"lean-manufacturing-practices-and-environmental-performance",totalDownloads:359,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Lean manufacturing is considered a rewarding production strategy due to its positive effects on organizational and economic efficiency in various industries. Given the growing ecological consciousness, environmental achievements of lean manufacturing also incorporate a strong economic relevance. The main objective of this chapter is, therefore, to investigate the impact of lean manufacturing practices on environmental performance and the existing coherences between Lean and ecologically oriented variables such as resource usage, energy consumption, and air pollution. The methodology is literature review evaluating the findings of research in this sphere. Besides the discussion of its principles and methods, current trends and challenges regarding lean production as a business model that supports eco-efficiency are presented. The implications of this study will allow executives to better recognize and simultaneously solve both the economic and environmental problems posed by their companies.",signatures:"Ruhet Genç",downloadPdfUrl:"/chapter/pdf-download/75839",previewPdfUrl:"/chapter/pdf-preview/75839",authors:[{id:"340234",title:"Prof.",name:"Ruhet",surname:"Genç",slug:"ruhet-genc",fullName:"Ruhet Genç"}],corrections:null},{id:"78284",title:"Circular and Lean Food Supply Chains",doi:"10.5772/intechopen.99769",slug:"circular-and-lean-food-supply-chains",totalDownloads:187,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Circular economy (CE) refers to the industrial economy that aims to achieve enriched sustainability through restorative objects and supply chain design. Many governments have put in place different initiatives in line with the CE. On the other hand, the term Lean operations refers to the reduction of the non-value adding activities and waste in a supply chain. The food sector has been criticized for its sustainability and circularity due to the high levels of food and packaging waste and at the same time the increasing costs. Although food supply chain entities have started to implement circular economy and lean practices, the current efforts do not seem to be sufficient to achieve a circular and lean food system. The aim of this chapter is to explore the possibility of a circular and at the same lean food supply chain.",signatures:"Stella Despoudi",downloadPdfUrl:"/chapter/pdf-download/78284",previewPdfUrl:"/chapter/pdf-preview/78284",authors:[{id:"338855",title:"Dr.",name:"Stella",surname:"Despoudi",slug:"stella-despoudi",fullName:"Stella Despoudi"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"2020",title:"New Technologies",subtitle:"Trends, Innovations and Research",isOpenForSubmission:!1,hash:"170d84903f390df23023d0623d8577d3",slug:"new-technologies-trends-innovations-and-research",bookSignature:"Constantin Volosencu",coverURL:"https://cdn.intechopen.com/books/images_new/2020.jpg",editedByType:"Edited by",editors:[{id:"1063",title:"Prof.",name:"Constantin",surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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She was previously president of the European Society of Comparative Literature, deputy head of the Department of English Studies at her university, and an evaluator in various international research programs, including Vice-Chair at EU Unit REA.A2, Marie Skłodowska-Curie European Postdoctoral Fellowships, Social Sciences and Humanities (SOC).",institutionString:"Complutense University of Madrid",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"4",institution:{name:"Complutense University of Madrid",institutionURL:null,country:{name:"Spain"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"442",title:"Organizational Research",slug:"organizational-research"}],chapters:[{id:"38278",title:"Social Research Methods in Higher Education: A Critical Analysis of Methodological Issues and Emerging Trends at the Zimbabwe Open University",slug:"social-research-methods-in-higher-education-a-critical-analysis-of-methodological-issues-and-emergin",totalDownloads:6844,totalCrossrefCites:0,authors:[{id:"116563",title:"Mr.",name:"Caleb",surname:"Kangai",slug:"caleb-kangai",fullName:"Caleb Kangai"}]},{id:"38279",title:"Methodology Transfers Between Social Sciences and Humanities in Relation to Natural Sciences, Technology and Government Policy",slug:"methodology-transfers-between-social-sciences-and-humanities-in-relation-to-natural-sciences-technol",totalDownloads:3344,totalCrossrefCites:0,authors:[{id:"115410",title:"Prof.",name:"Hajime",surname:"Eto",slug:"hajime-eto",fullName:"Hajime Eto"}]},{id:"38280",title:"Causality in Social Studies Education",slug:"causality-in-social-studies-education",totalDownloads:1718,totalCrossrefCites:0,authors:[{id:"114537",title:"Dr.",name:"Bayram",surname:"Tay",slug:"bayram-tay",fullName:"Bayram Tay"}]},{id:"38281",title:"The Assumption of Non-Gaussianity in Natural and Social Sciences and Its Influence on Detection of Causal Relationships",slug:"the-assumption-of-non-gaussianity-in-natural-and-social-sciences-and-its-influence-on-detection-of-c",totalDownloads:1900,totalCrossrefCites:0,authors:[{id:"139164",title:"Dr.",name:"Katerina",surname:"Hlavackova-Schindler",slug:"katerina-hlavackova-schindler",fullName:"Katerina Hlavackova-Schindler"}]},{id:"38282",title:"Qualitative Research: The Toolkit of Theories in the Social Sciences",slug:"qualitative_research_toolkit_theories_social_sciences",totalDownloads:2575,totalCrossrefCites:0,authors:[{id:"118755",title:"Dr.",name:"Sylvain",surname:"Cibangu",slug:"sylvain-cibangu",fullName:"Sylvain Cibangu"}]},{id:"38283",title:"A Simulation Approach to Validate Models Derived from Observational Studies",slug:"a-simulation-approach-to-validate-models-derived-from-observational-studies",totalDownloads:1415,totalCrossrefCites:0,authors:[{id:"116407",title:"Prof.",name:"Pierre",surname:"Robillard",slug:"pierre-robillard",fullName:"Pierre Robillard"}]},{id:"38284",title:"Cartographic Generalization Applied to Social Networks Maps in the City of Curitiba in Brazil",slug:"cartographic-generalization-applied-to-social-networks-maps-in-the-city-of-curitiba-in-brazil",totalDownloads:1350,totalCrossrefCites:0,authors:[{id:"118639",title:"MSc.",name:"Renan Martins",surname:"Pombo",slug:"renan-martins-pombo",fullName:"Renan Martins Pombo"}]},{id:"38285",title:"Open-Source Tools for Data Mining in Social Science",slug:"open-source-tools-for-data-mining-in-social-science",totalDownloads:4154,totalCrossrefCites:3,authors:[{id:"119511",title:"Dr.",name:"Nikola",surname:"Štambuk",slug:"nikola-stambuk",fullName:"Nikola Štambuk"},{id:"119512",title:"Dr.",name:"Paško",surname:"Konjevoda",slug:"pasko-konjevoda",fullName:"Paško Konjevoda"}]},{id:"38286",title:"Applying Social Sciences Research for Public Benefit Using Knowledge Mobilization and Social Media",slug:"applying-social-sciences-research-for-public-benefit-using-knowledge-mobilization-and-social-media",totalDownloads:2721,totalCrossrefCites:0,authors:[{id:"113142",title:"Dr.",name:"David",surname:"Phipps",slug:"david-phipps",fullName:"David Phipps"},{id:"117588",title:"Ms.",name:"Krista",surname:"Jensen",slug:"krista-jensen",fullName:"Krista Jensen"},{id:"117589",title:"Mr.",name:"J. 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Net Promoter Score (NPS) is a popular metric used in a variety of industries for measuring customer advocacy. Introduced by Reichheld (2003), NPS measures the likelihood that an existing customer will recommend a company to another prospective customer. NPS is derived from a single question that may be included as part of a larger customer survey. The single question asks the customer to use a scale of 0 to 10 to rate their willingness and intention to recommend the company to another person. Ratings of 9 and 10 are used to characterize so-called ‘promoters,’ ratings of 0 through 6 characterize ‘detractors,’ and ratings of 7 and 8 characterize ‘passives.’ The NPS is calculated as the percentage of respondents that are promoters minus the percentage of respondents that are detractors.
\n\t\t\tThe idea behind the labels given to customers is as follows. Promoters are thought to be extremely satisfied customers that see little to no room for improvement, and consequently would offer persuasive recommendations that could lead to new revenue. The passive ratings, on the other hand, begin to hint at room for improvement and consequently the effectiveness of a recommendation from a Passive may be muted by explicit or implied caveats. Ratings at the low end are thought to be associated with negative experiences that might cloud a recommendation and likely scare off prospective new customers. Additional discussion on the long history of NPS can be found in Hayes (2008).
\n\t\t\tSome implementations of NPS methodology use reduced 5-point or 7-point scales that align with traditional Likert scales. However it is implemented, the hope is that movements in NPS are positively correlated with revenue growth for the company. While Reichheld’s research presented some evidence of that, other findings are not as corroborative (Kenningham et al., 2007). Regardless of whether there is a predictive relationship between NPS and revenue growth, implementing policies and programs within a company that improve NPS is an intuitively sensible thing to do [see, for example, Vavra (1997)]. A difficult and important question, however, is how to identify key drivers of NPS.
This chapter is an illustrative tutorial that demonstrates how a statistical classification model can be used to identify key drivers of NPS. Our premise is that the classification model, the data it operates on, and the analyses it provides could usefully form components of a Decision Support System that can not only provide both snapshot and longitudinal analyses of NPS performance, but also enable analyses that can help suggest company initiatives aimed toward lifting the NPS.
\n\t\t\tWe assume that the NPS question was asked as part of larger survey that also probed customer satisfaction levels with respect to various dimensions of the company’s services. We develop a predictive classification model for customer advocacy (promoter, passive or detractor) as a function of these service dimensions. A novelty associated with our classification model is the optional use of constraints on the parameter estimates to enforce a monotonic property. We provide a detailed explanation of how to fit the model using the SAS software package and show how the fitted model can be used to develop company policies that have promise for improving the NPS. Our primary objective is to teach an interested practitioner how to use customer survey data together with a statistical classifier to identify key drivers of NPS. We present a case study that is based on a real-life data collection and analysis project to illustrate the step-by-step process of building the linkage between customer satisfaction data and NPS.
\n\t\tIn this section we provide a brief review of logistic and multinomial regression. Allen and Rao (2000) is a good reference that contains more detail than we provide, and additionally has example applications pertaining to customer satisfaction modeling.
\n\t\t\tThe binomial logistic regression model assumes that the response variable is binary (0/1). This could be the case, for example, if a customer is simply asked the question “Would you recommend us to a friend?” Let \n\t\t\t\t\t\t
The binomial logistic regression model posits that \n\t\t\t\t\t\t
Model fitting for the binomial logistic regression model entails estimating the parameters \n\t\t\t\t\t\t
and the maximum likelihood estimate (MLE) of \n\t\t\t\t\t\t
Suppose now that the outcome variable has more than two categories. For example, suppose the responses \n\t\t\t\t\t\t
where \n\t\t\t\t\t\t
and the MLE of \n\t\t\t\t\t\t
Carestream Health, Inc. (CSH) was formed in 2007 when Onex Corporation of Toronto, Canada purchased Eastman Kodak Company’s Health Group and renamed the business as Carestream Health. They are an annual $2.5B company and a world leader in medical imaging (digital and film), healthcare information systems, dental imaging and dental practice management software, molecular imaging and non-destructive testing. Their customers include medical and dental doctors and staff and healthcare IT professionals in small offices and clinics to large hospitals and regional and national healthcare programs. A major company initiative is to create a sustainable competitive advantage by delivering the absolute best customer experience in the industry. Customer recommendations are key to growth in the digital medical space and no one has been able to do it consistently well. The foundation for taking advantage of this opportunity is to understand what\'s important to customers, measure their satisfaction and likelihood to recommend based on their experiences, and drive improvement.
\n\t\t\tWhile descriptive statistics such as trend charts, bar charts, averages and listings of customer verbatim comments are helpful in identifying improvement opportunities to improve the Net Promoter Score (NPS), they are limited in their power. First, they lack quantitative measurements of correlation between elements of event satisfaction and NPS. As a consequence, it is not clear what impact a given process improvement will have on a customer’s likelihood to recommend. Second, they lack the ability to view multi-dimensional relationships – they are limited to single factor inferences which may not sufficiently describe the complex relationships between elements of a customer’s experience and their likelihood to recommend.
\n\t\t\tThis section summarizes the use of multinomial logistic regression analyses that were applied to 5056 independent customer experience surveys from Jan 2009 – Jan 2010. Each survey included a question that measured (on a 5-point Likert scale) how likely it would be for the customer to recommend colleagues to purchase imaging solutions from CSH. Five other questions measured the satisfaction level (on a 7-point Likert scale) of the customer with CSH services obtained in response to an equipment or software problem. Key NPS drivers are revealed through the multinomial logistic regression analyses, and improvement scenarios for specific geographic and business combinations are mapped out. The ability to develop a quantitative model to measure the impact on NPS of potential process improvements significantly enhances the value of the survey data.
\n\t\t\tThe 5-point Likert response to the question about willingness to recommend is summarized in Table 1 below. CSH calculates a unique net promoter score from responses on this variable using the formula\n\t\t\t\t\t\t
Recommendation | \n\t\t\t\t\t\t\tInterpretation | \n\t\t\t\t\t\t
1 | \n\t\t\t\t\t\t\tWithout being asked, I will advise others NOT to purchase from you | \n\t\t\t\t\t\t
2 | \n\t\t\t\t\t\t\tOnly if asked, I will advise others NOT to purchase from you | \n\t\t\t\t\t\t
3 | \n\t\t\t\t\t\t\tI am neutral | \n\t\t\t\t\t\t
4 | \n\t\t\t\t\t\t\tOnly if asked, I will recommend others TO purchase from you | \n\t\t\t\t\t\t
5 | \n\t\t\t\t\t\t\tWithout being asked, I will recommend others TO purchase from you | \n\t\t\t\t\t\t
Meaning of Each Level of Recommendation Score
Let \n\t\t\t\t\t\t
The demographic covariates include the (global) region code, country code, business code and the customer job title. The demographic covariates are coded using the standard dummy variable coding technique. For example, region code utilizes 7 binary variables \n\t\t\t\t\t\t
Country code utilizes similar dummy variables, but because countries are nested within regions we use the notation\n\t\t\t\t\t\t
In the data set we have\n\t\t\t\t\t\t
Finally, job title utilizes 10 dummy variables \n\t\t\t\t\t\t
The customer satisfaction covariates are also coded using the dummy variable scheme. The data on these covariates are the responses to the survey questions identified as q79, q82a, q82b, q82d and q82f. These questions survey the customer satisfaction on ‘Overall satisfaction with the service event,’ ‘Satisfaction with CSH knowledge of customer business and operations,’ ‘Satisfaction with meeting customer service response time requirements,’ ‘Satisfaction with overall service communications,’ and ‘Satisfaction with skills of CSH employees,’ respectively.
\n\t\t\t\tSurvey questions q82c and q82e, which survey satisfaction with ‘Time it took to resolve the problem once work was started,’ and ‘Attitude of CSH employees’ were also considered as covariates, but they did not show themselves to be statistically significant in the model. Their absence from the model does not necessarily imply they are not important drivers of their overall satisfaction with CSH, but more likely that their influence is correlated with the other dimensions of overall satisfaction that are in the model. Each customer satisfaction covariate is scored by customers using a 7-point Likert scale (where ‘1’ indicates the customer is “extremely dissatisfied” and ‘7’ indicates “extremely satisfied”), and thus each utilizes 7 dummy variables in the coding scheme. We denote these dummy variables as\n\t\t\t\t\t\t
Assembling all of the covariates together, we then have a total of 77 covariates in\n\t\t\t\t\t\t
The SAS code for obtaining maximum likelihood estimates (MLEs) for the model parameters \n\t\t\t\t\t\t
Parm. | \n\t\t\t\t\t\t\tEst. | \n\t\t\t\t\t\t\tParm. | \n\t\t\t\t\t\t\tEst. | \n\t\t\t\t\t\t\tParm. | \n\t\t\t\t\t\t\tEst. | \n\t\t\t\t\t\t\tParm. | \n\t\t\t\t\t\t\tEst. | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-7.80 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.41 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.15 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.53 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-5.69 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.28 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.14 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-2.34 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.11 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.62 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.23 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.045 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.092 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.11 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-1.63 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.92 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.27 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.59 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.11 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t2.09 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.92 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.23 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.43 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.67 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.13 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.13 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.84 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.77 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.59 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.34 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.58 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.44 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.40 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.23 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.19 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.19 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.45 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.42 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t2.68 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.85 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.60 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.71 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.69 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.21 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.05 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.08 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.89 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.69 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.097 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.31 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.59 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.78 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.25 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.14 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.16 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.53 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.20 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.83 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.48 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.31 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.050 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.11 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.81 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.24 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t-.47 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.75 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
Maximum Likelihood Estimates of\n\t\t\t\t\t\t\t\t
The section of the PROC LOGISTIC output entitled ‘Type-3 Analysis of Effects’ characterizes the statistical significance of the covariates through p-values obtained by referencing a Wald chi-square test statistic to a corresponding null chi-square distribution. Table 3 shows the chi-square tests and the corresponding p-values, and it is seen that all covariate groups are highly significant contributors in the model.
\n\t\t\t\tOne way to assess model adequacy for multinomial logistic regression is to use the model to predict Y and then examine how well the predicted values match the true values of Y. Since the output of the model for each customer is an estimated probability distribution for Y, a natural predictor of Y is the mode of this distribution. We note that this predictor considers equal cost for all forms of prediction errors. More elaborate predictors could be derived by assuming a more complex cost model where, for example, the cost of predicting 5 when the actual value is 1 is higher than the cost of predicting 5 when the actual value is 4. Table 4, the so-called confusion matrix of the predictions, displays the cross classification of all 5056 customers based on their actual value of Y and the model-predicted value of Y.
\n\t\t\t\tCovariate Group | \n\t\t\t\t\t\t\tDegrees of Freedom | \n\t\t\t\t\t\t\tWald Statistic | \n\t\t\t\t\t\t\tp-value | \n\t\t\t\t\t\t
RC | \n\t\t\t\t\t\t\t6 | \n\t\t\t\t\t\t\t41.2 | \n\t\t\t\t\t\t\t< .0001 | \n\t\t\t\t\t\t
CC | \n\t\t\t\t\t\t\t16 | \n\t\t\t\t\t\t\t40.9 | \n\t\t\t\t\t\t\t< .01 | \n\t\t\t\t\t\t
BC | \n\t\t\t\t\t\t\t1 | \n\t\t\t\t\t\t\t7.9 | \n\t\t\t\t\t\t\t< .01 | \n\t\t\t\t\t\t
JT | \n\t\t\t\t\t\t\t9 | \n\t\t\t\t\t\t\t43.7 | \n\t\t\t\t\t\t\t< .0001 | \n\t\t\t\t\t\t
q79 | \n\t\t\t\t\t\t\t6 | \n\t\t\t\t\t\t\t84.8 | \n\t\t\t\t\t\t\t< .0001 | \n\t\t\t\t\t\t
q82a | \n\t\t\t\t\t\t\t6 | \n\t\t\t\t\t\t\t56.5 | \n\t\t\t\t\t\t\t< .0001 | \n\t\t\t\t\t\t
q82b | \n\t\t\t\t\t\t\t6 | \n\t\t\t\t\t\t\t34.4 | \n\t\t\t\t\t\t\t< .0001 | \n\t\t\t\t\t\t
q82d | \n\t\t\t\t\t\t\t6 | \n\t\t\t\t\t\t\t34.8 | \n\t\t\t\t\t\t\t< .0001 | \n\t\t\t\t\t\t
q82f | \n\t\t\t\t\t\t\t6 | \n\t\t\t\t\t\t\t39.9 | \n\t\t\t\t\t\t\t< .0001 | \n\t\t\t\t\t\t
Statistical Significance of Covariate Groups
Actual Y | \n\t\t\t\t\t\t\tPredicted Y | \n\t\t\t\t\t\t\tTotal | \n\t\t\t\t\t\t||||
1 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t4 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t||
1 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t7 | \n\t\t\t\t\t\t\t4 | \n\t\t\t\t\t\t\t4 | \n\t\t\t\t\t\t\t20 | \n\t\t\t\t\t\t
2 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t8 | \n\t\t\t\t\t\t\t48 | \n\t\t\t\t\t\t\t22 | \n\t\t\t\t\t\t\t7 | \n\t\t\t\t\t\t\t88 | \n\t\t\t\t\t\t
3 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t342 | \n\t\t\t\t\t\t\t486 | \n\t\t\t\t\t\t\t133 | \n\t\t\t\t\t\t\t966 | \n\t\t\t\t\t\t
4 | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t126 | \n\t\t\t\t\t\t\t1233 | \n\t\t\t\t\t\t\t723 | \n\t\t\t\t\t\t\t2082 | \n\t\t\t\t\t\t
5 | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t39 | \n\t\t\t\t\t\t\t705 | \n\t\t\t\t\t\t\t1156 | \n\t\t\t\t\t\t\t1900 | \n\t\t\t\t\t\t
Total | \n\t\t\t\t\t\t\t8 | \n\t\t\t\t\t\t\t13 | \n\t\t\t\t\t\t\t562 | \n\t\t\t\t\t\t\t2450 | \n\t\t\t\t\t\t\t2023 | \n\t\t\t\t\t\t\t5056 | \n\t\t\t\t\t\t
Confusion Matrix of Multinomial Logistic Regression Model
A perfect model would have a confusion matrix that is diagonal indicating the predicted value for each customer coincided identically with the true value. Consider the rows of Table 4 corresponding to Y=4 and Y=5. These two rows account for almost 80% of the customers in the sample. It can be seen that in both cases, the predicted value coincides with the actual value about 60% of the time. Neither of these two cases predicts Y=1 or Y=2, and only 4% of the time is Y=3 predicted. The mean values of the predicted Y when Y=4 and Y=5 are 4.28 and 4.59, respectively. The 7% positive bias for the case Y=4 is roughly offset by the 11.8% negative bias for the case Y=5.
\n\t\t\t\tLooking at the row of Table 4 corresponding to Y=3, we see that 86% of the time the predicted Y is within 1 of the actual Y. The mean value of the predicted Y is 3.77, indicating a 26% positive bias. Considering the rows corresponding to Y=1 and Y=2, where only about 2% of the customers reside, we see the model struggles to make accurate predictions, often over-estimating the actual value of Y. A hint as to the explanation for the noticeable over-estimation associated with the Y=1, Y=2 and Y=3 customers is revealed by examining their responses to the covariate questions. As just one example, the respective mean scores on question q79 (“Overall satisfaction with the service event”) are 3.8, 4.1 and 5.2. It seems a relatively large number of customers that give a low response to Y are inclined to simultaneously give favorable responses to the covariate questions on the survey. Although this might be unexpected, it can possibly be explained by the fact that the covariate questions are relevant to the most recent service event whereas Y is based on a customer’s cumulative experience.
\n\t\t\t\tOverall, Table 4 reflects significant lift afforded by the multinomial logistic regression model for predicting Y. For example, a model that utilized no covariate information would have a confusion matrix whose rows were constant, summing to the row total. In sum, we feel the accuracy of the model is sufficient to learn something about what drives customers to give high responses to Y, though perhaps not sufficient to learn as much about what drives customers to give low responses to Y.
\n\t\t\t\t\n\t\t\t\t\tFigure 1 is a graphical display of the slopes for each of the customer satisfaction covariates. The larger the coefficient value, the more detrimental the response level is to NPS. The y-axis is therefore labeled as ‘demerits.’
\n\t\t\t\tMLEs of Slopes for 7-Point Likert Scale Customer Satisfaction Covariates
In view of the ordinal nature of the customer satisfaction covariates, the slopes, which represent the effect of the Likert scale levels, should decrease monotonically. That is, the penalty for a ‘satisfied’ covariate value should be less than or equal to that of a ‘dissatisfied’ covariate value. As such, it would be logical to have the estimated values of the slopes display the monotone decreasing trend as the response level of the covariates ascends. Figure 1 shows that the unconstrained MLEs for the slopes associated with the customer satisfaction covariates nearly satisfy the desired monotone property, but not exactly. The aberrations are due to data deficiencies or minor model inadequacies and can be resolved by using a constrained logistic regression model introduced in the next section.
\n\t\t\tConsider the situation where the
In order to simplify our use of PROC NLP, it is convenient to work with a full-rank parameterization of the logistic regression model. Because countries are nested within regions, a linear dependency exists between the dummy variables corresponding to regions and countries within regions. We can eliminate the linear dependency by removing region from the model and specifying country to be non-nested factor. The result of this model reparameterization is that instead of 6 degrees of freedom in the model for regions and 16 degrees of freedom for countries nested within regions, we equivalently have 22 degrees of freedom for countries. For the same purpose, we also redefine the dummy variable coding used for other categorical and ordinal covariates by using a full rank parameterization scheme. In particular, we use
Constrained MLEs of Slopes for 7-Point Likert Scale Customer Satisfaction Covariates
Beginning with line 12 in the SAS code, PROC NLP is used to derive the MLEs of the parameters under the constrained parameter space. The ‘max’ statement (line 13) indicates the objective function is the log-likelihood function of the model and that it is to be maximized. The maximization is carried out using a Newton-Raphson algorithm, and the ‘parms’ statement (line 14) specifies initial values for the intercept and slope parameters. The SAS variables bq
Covariate | \n\t\t\t\t\t\t\tMLE of Slope | \n\t\t\t\t\t\t\tCovariate | \n\t\t\t\t\t\t\tMLE of Slope | \n\t\t\t\t\t\t||
Unconstrained | \n\t\t\t\t\t\t\tConstrained | \n\t\t\t\t\t\t\tUnconstrained | \n\t\t\t\t\t\t\tConstrained | \n\t\t\t\t\t\t||
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.92 | \n\t\t\t\t\t\t\t2.01 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.27 | \n\t\t\t\t\t\t\t1.27 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t2.09 | \n\t\t\t\t\t\t\t2.01 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.92 | \n\t\t\t\t\t\t\t.96 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.43 | \n\t\t\t\t\t\t\t1.43 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.67 | \n\t\t\t\t\t\t\t.73 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.84 | \n\t\t\t\t\t\t\t.82 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.77 | \n\t\t\t\t\t\t\t.73 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.58 | \n\t\t\t\t\t\t\t.57 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.44 | \n\t\t\t\t\t\t\t.42 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.19 | \n\t\t\t\t\t\t\t.19 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.19 | \n\t\t\t\t\t\t\t.19 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tStructural 0 | \n\t\t\t\t\t\t\tImplied 0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tStructural 0 | \n\t\t\t\t\t\t\tImplied 0 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t2.68 | \n\t\t\t\t\t\t\t2.56 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.85 | \n\t\t\t\t\t\t\t1.28 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.71 | \n\t\t\t\t\t\t\t.98 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.69 | \n\t\t\t\t\t\t\t1.28 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.05 | \n\t\t\t\t\t\t\t.98 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.08 | \n\t\t\t\t\t\t\t1.07 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.89 | \n\t\t\t\t\t\t\t.88 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.69 | \n\t\t\t\t\t\t\t.69 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.31 | \n\t\t\t\t\t\t\t.30 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.59 | \n\t\t\t\t\t\t\t.58 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.14 | \n\t\t\t\t\t\t\t.14 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.16 | \n\t\t\t\t\t\t\t.16 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tStructural 0 | \n\t\t\t\t\t\t\tImplied 0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tStructural 0 | \n\t\t\t\t\t\t\tImplied 0 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t1.31 | \n\t\t\t\t\t\t\t1.28 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.81 | \n\t\t\t\t\t\t\t.85 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.75 | \n\t\t\t\t\t\t\t.77 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.53 | \n\t\t\t\t\t\t\t.56 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.14 | \n\t\t\t\t\t\t\t.21 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t.23 | \n\t\t\t\t\t\t\t.21 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tStructural 0 | \n\t\t\t\t\t\t\tImplied 0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
Unconstrained and Constrained Slope MLEs of Customer Satisfaction Covariates
\n\t\t\t\t\tTable 5 provides a side-by-side comparison of the constrained and unconstrained MLEs for the slopes of the customer satisfaction covariates, and Figure 2 is a plot that shows the monotone behavior of the constrained estimates. There is very little difference between the unconstrained and constrained MLEs for the demographic covariates. Recall that for the unconstrained MLEs, the zero for the slope of the last level of each covariate is a structural zero resulting from the non-full rank dummy variable coding used when fitting the model. In the case of the constrained MLEs, the slopes of the last levels of the covariates are implied zeros resulting from the full-rank dummy variable coding used when fitting the model. Table 5 shows that incorporating the constraints do not lead to a substantial change in the estimated slopes. In an indirect way, this provides a sanity check of the proposed model. We will use the constrained estimates for the remainder of the case study.
\n\t\t\tA purely empirical way to compute NPS is to use the observed distribution (based on all 5,056 survey responses) of
We illustrated potential pathways to improve the overall NPS score, but this can also be done with specific sub-populations in mind. For example, if the first region was under study, then one could simply adjust the demographic covariates as illustrated in section 3.4.2 before implementing scenarios adjustments.
\n\t\t\t\tPredicted NPS for Different Scenarios
Scenario | \n\t\t\t\t\t\t\tBrief Description | \n\t\t\t\t\t\t
1 | \n\t\t\t\t\t\t\tFor each of q79, q82a, q82b, q82d and q82f, alter the distributions of their responses by reassigning the probability of a neutral response (4) equally to the probability of responses (5), (6) and (7) | \n\t\t\t\t\t\t
2 | \n\t\t\t\t\t\t\tReplace the response distribution for sub-elements q82a, q82b, and q82d with what was observed for q82f (which was the sub-element that had the most favorable response distribution) | \n\t\t\t\t\t\t
3 | \n\t\t\t\t\t\t\tMake the response distribution for each of q82a, q82b, q82d and q82f perfect by placing all the probability on response (7) | \n\t\t\t\t\t\t
4 | \n\t\t\t\t\t\t\tImprove the response distribution for each of q82a, q82b, q82d and q82f by placing all the probability equally on responses (6) and (7) | \n\t\t\t\t\t\t
5 | \n\t\t\t\t\t\t\tImprove the response distribution for q79 by placing all the probability on response (7) | \n\t\t\t\t\t\t
6 | \n\t\t\t\t\t\t\tImprove the response distribution for q82a by placing all the probability on response (7) | \n\t\t\t\t\t\t
7 | \n\t\t\t\t\t\t\tImprove the response distribution for q82b by placing all the probability on response (7) | \n\t\t\t\t\t\t
8 | \n\t\t\t\t\t\t\tImprove the response distribution for q82d by placing all the probability on response (7) | \n\t\t\t\t\t\t
9 | \n\t\t\t\t\t\t\tImprove the response distribution for q82f by placing all the probability on response (7) | \n\t\t\t\t\t\t
10 | \n\t\t\t\t\t\t\tImprove the response distribution for each of q79, q82a, q82b, q82d and q82f by distributing the probability of response (1) equally on responses (2)-(7) | \n\t\t\t\t\t\t
11 | \n\t\t\t\t\t\t\tImprove the response distribution for each of q79, q82a, q82b, q82d and q82f by distributing the sum of the probability of responses (1) and (2) equally on responses (3)-(7) | \n\t\t\t\t\t\t
12 | \n\t\t\t\t\t\t\tImprove the response distribution for each of q79, q82a, q82b, q82d and q82f by distributing the sum of the probability of responses (1), (2) and (3) equally on responses (4)-(7) | \n\t\t\t\t\t\t
13 | \n\t\t\t\t\t\t\tSimulate making Business Code 2 as good as Business Code 1 by setting | \n\t\t\t\t\t\t
14 | \n\t\t\t\t\t\t\tImprove the response distributions of q79, q82a, q82b, q82d, and q82f by replacing them by the average across the different Region Codes, excluding the worst Region Code | \n\t\t\t\t\t\t
15 | \n\t\t\t\t\t\t\tImprove the response distributions of q79, q82a, q82b, q82d, and q82f by replacing them by the average across the different Region Codes, excluding the two worst Region Codes | \n\t\t\t\t\t\t
16 | \n\t\t\t\t\t\t\tImprove the response distributions of q79, q82a, q82b, q82d, and q82f by replacing them all by the observed, respective, distributions for Region Code 2 (which was the region that had the most favorable response distribution) | \n\t\t\t\t\t\t
Implementation Detail for Each Scenario
Alternative measures to NPS of customer advocacy include customer satisfaction (CSAT) and Customer Effort Score (CES) (Dixon et al., 2010). CES is measured on a 5-point scale and is intended to capture the effort required by a customer to resolve an issue through a contact-center or self-service channel. (Dixon et al., 2010) compared the predictive power of CSAT, NPS and CES on service customers\' intention to do repeat business, increase their spending, and speak positively about the company. They concluded that CSAT was a relatively poor predictor, while CES was the strongest. NPS ranked in the middle.
\n\t\t\tThe choice of which customer advocacy measure to use depends on many factors such as the type of company-to-customer relationship, the degree to which recommendations (for or against a company) influence a purchase decision, and whether the measures will be complemented by other customer feedback. To gain an in-depth understanding of customers\' experiences and how to improve them may require multiple indicators. In the end, it is the action taken to drive improvements that customers value that is most critical.
\n\t\t\tOur case study validates the feasibility for using a multinomial logistic regression model as a means to identify key drivers of NPS, though it is clear that the same methodology could be employed with alternative measures of customer advocacy. Improvement teams at CSH have used this model to prioritize projects relative to their expected impacts on NPS. A novel aspect of our model development was the implementation of monotone constraints on the slope parameters of the ordinal covariates. Our illustrative SAS code showing how to impose the constraints on the maximum likelihood estimates should be of significant help to practitioners interested in doing the same thing.
\n\t\tdata indata;
infile \'C:\\CarestreamHealth\\indata.txt\';
input RC CC BC JT Y q79 q82a q82b q82d q82f;
proc logistic data=indata;
class RC CC BC JT
q79 q82a q82b q82d q82f/param=glm;
model Y = RC CC(RC) BC JT
q70 q79 q82a q82b q82d q82f;
data indata;
set indata;
array cc{23} cc1-cc23; do i=1 to 23; if CC=i then cc{i}=1; else cc{i}=0;end;
if BC=1 then bc1=1;else bc1=0;
array jt{9} jt1-jt9; do i=1 to 9; if JT=i then jt{i}=1; else jt{i}=0;end;
array q{6} q1-q6; do i=1 to 6; if q79=i then q{i}=1; else q{i}=0;end;
array a{6} a1-a6; do i=1 to 6; if q82a=i then a{i}=1; else a{i}=0;end;
array b{6} b1-b6; do i=1 to 6; if q82b=i then b{i}=1; else b{i}=0;end;
array d{6} d1-d6; do i=1 to 6; if q82d=i then d{i}=1; else d{i}=0;end;
array f{6} f1-f6; do i=1 to 6; if q82f=i then f{i}=1; else f{i}=0;end;
run;
proc nlp data=indata;
max loglik;
parms alp1=-7, alp2=-5, alp3=-2, alp4=-1, bcc1-bcc10=0, bcc12-bcc23=0, bbc1=0, bj1-bj9=0, bq1-bq6=0, ba1-ba6=0, bb1-bb6=0,bd1-bd6=0, bf1-bf6=0;
bounds 0 <= bq6,0 <= ba6,0 <= bb6,0 <= bd6,0 <= bf6;
lincon 0<=alp4-alp3, 0<=alp3-alp2, 0<=alp2-alp1;
lincon 0<= bq5-bq6, 0<= bq4-bq5, 0<= bq3-bq4, 0<= bq2-bq3, 0<= bq1-bq2;
lincon 0<= ba5-ba6, 0<= ba4-ba5, 0<= ba3-ba4, 0<= ba2-ba3, 0<= ba1-ba2;
lincon 0<= bb5-bb6, 0<= bb4-bb5, 0<= bb3-bb4, 0<= bb2-bb3, 0<= bb1-bb2;
lincon 0<= bd5-bd6, 0<= bd4-bd5, 0<= bd3-bd4, 0<= bd2-bd3, 0<= bd1-bd2;
lincon 0<= bf5-bf6, 0<= bf4-bf5, 0<= bf3-bf4, 0<= bf2-bf3, 0<= bf1-bf2;
tp=cc1*bcc1+cc2*bcc2+cc3*bcc3+cc4*bcc4+cc5*bcc5+cc6*bcc6+cc7*bcc7+cc8*bcc8+cc9*bcc9+cc10*bcc10+cc12*bcc12+cc13*bcc13+cc14*bcc14+cc15*bcc15+cc16*bcc16+cc17*bcc17+cc18*bcc18+cc19*bcc19+cc20*bcc20+cc21*bcc21+cc22*bcc22+cc23*bcc23+bc1*bbc1+jt1*bj1+jt2*bj2+jt3*bj3+jt4*bj4+jt5*bj5+jt6*bj6+jt7*bj7+jt8*bj8+jt9*bj9+q1*bq1+q2*bq2+q3*bq3+q4*bq4+q5*bq5+q6*bq6+a1*ba1+a2*ba2+a3*ba3+a4*ba4+a5*ba5+a6*ba6+b1*bb1+b2*bb2+b3*bb3+b4*bb4+b5*bb5+b6*bb6+d1*bd1+d2*bd2+d3*bd3+d4*bd4+d5*bd5+d6*bd6+f1*bf1++f2*bf2+f3*bf3+f4*bf4+f5*bf5+f6*bf6;
pi1=exp(alp1+tp)/(1+exp(alp1+tp));pi2=exp(alp2+tp)/(1+exp(alp2+tp));
pi3=exp(alp3+tp)/(1+exp(alp3+tp));pi4=exp(alp4+tp)/(1+exp(alp4+tp));
if Y=1 then loglik=log(pi1);
if Y=2 then loglik=log(pi2-pi1);
if Y=3 then loglik=log(pi3-pi2);
if Y=4 then loglik=log(pi4-pi3);
if Y=5 then loglik=log(1-pi4);
Colorectal cancer is the third most common cancer worldwide and remains an important cause of death. CRC diagnosis and treatment require a multidisciplinary approach, and in stage IV disease combination chemotherapy (CT) and regional multimodality treatments − like metastasectomy and other local treatments − are increasingly used. Systemic therapy has evolved over the past few decades, with the emergence of combination CT and targeted agents (Figure 1).
Targeted therapies that have been approved or are currently under investigation for advanced colorectal cancer.
Setting | Study | Treatment | RR□, % | PFS□, months | OS□, months |
---|---|---|---|---|---|
1st line | PRIME | PAN+FOLFOX4 FOLFOX4 | 59* 46* | 10.1* 7.9* | 26.0* 20.2* |
1st line | PEAK | PAN-mFOLFOX6 mFOLFOX6 | 64 61 | 13.0* 9.5* | 41.3 28.9 |
1st line | PLANET-TTD | PAN-FOLFOX4 PAN-FOLFIRI | 74 67 | 12.8 14.8 | 39.0 45.8 |
1st line | 314 | PAN-FOLFIRI | RASwt: 56* RASmt: 38* | RASwt: 8.9* RASmt: 7.2* | NR |
1st line | COIN | CET-OXAL OXAL | 64* 57* | 8.6 8.6 | 17.9 17.0 |
1st line | OPUS | CET-FOLFOX4 FOLFOX4 | 61* 37* | 8.3* 7.2* | 22.8 18.5 |
1st line | CRYSTAL | CET-FOLFIRI FOLFIRI | 46.9* 38.7* | 9.9* 8.7* | 24.9 21.0 |
1st line | FIRE-3 | CET-FOLFIRI BEVA-FOLFIRI | 62.0 58.0 | 10.0 10.3 | 28.7* 25.0* |
1st line | CALGB 80405 | CET-FOLFOX/FOLFIRI BEVA-FOLFOX/FOLFIRI | 59.6 55.2 | 10.5 10.6 | 30.0 29.0 |
2nd or greater | 181 | PAN-FOLFIRI FOLFIRI | 36* 10* | 5.9* 3.9* | 14.5 12.5 |
2nd or greater | PICOLLO | PAN- CPT-11 CPT-11 | 34* 12* | HR 0.78* | 10.4 10.9 |
2nd or greater | Saltz, 2004 | CET | 8.8 | 1.4 | 6.4 |
2nd or greater | Cunningham, 2014 | CET + CPT-11 CET | 22.9* 10.8* | 4.1* 1.5* | 8.6 6.9 |
2nd or greater | ASPECCT | PAN CET | 22.5 20 | 4.1 4.4 | 10.4 10.0 |
Targeted therapies against EGFR in colorectal cancer.
Results for the KRAS wild-type subgroup, except if clearly stated.
Difference between groups is statistically significant (p < 0.05).
BEVA, bevacizumab; CET, cetuximab; CPT-11, irinotecan; mt, mutated; NR, not reported; ORR, overall response rate; OS, overall survival; OXAL, oxaliplatin-containing chemotherapy regimen; PAN, panitumumab; PFS, progression-free survival; wt, wild-type.
In the present review, genomic and tumor microenvironment alterations driving treatment selection are discussed.
Metastatic CRC (mCRC) presents with synchronous metastatic disease at initial diagnosis in 20% of cases, with 50–60% of patients developing metachronous metastases. Approximately 56% of patients with CRC will ultimately die from their cancer [1]. The cornerstone of CRC treatment for 20 years has been fluoropyrimidine-based CT doublets, with either irinotecan (FOLFIRI or CAPIRI) or oxaliplatin (FOLFOX or CAPOX) in the first- and second-line settings [2].
In the past two decades, remarkable progress has been achieved in mCRC treatment with the introduction of molecular targeted agents (Figure 2). Today, the median overall survival (OS) for these patients in phase III trials is approximately 30 months, more than doubling that of 20 years ago [3]. Simultaneously, mortality has declined, what is attributed to earlier diagnosis (due to screening tests) and improved treatment options, including new systemic CT agents and biologic agents targeting specific pathways [1].
Timeline of development of targeted therapies in colon cancer.
More recently, consensus molecular subtypes (CMS) defined by gene expression profiling have identified biologically different CRC subtypes, which seem to have a prognostic and predictive value. However, CMS subtyping is not a standard test with therapeutic application at present, being more relevant in the research field [2].
New targeted therapies against the epidermal growth factor receptor (EGFR) had an impressive impact on mCRC prognosis, with an actual median OS over 30 months (varying according to therapeutics options) [4, 5, 6].
As part of the ErbB tyrosine kinase family, EGFR is a transmembrane receptor and its activation by extracellular ligands stimulates downstream pathways, such as RAS–RAF–MEK-MAPK, PIK3CA-AKT, the SRC family kinases, PLCγ-PKC, and JAK/STATs, inducing proliferation, migration, invasion, survival, and angiogenesis [6, 7]. Thus, EGFR is an important factor in tumor development and progression, being expressed in various cancers and in 60–80% of CRCs [8].
Target therapy against EGFR is now a standard of care in RAS wild-type mCRC. Two monoclonal antibodies (mAbs) are approved: cetuximab (human-mouse chimeric mAb) and panitumumab (fully human mAb). By recognizing and binding to the extracellular domain of the EGFR receptor, these mAbs prevent binding of other extracellular ligands and subsequent receptor internalization and degradation, thus inhibiting and blocking downstream pathways and signaling [9]. Tumor RAS mutational status predicts efficacy of anti-EGFR agents in mCRC patients, with RAS mutations being a well-established negative predictive biomarker for patient selection [10].
Several phase II and III clinical trials have established the efficacy of cetuximab and panitumumab, either in monotherapy or in association with CT, in terms of progression-free survival (PFS), OS, and overall response rate (RR), while maintaining quality of life (Table 1) [6, 11, 12, 13].
The PRIME trial, a randomized phase III trial investigating the addition of panitumumab to FOLFOX4 as first-line therapy in RAS wild-type mCRC, showed a 2- and 6-month PFS and OS benefit, respectively, with the combination. Regarding safety, known EGFR inhibition adverse events (AE) were more frequently observed with panitumumab, including skin toxicity and diarrhea (36% vs. 2% and 18% vs. 9% in panitumumab and placebo arms, respectively) [11].
The randomized phase II PEAK trial compared the efficacy and safety of mFOLFOX6 plus panitumumab with mFOLFOX plus bevacizumab (an anti- vascular endothelial growth factor [VEGF] mAb) as first-line therapy in RAS wild-type mCRC. The study primary endpoint was met, with panitumumab showing a 3.5-month PFS increase compared with bevacizumab. An OS improvement was also observed, although not statistically significant [14]. Rivera et al. and Stintzing S et al. also demonstrated that early tumor shrinkage in an important and early predictor of treatment sensitivity and deep tumor response correlates with OS [15, 16].
The open-label phase II PLANET-TTD trial compared panitumumab with two different CT regimens (FOLFOX 4 and FOLFIRI) as first-line treatment of RAS wild-type mCRC, but no significant efficacy differences were observed between the two regimens [17].
The 314 trial, a single-arm phase II study evaluating first-line panitumumab plus FOLFIRI in mCRC patients, confirmed the impact of KRAS exon 2 status in being a negative predictor of efficacy in mutant patients. In a total of 154 patients, 59% had KRAS wild-type tumors. RR and median duration of response (DoR) were higher in the KRAS wild-type group. Additionally, more patients in the wild-type group underwent R0 resection (8% vs. 5%), and a PFS benefit was also observed in this group (8.9 vs. 7.2 months) [18].
In the COIN trial, cetuximab was added to oxaliplatin-containing CT (FOLFOX or CAPOX) in first-line setting of mCRC. In patients with KRAS wild-type tumors, no OS or PFS difference was reported between the two groups, while overall response rate (ORR) was higher with the addition of cetuximab to CT compared to CT alone [19].
Similar ORR results were seen in the OPUS trial. In KRAS wild-type tumors, the addition of cetuximab to FOLFOX-4 was associated with a clinically significant increased chance of response and a lower risk of disease progression. The same results were not seen in the overall population, confirming the relevance of KRAS mutational status [12].
Although the addition of cetuximab to oxaliplatin-containing CT had little survival impact, the CRYSTAL trial showed different results when combining cetuximab to FOLFIRI. A borderline significant PFS increase was seen in the combination arm, although with no OS differences. However, when KRAS mutational status was considered, a significant PFS increase was observed favoring cetuximab [20].
Additionally, in the phase III open-label FIRE-3 trial, cetuximab was compared with bevacizumab, both in combination with FOLFIRI. No differences were observed in the primary endpoint of ORR or in PFS, but the median OS was improved in cetuximab arm [21].
Cetuximab was further compared with bevacizumab, both combined with CT (FOLFOX or FOLFIRI), in the CALGB 80405, with no significant differences in ORR, PFS, or OS [22].
In the 181 trial, the efficacy and safety of adding panitumumab to FOLFIRI was compared with FOLFIRI alone in RAS wild-type mCRC patients who had failed the initial treatment. Addition of panitumumab to the regimen resulted in a significant PFS improvement, of approximately 2 months. Although not significant, a trend towards an OS benefit was seen with the addition of panitumumab [23].
Conversely, the randomized open-label PICOLLO trial reported no benefit with the addition of panitumumab to irinotecan after progression on fluoropyrimidine, with or without oxaliplatin. However, better PFS and more responses were reported in the panitumumab group [24].
In 2004, Saltz et al. and Cunningham et al. evidenced the role of cetuximab in heavily pretreated patients. Saltz et al. reported a median OS of 6.4 months and a median PFS of 1.4 months in 57 patients receiving cetuximab monotherapy after progression on irinotecan, and a tumor RR of 8.8% [25]. Cunningham et al. included over 300 patients and investigated the role of cetuximab (with or without irinotecan) after progression on irinotecan. A PFS and ORR benefit was observed, with a numeric but not statistically significant difference also observed in OS (8.6 vs. 6.9 months) [26].
Later, the randomized phase II ASPECCT trial compared panitumumab alone with cetuximab alone as third-line treatment for mCRC patients with RAS wild-type (exon 2) tumors. With OS as primary endpoint, panitumumab was given at a dose of 6 mg/Kg every two weeks and cetuximab at a loading dose of 400 mg/m2, followed by a weekly dose of 250 mg/m2. No efficacy differences were observed, with a median OS of 10.4 months for panitumumab and 10.0 months for cetuximab [27].
Regarding maintenance and treatment intensification, three clinical trials are worth mentioning: VOLFI, VALENTINO, and SAPPHIRE.
VOLFI was a randomized open-label phase II trial comparing the addition of panitumumab to FOLFOXIRI CT regimen. An ORR of 87,3% was seen in the FOLFOXIRI plus panitumumab arm, which was higher compared with FOLFOXIRI alone. PFS was similar in both arms, whereas OS showed a trend in favor of panitumumab [28]. This was the highest ORR reported in mCRC, suggesting that these protocols can be considered to obtain maximum cytoreduction in selected patients.
The VALENTINO trial, an open-label phase II trial, investigated maintenance therapy with panitumumab (induction therapy with FOLFOX-4 + panitumumab followed by maintenance with panitumumab ±5FU/LV). The study hypothesis that panitumumab alone was not inferior to the combination as maintenance therapy could not be proven. ORR and OS results did not differ between the two arms [29].
In the SAPPHIRE trial, patients received six cycles of mFOLFOX6 plus panitumumab as induction therapy. Patients who completed induction therapy without progression were then randomized to mFOLFOX6 plus panitumumab (group A) or 5-FU/LV plus panitumumab (group B). PFS, RR, OS, and time to treatment failure were similar between groups, adding to the concept that planned discontinuation of oxaliplatin after six cycles of mFOLFOX6 is a potential treatment option for mCRC patients, achieving similar efficacy while reducing oxaliplatin-associated peripheral neuropathy compared with mFOLFOX6 plus panitumumab [30].
Although anti-EGFR therapy has shown benefit in a particular subgroup of CRC patients, primary or innate resistance is high among unselected patients. Furthermore, even patients that initially respond to cetuximab and panitumumab, eventually develop resistance and relapse under these therapies (secondary resistance). Knowledge of the resistance mechanisms associated with the EGFR pathway is crucial to improve therapy efficacy.
RAS–RAF-MAPK is an EGFR direct downstream signaling pathway, highly deregulated in CRC. Mutations frequently found in these family members generally lead to protein constitutive activation independently of the upstream signaling cascade. Over the last decade, analysis of retrospective clinical trial data (in particular of the OPUS, CRISTAL, and PRIME trials) led to the discovery that patients harboring
Although
Evidence from cellular studies has suggested that constitutive activation of other EGFR downstream pathways, such as those including the JAK–STAT family, are implicated in resistance to the anti-EGFR gefitinib [36, 37].
Additionally, amplification of other receptor tyrosine kinases (RTKs) has been proposed as a resistance mechanism to anti-EGFR therapies. Expression of VEGF-1 or its receptor (VEGFR) has been associated with cetuximab resistance in both preclinical models and metastatic CRC patients [38]. Bertotti et al. reported that human epidermal growth factor receptor 2 (HER2) gene amplification correlated with cetuximab resistance in a patient-derived xenograft mouse model [39]. Besides HER2, also HER3 has been described to have a role in resistance mechanism to EGFR-targeted therapies. In a cohort of metastatic CRC patients treated with irinotecan and cetuximab, HER3 overexpression was associated with lower PFS and OS [40].
Finally, growing evidence implicates the MET pathway in both primary and secondary resistance mechanisms to mAbs in
Although RAS mutations are negative predictors of efficacy in cetuximab and panitumumab treatment, it is acknowledged that not all RAS wild-type patients respond to these agents. To investigate this, research efforts were driven downwards in the MAPK pathway, putting the spotlight on BRAF. This is the main effector in EGFR pathway and is usually mutated in 5–10% of mCRC patients. BRAF and KRAS are usually mutually exclusive, with BRAF V600E mutation (class I) accounting for most alterations found and conferring worse prognosis to these patients.
Regardless of EGFR blockade, BRAF mutations can keep the downstream signaling persistently activated, suggesting that they can confer EGFR blockade resistance. In fact, in a retrospective trial, De Roock et al. showed that chemorefractory mCRC patients with
Multiple combinations with drugs targeting the MAPK pathway have been tested in BRAF-mutant CRC. Monotherapy results were disappointing when compared to the clinical activity seen in melanoma. In contrast to melanoma, CRC expresses high levels of activated EGFR, which reactivate the MAPK pathway after single BRAF inhibition [44, 45]. In view of the possibility of therapy resistance via EGFR signaling feedback activation, the trial was amended to include safety and efficacy assessment of vemurafenib combined with cetuximab in a heavily pretreated population, with positive results (median PFS of 3.7 months and median OS of 7.1 months). Similar results were observed when combining dabrafenib with panitumumab (median PFS of 3.5 months) and encorafenib with cetuximab (RR of 23.1%, median PFS of 3.7 months), with phase II results of the latter showing a median PFS of 4.2 months and an ORR of 22% [46].
CT was also combined with BRAF and EGFR inhibition in a phase II trial of irinotecan, cetuximab, and vemurafenib. A total of 106 patients were enrolled, with the study reporting a PFS benefit of 4.3 months with the addition of vemurafenib compared to 2.0 months in the control arm [47].
BRAF inhibition can also induce EGFR overactivation or PI3K modulation, and triplet combos targeting EGFR, MAPK, and PI3K have shown positive results. The MEK116833 trial included 24 patients receiving full-dose combination of panitumumab, trametinib, and dabrafenib and reported an ORR of 21%, a median PFS of 4.1 months, and an OS of 9.1 months. Additionally, a randomized phase II trial combining encorafenib, cetuximab, and the PI3K inhibitor alpelisib reported a median PFS of 5.4 months and an ORR of 27% in interim analysis [48, 49, 50, 51].
More recently, the phase 3 BEACON trial investigated the doublet of encorafenib plus cetuximab and the triplet of encorafenib plus cetuximab plus binimetinib in patients with
HER2 is a growth factor receptor involved in CRC development and progression. HER2 amplification is relatively uncommon, reported in only 3–5% of metastatic CRC patients with wild-type KRAS and wild-type BRAF [54].
Trastuzumab is a monoclonal antibody targeting HER2. The phase II HERACLES trial included mCRC patients with KRAS wild-type, HER2-positive (defined as 2+/ 3+ HER2 score in >50% of cells by IHC or HER2:CEP17 ratio > 2 in >50% of cells by fluorescent
Both the TRIUMPH (trastuzumab and pertuzumab) and MOUNTAINEER (trastuzumab and tucatinib) trials reported high response rates (35% and 52%, respectively) and encouraging median PFS (4.0 and 8.1 months, respectively), supporting dual HER2 blockade in patients with HER2-amplified metastatic CRC [57, 58]. Conversely, the combination of pertuzumab and TDM-1 did not show an enhanced objective response in the HERACLES-B trial, although achieving a similar disease control to the HERACLES-A trial (ORR of 10% and median PFS of 4.8 months at cut-off) [59].
Regarding new antibody-drug conjugates, the phase 2 DESTINY-CRC01 trial, of trastuzumab deruxtecan (T-DXd; DS-8201) and also in patients with metastatic HER2-amplified CRC, reported significant responses (ORR of 45.3%, disease control rate [DCR] of 83%), including in patients previously submitted to HER2 blockade [60].
Tumor angiogenesis is one of the hallmarks of cancer and a key process in tumor development [61, 62]. One of the most relevant pathways involved in angiogenesis is the vascular endothelial growth factor/vascular endothelial growth factor receptor (VEGF/VEGFR) signaling pathway. VEGF-A is a heparin-binding glycoprotein with potent angiogenic activity. VEGF is produced by different cell types, such as immune cells, fibroblasts, and cancer cells, in response to tumor hypoxia via hypoxia-inducible factor (HIF)-1a pathway, inducing an angiogenic switch [63]. Overproduction of pro-angiogenic growth factors leads to formation of chaotic blood vessels in the tumor, with a leaky endothelial wall [64].
In CRC, primary tumor growth and distant metastases development are highly dependent on new vessel formation, making VEGF signaling pathway an attractive therapeutic target. Inhibition of VEGF signaling pathway can be achieved through neutralizing antibodies binding VEGF ligands or blocking VEGFR, or tyrosine kinase inhibitors (TKIs) blocking intracellular VEGFR-dependent signaling [65].
Bevacizumab. The first angiogenesis inhibitor approved for mCRC was bevacizumab, an immunoglobulin G (IgG)1 monoclonal antibody with affinity to VEGF-A. Several trials have evaluated the benefit of adding bevacizumab to cytotoxic regimens as first-line treatment of patients with mCRC, with inconsistent PFS and OS results (Table 2).
Study | Treatment | PFS, months | OS, months | HR (p-value) |
---|---|---|---|---|
Hurwitz et al. (III) | BEVA-ILF PLACEBO-IFL | 10.6* 6.2* | 20.3 15.6 | PFS - 0.54 (<0.001) OS - 0.66 (>0.001) |
Saltz et al. (III) | XELOX BEVA-FOLFOX PLACEBO | 9.4* 8.0* - | 23.3 19.9 - | PFS - 0.83 (0.002) OS - 0.89 (0.077) |
AVEX (III) | BEVA-CAP CAP | 9.1* 5.1* | — | PFS - 0.53 (<0.001) |
ITACa (III) | BEVA-FOLFIRI/FOLFOX PLACEBO-FOLFIRI/FOLFOX | 9.6 8.4 | — | PFS - 0.86 (0.182) |
SOLSTICE (III) | BEVA-Trifluridine/tipiracil BEVA-CAP | — | — | Ongoing |
VELOUR (III) | Aflibercept-FOLFIRI PLACEBO-FOLFIRI | 6.90* 4.67* | 13.50* 12.06* | PFS - 0.758 \t(<0.001) OS - 0.817 (0.003) |
AFFIRM (II) | Aflibercept-FOLFOX PLACEBO-FOLFOX | 8.48 8.77 | — | PFS - 1.00 |
RAISE (III) | Ramucirumab-FOLFIRI PLACEBO-FOLFIRI | — | 13.3* 11.7* | OS - 0.844 (0.022) |
CORRECT (III) | Regorafenib PLACEBO | — | 6.4* 5.0* | OS - 0.77 (0.005) |
CONCOUR (III) | Regorafenib PLACEBO | — | 8.8* 6.3* | OS - 0.55 (<0.001) |
CONSIGN (III) | Regorafenib | AEs: hypertension (15%), hand-foot skin reaction (14%), fatigue (13%), diarrhea (5%), and elevated aminotransferase (6%), aspartate aminotransferase (7%), and bilirubin (13%). |
Targeted therapies against VEGF in colorectal cancer.
Difference between groups is statistically significant (p < 0.05).
AEs, adverse events; BEVA, bevacizumab; CAP, capecitabine; HR, hazard ratio; OS, overall survival; PFS, progression-free survival.
A phase III trial conducted by Hurwitz et al. compared the efficacy of irinotecan, bolus fluorouracil, and leucovorin (IFL) plus bevacizumab versus IFL plus placebo in untreated mCRC patients. Bevacizumab was intravenously administered at a dose of 5 mg/kg every two weeks along with CT. Bevacizumab arm showed a meaningful improvement in OS (20.3 versus 15.6 months in placebo arm) and PFS (10.6 versus 6.2 months in placebo arm) [66]. Saltz et al. assigned mCRC patients in a 2x2 factorial design to receive CAPOX or FOLFOX4 followed by bevacizumab or placebo as first-line treatment. Median PFS was higher in the bevacizumab group compared with placebo (9.4 versus 8.0 months). OS differences did not reach statistical significance, but only 29% of bevacizumab recipients were treated until disease progression or toxicity [67]. For elderly patients with untreated and unresectable mCRC not candidates for oxaliplatin- or irinotecan-based therapies, the phase III AVEX trial compared the efficacy and safety of capecitabine combined with bevacizumab versus capecitabine alone. Capecitabine was given at a dose of 1000 mg/m2 orally twice a day on days 1–14 and bevacizumab was administered intravenously at a dose of 7.5 mg/kg on day 1, every 21 days. Longer PFS was documented in the bevacizumab arm (9.1 versus 5.1 months for capecitabine alone), with acceptable tolerance. Grade ≥ 3 adverse events reported in the combination arm included hand-foot syndrome (16%), diarrhea (7%), and venous thromboembolic events (8%) [68].
Despite these results, the 2015 phase III ITACa trial reported no statistically significant PFS and OS differences when bevacizumab was added to standard first-line CT (FOLFIRI or FOLFOX4) [69]. Other previous trials reported the same negative results. Considering these discrepancies, a 2017 meta-analysis based on 9 studies examined the survival impact of bevacizumab plus CT in first-line treatment of mCRC patients, showing that the combination significantly prolonged PFS (HR 0.66; p < 0.0001) and OS (HR 0.84; p = 0.0001) compared with CT alone. Subgroup analyses suggested that irinotecan-based regimens might be a better partner for bevacizumab than oxaliplatin-based regimens, with superior PFS and OS benefit [70].
Sidedness of the primary tumor is known to be an important prognostic factor in metastatic setting of CRC, with worst survival outcomes for right-sided tumors. Several clinical trials investigated the prognostic role of bevacizumab in the treatment of patients with right-sided and left-sided CRC. A post-hoc analysis of 16 randomized trials including PEAK, FIRE-3, and CALGB/SWOG trials showed that right-sided tumors have impaired CT sensitivity, while addition of bevacizumab to cytotoxic regimens can be an optimal first-line treatment for RAS-wild-type right-sided mCRC [71].
Although continuing bevacizumab with second-line chemotherapy showed benefit after disease progression, other anti-VEGF drugs should be considered for fast progressors (PFS <3–4 months) [72].
In patients with unresectable mCRC who are not candidates for intensive therapy, the ongoing phase III SOLSTICE trial is currently comparing trifluridine/tipiracil (TAS-102) plus bevacizumab versus capecitabine plus bevacizumab as first-line treatment [73].
Aflibercept. Aflibercept is a recombinant fusion protein composed by VEGF-binding portions from VEGFR-1 and -2 extracellular domains fused to the Fc portion of human IgG1. It acts by blocking the activity of VEGF-A and -B, preventing their binding to VEGFR on endothelial and tumor cells [74].
The role of aflibercept was evaluated in the phase III VELOUR trial, of mCRC patients previously treated with oxaliplatin-based regimens in first line, including with bevacizumab. Second-line FOLFIRI was intravenously administered with placebo or aflibercept at the dose of 4 mg/kg every two weeks. Aflibercept improved the median OS (13.50 vs. 12.06 months) and median PFS (6.90 versus 4.67 months) compared to placebo [74]. These results lead to approval of the drug in combination with FOLFIRI as second-line treatment for patients pretreated with oxaliplatin-based doublet with bevacizumab. The most common grade ≥ 3 AEs reported in the VELOUR trial included neutropenia, diarrhea, stomatitis, hypertension, and fatigue. Additionally, there was no evidence of greater toxicity in patients previously treated with bevacizumab [74].
More recently, the phase II AFFIRM trial investigated the addition of aflibercept to first-line oxaliplatin-based regimens in mCRC patients. Patients received mFOLFOX6 plus aflibercept or mFOLFOX6 alone. Despite VELOUR results, this study did not reach the primary endpoint of PFS. Adding aflibercept to first-line mFOLFOX6 did not increase efficacy and was associated with higher toxicity [75].
Ramucirumab. Ramucirumab is a human IgG1 monoclonal antibody against VEGFR-2. Efficacy and safety of ramucirumab in combination with second-line FOLFIRI was evaluated in the phase III RAISE trial. Patients with progressive mCRC during or after first-line treatment with bevacizumab, oxaliplatin, and fluoropyrimidine were randomized to receive intravenous ramucirumab 8 mg/kg plus FOLFIRI or placebo plus FOLFIRI every 2 weeks. Ramucirumab significantly improved survival in this subpopulation, reaching a median OS of 13.3 months, against 11.7 months in the placebo arm. Grade ≥ 3 AEs included neutropenia (38%), hypertension (11%), diarrhea (11%), and fatigue (12%). Febrile neutropenia was only reported in 3% of patients and most toxicities reported were manageable [76]. This trial lead to the approval of ramucirumab in combination with FOLFIRI in the second-line setting of mCRC previously treated with bevacizumab, oxaliplatin, and fluoropyrimidine in first line.
Regorafenib. The only TKI approved for mCRC treatment is regorafenib, a multi-kinase inhibitor of angiogenic pathway members, including VEGFR-1 and -2, platelet-derived growth factor receptor (PDGFR)-β, and tyrosine kinase with immunoglobulin-like and EGF-like domains 2 (TIE2) [77].
Several phase III trials evaluated the role and efficacy of regorafenib as single-agent in mCRC patients progressing after several standard lines of treatment (Table 2). The CORRECT trial was the first to compare treatment with regorafenib 160 mg daily for 21 days, every 28-day cycle, versus placebo. Final study results reported a quality of life (QoL) and OS (6.4 vs. 5.0 months in placebo arm) improvement in favor of regorafenib [78]. The phase III CONCOUR trial was similar to the CORRECT trial but exclusively recruited Asian patients, holding similar OS results [79]. The CONSIGN trial was designed to specifically evaluate regorafenib safety. In a total of 2864 patients (median age of 62 years), the most common grade ≥ 3 AEs were hypertension (15%), hand-foot syndrome (14%), fatigue (13%) and diarrhea (5%). Grade ≥ 3 laboratory toxicities included elevated alanine aminotransferase (6%), aspartate aminotransferase (7%), and bilirubin (13%) [80].
Despite the outcome benefits seen with anti-VEGF agents in CRC, these are usually transient and followed by relapse and tumor growth [81]. Several resistance mechanisms to anti-VEGF therapies have been described, including VEGF axis-dependent alterations, non-VEGF axis-dependent upregulation, and stromal cell interactions [82].
Upregulation of alternative VEGFR-2 angiogenic ligands, such as VEGF-C, −D, and placental growth factor (PIGF), can bypass VEGF-A inhibition and elicit bevacizumab resistance [82]. In a phase II trial, Kopetz et al. showed that PlGF, VEGF-C, and VEGF-D plasma levels in mCRC patients receiving FOLFIRI plus bevacizumab were elevated prior to and at the time of disease progression [83].
Complementary angiogenic pathways other than VEGF/VEGFR signaling exert control on tumor angiogenesis and may explain acquired resistance to anti-VEGF therapies. These pathways involve members of the platelet-derived growth factor (PDGF) family, HIF, members of the fibroblast growth factor (FGF) family, angiopoietin (Ang), and Notch [84, 85].
The PDGF family consists of five ligands that bind to tyrosine kinases PDGFR-α and -β, activating downstream signal transduction pathways, as PI3K/Akt and PLCγ. PDGF-C was shown to be upregulated in cancer-associated fibroblasts (CAFs) of anti-VEGF-resistant tumors in vivo [86], making it a possible resistance mediator.
HIF-1 is a transcription factor with a key role in cellular response to reduced oxygen levels. Among its multiple downstream effects is induction of VEGF-A, VEGFR, PIGF, and PDGF expression [85].
Growth factors of the FGF family are potent mediators of tumor angiogenesis. Binding of FGF to fibroblast growth factor receptor (FGFR) tyrosine kinase activates downstream pathways such as MAPK/ERK, PI3K/Akt, and STAT [86], acting synergistically with VEGFA to induce angiogenesis via endothelial cell proliferation, survival, and migration [87]. FGF-2 upregulation is observed in anti-VEGF-resistant tumors, especially in tumors exposed to a hypoxic environment, [86] while FGF-2 blockade results in decreased tumor growth in
Ang-Tie signaling is a vascular-specific pathway essential for blood vessel development and vascular permeability regulation. Ang-2 acts as an antagonist of the Tie2 receptor, leading to development of vascular sprouts in the context of VEGF exposure [86]. mCRC patients with poor bevacizumab response showed high serum Ang2 levels, suggesting its relevance in resistance to anti-angiogenic therapy [89].
Delta-like ligand 4 (DII4) is a Notch ligand overexpressed in several solid malignancies, including CRC. DII4 upregulation is thought to contribute to bevacizumab resistance, which can be overcome by Notch inhibition with a γ-secretase inhibitor [90].
TGF-β is a ligand for type II TGF-β receptors and endoglin (CD105). It has important regulatory functions in angiogenesis, either directly, or indirectly by activating fibroblasts to produce extracellular matrix and stimulating the tube formation in endothelial cells [91]. Anti-VEGF therapy-resistant tumors can exhibit high levels of TGF-β1 expression. Additionally, in preclinical models VEGF pathway blockade led to increased CD105 levels, suggesting a role for CD105 in anti-VEGF therapy resistance [92].
It has been recently suggested that tumor stromal cells and bone marrow-derived cells (BMDCs) recruited to the tumor microenvironment by secreted cytokines play an important role in acquired resistance to anti-VEGF therapies [81].
CAFs entail a large portion of stromal cells present in the tumor environment. These cells secrete a number of pro-angiogenic mediators, including IGF, FGF, EGF, cytokines, and chemokines, and are capable of recruiting endothelial progenitor cells (EPCs) to the tumor site [93, 94]. Interestingly, Kinugasa et al. showed that CAFs from anti-VEGF-resistant tumors express high levels of CD44, a marker for cancer stem cells and cytotoxic resistance. CAFs can hence be considered a promising target for overcoming resistance to anti-angiogenic agents [95].
BMDCs are comprised of endothelial and pericyte progenitors, macrophages, and myeloid-derived suppressor cells (MDSCs) [96]. Preclinical models suggest that EPCs in the tumor microenvironment are able to secrete different proangiogenic factors and accelerate angiogenesis [97]. More importantly, endothelial precursor cells can differentiate into endothelial cells and participate in new vessel formation [98, 99].
Tumor-associated macrophages (TAMs) are also involved in angiogenesis. VEGF blockade by bevacizumab seems to promote TAM proliferation and reprogramming to pro-angiogenic macrophages [81]. This type of macrophages can secrete VEGF-A, TNFα, and IL-8, all of which affect different stages of angiogenesis by modifying the local extracellular matrix, promoting proliferation and migration of endothelial cells, and inhibiting development of differentiated capillaries [81].
A study by Shojaei et al. demonstrated that MDSCs were present in higher levels in anti-VEGF-resistant tumors and were functionally different from those in anti-VEGF-sensitive tumors. This population was able to sustain tumor growth even in presence of anti-VEGF inhibitors, although the exact mechanism behind this is not been fully established [100].
CD4+ T-helper cells mediate anti-VEGF resistance through IL-17 production in the tumor microenvironment and BMDC recruitment. These cells have been shown to regulate secretion of several proangiogenic factors from CAFs and other stromal cells. Additionally, Numasaki et al. reported that tumor microvessel density correlates with levels of infiltrating IL-17-producing CD4 T-cells [25, 42, 81, 101].
The main side effects of the anti-EGFR therapies cetuximab and panitumumab are dermatological toxicities, reported in 85–96% of patients (Table 3) [102]. The most common AE is papulopustular skin rash, generally developing over a period of 6 weeks after starting treatment and potentially impacting quality of life and therapy adherence. General prevention and management principles include the use of skin moisturizer, sunscreen, hydrocortisone cream, and oral tetracycline. The STEPP trial compared pre-emptive with reactive skin treatment and showed an over 50% reduction in grade ≥ 2 skin toxicities and less QoL impairment with the pre-emptive compared with reactive treatment [103]. In cases of grade 3 rash, treatment should be delayed until toxicity has resolved to grade 2 or less and dose should be reduced in a second occurrence. In grade 1 or 2 rash, dose reduction is not indicated. Other dermatological symptoms, including hair growth, periungual and nail plate abnormalities, xerosis, telangiectasias, and pruritus can occur at lower rates [102].
Target | Effect | Drug-incidence | Prevention/treatment | Dose reduction/delay treatment |
---|---|---|---|---|
EGFR | Rash | C 52–89% P 20–50% | Skin moisturizer, sunscreen, hydrocortisone cream, and oral tetracycline | Reduction in 2nd G3 occurrence, delay until ≤ G2 |
Infusion reactions | C 14–21% P-3% | Antihistamines and corticosteroids Low rate, gradual titration | Grade dependent | |
Hypomagnesemia | C 4–38% P 27% | Magnesium replacement | Some G3/4 toxicity delay until recovery | |
Diarrhea | 2% G3/4 | Loperamide, hydration, electrolyte replacement, hospitalization | Reduction in 1st G3 or 2nd G2 occurrence | |
VEGF | Hypertension | B 25% A 42.4% Reg 15% Ram 11% | Blood pressure monitoring, antihypertensive drugs | Cease if G4 or persisting G3 toxicity |
Proteinuria | 18.7% | Screening for proteinuria angiotensin receptor blockers | Discontinue if nephrotic syndrome | |
Hand-foot syndrome | B 16% Reg 14% | Emollient, analgesia | Reduction in 1st G3 or 2nd G2 occurrence, delay until ≤ G1 | |
Thromboembolic events | B 8% | Anticoagulation therapy | Cease bevacizumab |
Adverse effects of any severity with anti-EGFR and -VEGF therapies.
A, aflibercept; B bevacizumab; C cetuximab; EGFR, epidermal growth factor receptor; G grade; P, panitumumab; Ram, ramucirumab; Reg, regorafenib, VEGF, vascular endothelial growth factor.
Infusion reactions commonly occur with cetuximab and should be prevented with premedication, antihistamines, and corticosteroids. Other adverse effects, like hypomagnesemia, ocular toxicities as conjunctivitis and blepharitis, and less commonly diarrhea, can also occur [104]. Toxicity management is grade-depend and, in some cases, should be addressed by a multidisciplinary team.
The main anti-VEGF side effects are cardiovascular and kidney problems (Table 3). Hypertension has been observed at high rates in all phase III studies of anti-VEGF drugs and is normally manageable with standard antihypertensive medications, but this treatment should not be initiated in patients with uncontrolled hypertension. Proteinuria is another side effect, defined as protein content in the urine >300 mg/dL. No standard treatment is established, but anti-angiogenic drugs should be disused if protein content in the urine is >2 g/24 h, and evaluation by a nephrologist should be considered. Hand-foot syndrome is also common with this class of drugs [105].
Bevacizumab has also been associated with other side effects, like thromboembolic events (8%), delayed wound healing, bleeding, fistulae, and gastrointestinal perforation (1.7%). Bevacizumab treatment should be ceased in cases of hemorrhagic events ≥grade 3, pulmonary embolism, cerebrovascular events or arterial insufficiency, arterial thromboembolic events, grade 4 or persistent grade 3 hypertension, nephrotic syndrome, or gastrointestinal perforation [106]. Potentially life-threatening events have occurred only in a small number of patients, with bevacizumab being well tolerated by the majority.
The constitutive activation of RTKs promoted by genomic translocations play an important role in tumorigenesis across different malignancies, including CRC. Examples include ALK, ROS1, and NTRK1–2-3 (NTRK), which altogether occur in 0.2–2.4% of CRCs and may represent new therapeutic targets (Table 4) [107].
Target | Frequency | Clinicopathological features | Testing methods | Agent | Mechanism of action | Current status |
---|---|---|---|---|---|---|
NTRK genes (NTRK 1, NTRK 2, NTRK 3) fusions | 0.5–2.0% in mCRC (4% in MSI-H) | Associated with MSI-H/dMMR; wt BRAF/RAS, elderly females and right sided tumors; associated with poor prognosis; resistance to anti-EGFR monoclonal antibodies | IHC and NGS | Larotrectinib Entrectinib | Small molecule inhibitor targeting TRK proteins | Approved by the FDA and EMA |
ALK/ROS1 | 0.8–2.5% | Associated with MSI-H/dMMR; wt BRAF/RAS, elderly females and right-sided tumors; associated with poor prognosis; resistance to anti-EGFR monoclonal antibodies | FISH, RT-PCR, NGS | Clinical trials; Ceritinib | Small-molecule inhibitor targeting ALK/ROS1 | Under investigation |
FGFR | 3–5% | FGFR3 related with worse prognosis | NGS plus FISH | Regorafenib and newly developing FGFR-specific TKIs | Small-molecule inhibitor targeting FGFR signaling | Under investigation |
c-Met overexpression | Overexpressed in 50–60%, amplified in 10% and mutated in 5% of CRCs | Shorter OS, shorter PFS with bevacizumab treatment; poor prognosis; resistance to anti-EGFR monoclonal antibodies | IHC | Clinical trials | Under investigation | Under investigation |
RET fusions | 0.2% | Worse prognosis, poor treatment response, and reduced OS | IHC and FISH | Vandetanib, cabozantinib | Under investigation | Under investigation |
Summary of new targeted therapies in mCRC.
dMMR, deficient mismatch repair; FGFR, fibroblast growth factor receptor; FISH, fluorescent
The NTRK (neurotrophic tropomyosin receptor kinase) 1, 2, and 3 genes encode three tropomyosin receptor kinase (TRK) receptors —TrkA, TrkB, and TrkC— which are transmembrane proteins [2, 108, 109]. Gene fusions involving those genes lead to constitutively activated NTRK proteins and, consequently, tumorigenesis [107]. The prevalence of NTRK fusions in mCRC is estimated to be 0.5–2.0% [110], but increases to 4% in microsatellite instability-high (MSI-H) mCRC [2].
NTRK gene rearrangements are more commonly detected in non-Lynch syndrome MSI-H/ deficient mismatch repair (dMMR) tumors with MLH1 promoter hypermethylation and wild-type BRAF/KRAS/NRAS, and define a molecular subgroup associated with poor prognosis [111]. They are also more frequent in elderly females with right-sided tumors [107, 109, 112].
Fusion-detection options include targeted DNA and RNA panels, RNA sequencing, FISH, and IHQ [2]. Recent ESMO recommendations for NTRK fusion detection state that, in tumors with low NTRK fusion frequency, as mCRC, detection can be done via one-step next-generation sequencing (NGS) or via IHQ followed by NGS (if IHQ positive) [113].
Larotrectinib and entrectinib are TRK inhibitors approved by the FDA and EMA in more than 10 tumor types. Larotrectinib, a small-molecule inhibitor targeting all three TRK proteins, has been tested in the multicenter single-arm LOXO-TRK-14001, SCOUT, and NAVIGATE clinical trials [111]. Larotrectinib at the dose of 100 mg twice daily showed a good safety profile and good responses (75% of ORR, 1-year PFS of 55%) [114]. In November 2018, the FDA granted accelerated tissue-agnostic approval to larotrectinib for solid tumors with NTRK gene fusions [2, 111, 112] Entrectinib is an oral pan-TRK, -ROS1, and -ALK inhibitor that is clinically active in patients with NTRK-rearranged tumors and is able to penetrate the blood–brain barrier [107]. Three clinical trials (ALKA-372-001, STARTRK-1, and STARTRK-2) have investigated this agent [107]. Pooled analyses of the three trials presented at the ESMO 2018 Congress and ASCO 2019 Meeting showed that entrectinib induced clinically meaningful durable responses in patients with solid tumors with or without metastatic central nervous systemic disease harboring NTRK fusions [111].
The second-generation TRK inhibitor BAY2731954 (formerly known as Loxo-195) and the next-generation ROS1, pan-TRK, and ALK inhibitor repotrectinib are being tested, with promising results [111].
As already shown with BRAF V600E mutations, patients with ALK-, ROS-, and NTRK-rearranged tumors seem to derive no benefit from treatment with anti-EGFR monoclonal antibodies [107]. Additionally, the high prevalence of MSI-H status in rearranged tumors opens the way for evaluation of new combination approaches including targeted (ALK, ROS1, TrkA-B-C) and immunotherapy agents [107].
Regarding resistance mechanisms, a dose-dependent effect seems to affect mutation emergence. Two mutations have been associated with entrectinib resistance: NTRK1 p. G667C and NTRK1 p.G595R [108]. For larotrectinib, three different mutational categories have been described: solvent front mutations (NTRK1 p.G595R, NTRK3 p.G623R); gatekeeper mutations (NTRK1 p.F589L); and xDFG mutations (NTRK1 p.G667S, NTRK3 p.G696A). Novel agents under development intend to overcome NTRK1 p.G595R-mediated resistance to TRK inhibitors [115].
The mesenchymal-epithelial transition (MET) protooncogene (also known as N-methyl-N′-nitroso-guanidine human osteosarcoma transforming gene) encodes for c-MET, a receptor with tyrosine kinase activity targeting HGF. Activation of this pathway has been implicated in CRC metastatic progression [2].
MET receptor tyrosine kinase can be overexpressed in 50–60%, amplified in 10%, and mutated in 5% of CRCs [2]. In a study by Lee et al., c-MET overexpression showed no correlation with primary tumor site, histological type, or molecular aberrations, but correlated with shorter OS and was a predictive biomarker of shorter PFS in bevacizumab-treated patients [3].
EGFR and MET are co-expressed in CRC and MET activation has been implicated in resistance to the anti-EGFR therapy [2, 116]. Inhibition of the HGF/c-Met pathway may improve response to EGFR inhibitors in CRC and combination therapy should be further investigated [116]. This supports the hypothesis that anti-EGFR therapy selects MET-amplified (cetuximab- and panitumumab-resistant) preexisting clones, eventually limiting the efficacy of further anti-EGFR therapies [117].
Multiple clinical trials have evaluated MET inhibition, but several of those conducted in mCRC have been unsuccessful [2]. Treatment strategies targeting HGF and c-Met include HGF antagonists, c-Met and HGF-blocking antibodies, and small-molecule c-Met inhibitors [118].
Although MET genomic aberrations are commonly observed in mCRC, these remain in the research setting [2].
The EML4-ALK fusion gene is produced by inversion in the short arm of chromosome 2, where anaplastic large-cell lymphoma kinase (ALK) joins echinoderm microtubule-associated protein-like 4 (EML4), resulting in a chimeric protein with constitutive ALK activity. ROS1 is an orphan receptor tyrosine kinase phylogenetically related to ALK [110].
ALK and ROS1 gene rearrangements have not been extensively studied in CRC. Around 0.8–2.5% of patients with mCRC have been reported to have either ALK or ROS1 rearrangements [110]. ALK, ROS1, and NTRK fusions occur more frequently in elderly patients with right-sided, RAS wild-type, MSI-H mCRC, and are associated with shorter OS and poor prognosis [107, 110]. The small patient numbers make it challenging to develop a clinical trial of targeted therapies for this patient population [110]. As no FDA-approved agents targeting these genomic alterations exist for CRC patients, basket trials (as the TAPUR trial) may give valuable insights in this setting [112].
RET is a proto-oncogene encoding a transmembrane tyrosine kinase receptor for the glial-derived neurotrophic factor family [110].
RET fusions occur in 0.2% of solid tumors, being very typical in specific tumor types, such as thyroid carcinomas [119]. The effect of RET activation is less clear in CRC, but several studies suggest that it might be associated with worse prognosis, poor treatment response, and reduced OS. Due to rarity of this aberration, clinical trials in CRC are not easy to conduct, with data derived mainly from early trials or case reports [110]. Clinicopathological factors associated with RET fusions include right colon location, older age, RAS and BRAF wild-type status, and MSI-H status [119].
Fibroblast growth factor receptors (FGFRs) are a subfamily of RTKs occurring in approximately 3–5% of CRC patients [112]. Initial evidence shows poor outcomes associated with FGFR3 alterations [120]. There is no evidence of clinicopathological characteristics related to these alterations [120].
Regorafenib, a multi-kinase inhibitor also targeting FGFR, is currently approved by the FDA for metastatic CRC patients who progressed on frontline therapies. This agent can be considered in CRC patients with FGFR alterations while novel FGFR inhibitors are not available [121]. Newly developed, more potent FGFR inhibitors are currently being investigated in multiple solid tumors [112].
Microsatellite instability (MSI) is currently a key biomarker in CRC, with diagnostic, prognostic, and therapeutic implications. For these reasons, MSI analysis is becoming increasingly important and testing for deficient mismatch repair (d-MMR)/MSI is recommended, both for hereditary syndrome screening and due to prognostic and treatment implications [122].
Inactivation of a DNA mismatch repair (MMR) gene (MLH1, MSH2, MSH6, or PMS2) by mutation or transcriptional silencing results in deficient function of the MMR system, responsible for excising DNA mismatches introduced by DNA polymerase during cell division. This activity loss translates in an accumulation of DNA replication errors and mismatches in repeated sequences, leading to hypermutated tumors [123]. In most cases, d-MMR and MSI arise due to sporadic somatic hypermethylation of MLH1 and other genes, but they can also result from germline mutations in MMR genes and from Lynch syndrome in approximately 3% of all CRCs [124].
The MMR system can be assessed through different approaches, as IHC, polymerase chain reaction (PCR)-based assays, and more recently NGS. IHC looks at MLH1, MSH2, MSH6, and PMS2 staining in tumor samples to identify the protein expression loss that characterizes d-MMR [125]. PCR amplification requires both tumor and matched normal samples. Five microsatellite loci have been PCR-amplified and analyzed by capillary electrophoresis. Instability at more than one locus was defined as MSI-high (MSI-H), at a single locus as MSI-low (MSI-L), and absence of instability at any locus as microsatellite stable (MSS), proficient MMR (p-MMR) [126]. NGS detection directly targets certain genes, which are genome sequenced to retrieve information on MSI and MMR and tumor mutational burden (TMB), integrating all information in the same test. NGS requires a smaller sample and is more accurate than PCR. Ethical issues may arise with the use of this technique regarding counseling and consent for additional genetic testing [127]. In CRC, MSI varies according to tumor stage, with higher incidence reported in early stages (20% in stages I-II, 12% in stage III) and lower incidence reported in the metastatic setting (4–5%) [128].
The success of immune checkpoint inhibitors (ICI) in d-MMR over the last years has disclosed a new therapeutic scenario. Endogenous peptides are processed and presented on major histocompatibility complex (MHC) class I molecules on the surface of all cells, being recognized by T cell receptors (TCRs). TCR–MHC signaling pathways are modulated by co-stimulatory or co-inhibitory signals. ICI target co-inhibitory receptors, like cytotoxic T lymphocyte antigen 4 (CTLA-4) and programmed cell death 1 (PD-1) on T cells, or their ligands, as programmed cell death ligand 1 (PDL-1), on tumor and various immune cells [129]. ICI are approved in several malignancies. In mCRC, phase I trials reported response to immune checkpoint therapy in a subgroup of patients with MSI-H, d-MMR, or high TMB [130].
Pembrolizumab is a humanized IgG4 antibody and was the first anti-PD-1 to show efficacy in d-MMR mCRC (Table 5). In the phase II KEYNOTE-016 trial, patients with d-MMR tumors responded better to pembrolizumab (RR of 40%, 20-week PFS of 78%) than MSS tumors (RR of 0%, 20-week PFS of 11%) [131]. In the updated analysis, an ORR of 52%, 2-year PFS of 59%, and OS of 72% was reported for MSI-H CRC [132]. The phase II KEYNOTE-164 trial confirmed the efficacy of pembrolizumab in second-line setting of MSI-H CRC, with an ORR of 33%, median PFS of 2.3 months, and median OS of 31.4 months [133]. Based on these results, pembrolizumab was approved by the FDA for MSI-H/d-MMR unresectable or metastatic CRC after progression on CT. In the phase III KEYNOTE-177 trial, first-line treatment with pembrolizumab in monotherapy significantly reduced the risk of disease progression or death by 40% (HR 0.60; 95% CI 0.45–0.80; p = 0.0004), with a median PFS of 16.5 months versus 8.2 months with CT in MSI-H CRC. The study is ongoing, and OS data will be presented later this year [134]. This led to FDA approval of pembrolizumab in first-line treatment of unresectable or metastatic MSI-H/dMMR CRC.
Setting | Study | Treatment | RR | PFS | OS | Approval |
---|---|---|---|---|---|---|
CT-refractory MSI-H/d-MMR mCRC | Phase II Keynote 164 | Pembrolizumab | 33% | 2.1 m | 31.4 m | FDA (1st line, CT-refractory) |
1st line MSI-H/d-MMR mCRC | Phase III Keynote 177 | Pembrolizumab | 43.8% | 16.5 m | NR | |
CT-refractory MSI-H/d-MMR mCRC | Phase II CheckMate-142 | Nivolumab | 31% | 50% | 73% | FDA (CT-refractory) |
Phase II CheckMate-142 | Nivolumab + ipilimumab | 55% | 71% | 85% | ||
1st line MSI-H/d-MMR mCRC | Phase II CheckMate-142 | Nivolumab + ipilimumab | 60% | 77% | 83% | Not approved |
Immune checkpoint inhibitors in mCRC.
CT, chemotherapy; dMMR, deficient mismatch repair, FDA, Food and Drug Administration; mCRC, metastatic colorectal cancer; MSI-H, microsatellite instability-high; NR, not reached; OS, overall survival; PFS, progression-free survival; RR, response rate.
Nivolumab, a humanized monoclonal IgG4-based PD-1 antibody, showed activity in MSI-H/d-MMR refractory CRC in the phase II CheckMate-142 trial, with an ORR of 31.1% regardless of tumor PD-L1 expression, 1-year PFS of 50%, and OS of 73% [135]. This trial included a cohort of nivolumab in combination with the CTLA-4 inhibitor ipilimumab, which showed a 55% ORR, 71% PFS, and 85% OS. Both nivolumab and the combination of nivolumab plus ipilimumab were approved by the FDA for CT-refractory MSI-H/dMMR mCRC. The immunotherapy doublet was also evaluated in first line in the CheckMate-142 trial, with 1-year PFS and OS of 77% and 83%, respectively, ORR of 60%, and DCR of 84% [136].
Following these studies, MSI status has become a crucial biomarker to define therapeutic options for patients in the metastatic setting.
Other PD-1/PD-L1 inhibitors are under investigation, like atezolizumab, avelumab, and durvalumab, and new immune checkpoint targets are in phase I trials, such as tumor-overexpressed T cell Ig and mucin domain-containing protein 3 (TIM-3), T cell Ig, and T cell-derived lymphocyte activation gene 3 (LAG-3). [137].
Most mCRC patients are MSS/p-MMR and results with ICI have been unsatisfactory, with immune resistance mechanisms not clearly elucidated yet. Several trials have been developed exploring ways to overcome this resistance, including by modulating tumor microenvironment, reducing tumor-specific antigen expression, altering immunosuppressive pathways, and activating other immune checkpoint pathways, immune regulatory cells, and cytokines [138]. Combining immunotherapy with CT, radiotherapy, bispecific antibody therapy, other immune checkpoint modulators, and other targeted agents are among strategies explored. The rationale behind this multimodal approach is the potential synergistic effect of targeting different immune escape pathways, resulting in improved response to ICI and patient outcomes [139].
CT has anti-tumor activity due to the direct cytotoxic effect on cancer cells and to stimulating host immune response, and several clinical trials are ongoing investigating the combination of immunotherapy with CT and targeted agents [140]. Radiotherapy can activate the host immune response by upregulating expression of tumor-specific neoantigens through cell damage and increasing membrane MHC class I expression, and several studies are ongoing in CRC combining radiotherapy with ICI. Another combined strategy is ICI and MEK blockers, considering that MEK blockade seems to increase T cell response via upregulation of PD-L1 expression [141]. Following a phase Ib trial of atezolizumab and the MEK inhibitor cobimetinib in MSS CRC, other trials were conducted, with no significant survival improvement [142]. The CEA CD3 TCB (RG7802, RO6958688) is a novel T-cell bispecific antibody targeting the carcinoembryonic antigen (CEA) on tumor cells and CD3 on T cells, which displays anti-tumor activity, leading to increased intra-tumoral T cell infiltration and activation and PD-1/PD-L1 upregulation. CEA-TCB antibody was tested in phase I trials of MSS CRC plus atezolizumab, showing antitumor activity with acceptable toxicity [143].
Considering immune side effects associated with ICI and their variable efficacy, it is important to identify biomarkers that help predict response to ICI and select potentially sensitive patients that can be candidates for these agents.
PD-L1 expression level is an established biomarker in some malignancies, but the relationship between PD-L1 positivity and response has not been proven in CRC [144]. TMB has emerged as a marker of response to immunotherapy in some tumors, suggesting that tumor cells with high mutational burden generate and present more peptide neoantigens on their MHC class I molecules, increasing T cell infiltration [145]. In CRC, dMMR/MSI-H tumors have a high mutational burden, as well as some pMMR/MSS, which may present an ultramutated phenotype as DNA polymerase epsilon (POLE) mutations, found in ∼1–2% of pMMR CRC. POLE mutations cause an increased immunogenicity and upregulation of immune checkpoint genes, such as PD-1/PD-L1 and CTLA-4, which result in similar clinical responses to dMMR tumors and may predict response to anti-PD-1 therapy [146]. Some case reports link POLE mutations with efficacy to PD-1 blockade, and phase II studies are ongoing in this setting.
The interaction between tumor and microenvironment led to the development of an immunoscore based on calculation of two lymphocytic populations (CD3/CD45-CD8 or CD8/CD45) in the centre and invasive margins of the tumor, which may predict ICI response [147]. Other lines of investigation are being explored, including the study of factors that indicate cytotoxic T cell activity, such as granzymes, perforins, and IFN-γ levels.
CRC is one of the tumor types for which immunotherapy has been less effective. Better knowledge of the molecular immune mechanisms is required to develop predictive biomarkers and effective therapeutic combination strategies, converting “cold” tumors, immune-desert and immunotherapy-resistant, in “hot” tumors, inflamed, infiltrated by the immune system, and immunotherapy responsive.
CRC treatment has changed over the last decades, not only by including different chemotherapy agents and combinations, but mainly because new targeted agents have emerged.
In metastatic setting, anti-EGFR and anti-VEGF drugs are widely used and have shown gains in survival and response rate, an important marker in CRC potentially resectable liver metastases. In contrast, several trials with targeted agents have been conducted in the adjuvant setting, without survival benefit. Immunotherapy emerged as a new treatment option with survival benefit, but at the moment it is only effective in a small portion of patients. Several other agents targeting other pathways are emerging, such as NTRK, c-MET, ALK, ROS1, and FGFR inhibitors, with promising results.
In conclusion, patients with CRC are living longer with targeted treatments, but more information about resistance mechanisms and biomarkers is necessary to extend even more their survival gains.
The authors gracefully acknowledge Joana Cavaco-Silva (
L. Costa performed consulting activities for Amgen, Novartis and Servier outside the scope of this manuscript. The remaining authors declare no conflicts of interest.
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\\n"}]'},components:[{type:"htmlEditorComponent",content:'Copyright is the term used to describe the rights related to the publication and distribution of original Works. Most importantly from a publisher's perspective, copyright governs how Authors, publishers and the general public can use, publish, and distribute publications.
\n\nIntechOpen only publishes manuscripts for which it has publishing rights. This is governed by a publication agreement between the Author and IntechOpen. This agreement is accepted by the Author when the manuscript is submitted and deals with both the rights of the publisher and Author, as well as any obligations concerning a particular manuscript. However, in accepting this agreement, Authors continue to retain significant rights to use and share their publications.
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Tiefenbacher"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"863",title:"Natural Disasters",subtitle:null,isOpenForSubmission:!1,hash:"7d03632c95c81e3de1eba473b9975204",slug:"natural-disasters",bookSignature:"Sorin Cheval",coverURL:"https://cdn.intechopen.com/books/images_new/863.jpg",editedByType:"Edited by",editors:[{id:"123456",title:"Dr.",name:"Sorin",middleName:null,surname:"Cheval",slug:"sorin-cheval",fullName:"Sorin Cheval"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:10,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"31818",doi:"10.5772/28441",title:"Comprehensive Monitoring of Wildfires in Europe: The European Forest Fire Information System (EFFIS)",slug:"comprehensive-monitoring-of-wildfires-in-europe-the-european-forest-fire-information-system-effis-",totalDownloads:4546,totalCrossrefCites:74,totalDimensionsCites:167,abstract:null,book:{id:"600",slug:"approaches-to-managing-disaster-assessing-hazards-emergencies-and-disaster-impacts",title:"Approaches to Managing Disaster",fullTitle:"Approaches to Managing Disaster - Assessing Hazards, Emergencies and Disaster Impacts"},signatures:"Jesús San-Miguel-Ayanz, Ernst Schulte, Guido Schmuck, Andrea Camia, Peter Strobl, Giorgio Liberta, Cristiano Giovando, Roberto Boca, Fernando Sedano, Pieter Kempeneers, Daniel McInerney, Ceri Withmore, Sandra Santos de Oliveira, Marcos Rodrigues, Tracy Durrant, Paolo Corti, Friderike Oehler, Lara Vilar and Giuseppe Amatulli",authors:[{id:"73894",title:"Dr.",name:"Jesús",middleName:null,surname:"San-Miguel-Ayanz",slug:"jesus-san-miguel-ayanz",fullName:"Jesús San-Miguel-Ayanz"},{id:"126055",title:"MSc.",name:"Ernst",middleName:null,surname:"Schulte",slug:"ernst-schulte",fullName:"Ernst Schulte"},{id:"126056",title:"Dr.",name:"Guido",middleName:null,surname:"Schmuck",slug:"guido-schmuck",fullName:"Guido Schmuck"},{id:"126057",title:"Dr.",name:"Andrea",middleName:null,surname:"Camia",slug:"andrea-camia",fullName:"Andrea Camia"},{id:"126058",title:"Dr.",name:"Peter",middleName:null,surname:"Strobl",slug:"peter-strobl",fullName:"Peter Strobl"},{id:"126059",title:"Mr.",name:"Giorgio",middleName:null,surname:"Liberta",slug:"giorgio-liberta",fullName:"Giorgio Liberta"},{id:"126060",title:"MSc.",name:"Cristiano",middleName:null,surname:"Giovando",slug:"cristiano-giovando",fullName:"Cristiano Giovando"},{id:"126061",title:"BSc.",name:"Roberto",middleName:null,surname:"Boca",slug:"roberto-boca",fullName:"Roberto Boca"},{id:"126062",title:"Dr.",name:"Fernando",middleName:null,surname:"Sedano",slug:"fernando-sedano",fullName:"Fernando Sedano"},{id:"126063",title:"Dr.",name:"Pieter",middleName:null,surname:"Kempeners",slug:"pieter-kempeners",fullName:"Pieter Kempeners"},{id:"126064",title:"Dr.",name:"Daniel",middleName:null,surname:"McInerney",slug:"daniel-mcinerney",fullName:"Daniel McInerney"},{id:"126066",title:"BSc.",name:"Ceri",middleName:null,surname:"Whitmore",slug:"ceri-whitmore",fullName:"Ceri Whitmore"},{id:"126068",title:"MSc.",name:"Sandra",middleName:null,surname:"Santos De Oliveira",slug:"sandra-santos-de-oliveira",fullName:"Sandra Santos De Oliveira"},{id:"126070",title:"MSc.",name:"Marcos",middleName:null,surname:"Rodrigues",slug:"marcos-rodrigues",fullName:"Marcos Rodrigues"},{id:"126072",title:"MSc.",name:"Tracy",middleName:null,surname:"Durrant",slug:"tracy-durrant",fullName:"Tracy Durrant"},{id:"126073",title:"MSc.",name:"Paolo",middleName:null,surname:"Corti",slug:"paolo-corti",fullName:"Paolo Corti"},{id:"126074",title:"MSc.",name:"Friderike",middleName:null,surname:"Oehler",slug:"friderike-oehler",fullName:"Friderike Oehler"},{id:"126075",title:"Dr.",name:"Lara",middleName:null,surname:"Vilar",slug:"lara-vilar",fullName:"Lara Vilar"},{id:"126076",title:"Dr.",name:"Giuseppe",middleName:null,surname:"Amatulli",slug:"giuseppe-amatulli",fullName:"Giuseppe Amatulli"}]},{id:"41478",doi:"10.5772/51387",title:"Monogenetic Basaltic Volcanoes: Genetic Classification, Growth, Geomorphology and Degradation",slug:"monogenetic-basaltic-volcanoes-genetic-classification-growth-geomorphology-and-degradation",totalDownloads:6196,totalCrossrefCites:71,totalDimensionsCites:143,abstract:null,book:{id:"3088",slug:"updates-in-volcanology-new-advances-in-understanding-volcanic-systems",title:"Updates in Volcanology",fullTitle:"Updates in Volcanology - New Advances in Understanding Volcanic Systems"},signatures:"Gábor Kereszturi and Károly Németh",authors:[{id:"51162",title:"Dr.",name:"Károly",middleName:null,surname:"Németh",slug:"karoly-nemeth",fullName:"Károly Németh"},{id:"62029",title:"Dr.",name:"Gabor",middleName:null,surname:"Kereszturi",slug:"gabor-kereszturi",fullName:"Gabor Kereszturi"}]},{id:"38733",doi:"10.5772/51270",title:"An Overview of Mud Volcanoes Associated to Gas Hydrate System",slug:"an-overview-of-mud-volcanoes-associated-to-gas-hydrate-system",totalDownloads:3993,totalCrossrefCites:13,totalDimensionsCites:22,abstract:null,book:{id:"3088",slug:"updates-in-volcanology-new-advances-in-understanding-volcanic-systems",title:"Updates in Volcanology",fullTitle:"Updates in Volcanology - New Advances in Understanding Volcanic Systems"},signatures:"Umberta Tinivella and Michela Giustiniani",authors:[{id:"151612",title:"Dr.",name:"Umberta",middleName:null,surname:"Tinivella",slug:"umberta-tinivella",fullName:"Umberta Tinivella"},{id:"151614",title:"Dr.",name:"Michela",middleName:null,surname:"Giustiniani",slug:"michela-giustiniani",fullName:"Michela Giustiniani"}]},{id:"52524",doi:"10.5772/65425",title:"Earthquakes and Structural Damages",slug:"earthquakes-and-structural-damages",totalDownloads:3391,totalCrossrefCites:14,totalDimensionsCites:21,abstract:"Earthquakes are the most destructive natural hazards throughout human history. Hundreds of thousand people lost their lives and loss of billions of dollars’ properties occurred in these disasters. Occurred medium or high-intensity magnitude earthquakes in last twenty years showed that these loses continue. For reinforced concrete (R/C) buildings, inappropriate design such as soft and weak stories, strong beam–weak column, short column, hammering, unconfined gable wall and in-plane/out-of-plane movement of the walls causes damages. These are the main reasons. In addition to this, low quality of structural materials, poor workmanship, lack of engineering services, and construction with insufficient detailing of the structural elements are the another reasons of damages. Main reasons of masonry building damages in terms of design faults can be shown as heavy earthen roofs, inappropriate detailing of wall to wall connection and wall to roof connection, absence of bond beams, large openings. However, construction of buildings by using local materials with poor workmanship on the base of traditional rules is the other reason of failures for these buildings. In this book chapter, earthquakes and reasons of damages arose from earthquakes for reinforced concrete and masonry structures were presented. In addition to this, appropriate solutions are suggested.",book:{id:"5499",slug:"earthquakes-tectonics-hazard-and-risk-mitigation",title:"Earthquakes",fullTitle:"Earthquakes - Tectonics, Hazard and Risk Mitigation"},signatures:"Burak Yön, Erkut Sayın and Onur Onat",authors:[{id:"192483",title:"Dr.",name:"Burak",middleName:null,surname:"Yön",slug:"burak-yon",fullName:"Burak Yön"},{id:"192486",title:"Dr.",name:"Erkut",middleName:null,surname:"Sayın",slug:"erkut-sayin",fullName:"Erkut Sayın"},{id:"192487",title:"Dr.",name:"Onur",middleName:null,surname:"Onat",slug:"onur-onat",fullName:"Onur Onat"}]},{id:"52565",doi:"10.5772/65511",title:"Earthquake Prediction",slug:"earthquake-prediction",totalDownloads:2049,totalCrossrefCites:11,totalDimensionsCites:21,abstract:"Among the countless natural disasters, earthquakes are capable to inflict vast devastation to a large number of buildings and constructions at the blink of an eye. Lack of knowledge and awareness on earthquake as well as its comeback is conspicuous and results in disaster; leading to bitter memories. Therefore, earthquake forecast has been a polemical study theme that has defied even the most intelligent of minds. In this chapter, an attempt was made to do an extensive overview in the area of the earthquake prediction as well as classifying them into the main strategies comprising short‐, immediate‐, and long‐term prediction. An example of each strategy was carried out by mentioning their corresponding approaches/algorithms, such as ΔCFS, CN, MSc, M8, ANN, FFBPANN, KNN, GRNN, RBF, and LMBP; depending on the importance of each strategy. Based on these, it was concluded that, after the Tohoku‐Oki earthquake with M9.0, the current orientation of the Headquarters for earthquake Research Promotion of MEXT in Japan declare that, their mission would be long‐term statistical forecast of seismicity. Even, it is claimed that they do not emphasize on short‐term forecasting. Besides, intermediate‐term estimations are not capable to be used for prevention of all damages and protect all human life, but they may be utilized to undertake certain affordable activities to decrease damage, losses, and modify postdisaster relief. And, despite the long‐term prediction is more concerned by researchers, there is no certain satisfactory level to content them. De facto, the made covenant of 1970 that investigators will be capable to forecast/predict ground excitations within a decade, still remains unmet.",book:{id:"5499",slug:"earthquakes-tectonics-hazard-and-risk-mitigation",title:"Earthquakes",fullTitle:"Earthquakes - Tectonics, Hazard and Risk Mitigation"},signatures:"Khaled Ghaedi and Zainah Ibrahim",authors:[{id:"190572",title:"Dr.",name:"Khaled",middleName:null,surname:"Ghaedi",slug:"khaled-ghaedi",fullName:"Khaled Ghaedi"},{id:"196228",title:"Prof.",name:"Zainah",middleName:null,surname:"Ibrahim",slug:"zainah-ibrahim",fullName:"Zainah Ibrahim"}]}],mostDownloadedChaptersLast30Days:[{id:"41664",title:"Volcanic Natural Resources and Volcanic Landscape Protection: An Overview",slug:"volcanic-natural-resources-and-volcanic-landscape-protection-an-overview",totalDownloads:3782,totalCrossrefCites:2,totalDimensionsCites:4,abstract:null,book:{id:"3088",slug:"updates-in-volcanology-new-advances-in-understanding-volcanic-systems",title:"Updates in Volcanology",fullTitle:"Updates in Volcanology - New Advances in Understanding Volcanic Systems"},signatures:"Jiaqi Liu, Jiali Liu, Xiaoyu Chen and Wenfeng Guo",authors:[{id:"60000",title:"Prof.",name:"Jiaqi",middleName:null,surname:"Liu",slug:"jiaqi-liu",fullName:"Jiaqi Liu"}]},{id:"31815",title:"Disaster Management Based on Business Process Model Through the Plant Lifecycle",slug:"disaster-management-based-on-business-process-model-through-the-plant-lifecycle",totalDownloads:2727,totalCrossrefCites:6,totalDimensionsCites:10,abstract:null,book:{id:"600",slug:"approaches-to-managing-disaster-assessing-hazards-emergencies-and-disaster-impacts",title:"Approaches to Managing Disaster",fullTitle:"Approaches to Managing Disaster - Assessing Hazards, Emergencies and Disaster Impacts"},signatures:"Yukiyasu Shimada, Teiji Kitajima, Tetsuo Fuchino and Kazuhiro Takeda",authors:[{id:"70197",title:"Dr.",name:"Yukiyasu",middleName:null,surname:"Shimada",slug:"yukiyasu-shimada",fullName:"Yukiyasu Shimada"},{id:"82055",title:"Dr.",name:"Tetsuo",middleName:null,surname:"Fuchino",slug:"tetsuo-fuchino",fullName:"Tetsuo Fuchino"},{id:"82056",title:"Prof.",name:"Teiji",middleName:null,surname:"Kitajima",slug:"teiji-kitajima",fullName:"Teiji Kitajima"},{id:"121284",title:"Dr.",name:"Kazuhiro",middleName:null,surname:"Takeda",slug:"kazuhiro-takeda",fullName:"Kazuhiro Takeda"}]},{id:"52524",title:"Earthquakes and Structural Damages",slug:"earthquakes-and-structural-damages",totalDownloads:3388,totalCrossrefCites:14,totalDimensionsCites:21,abstract:"Earthquakes are the most destructive natural hazards throughout human history. Hundreds of thousand people lost their lives and loss of billions of dollars’ properties occurred in these disasters. Occurred medium or high-intensity magnitude earthquakes in last twenty years showed that these loses continue. For reinforced concrete (R/C) buildings, inappropriate design such as soft and weak stories, strong beam–weak column, short column, hammering, unconfined gable wall and in-plane/out-of-plane movement of the walls causes damages. These are the main reasons. In addition to this, low quality of structural materials, poor workmanship, lack of engineering services, and construction with insufficient detailing of the structural elements are the another reasons of damages. Main reasons of masonry building damages in terms of design faults can be shown as heavy earthen roofs, inappropriate detailing of wall to wall connection and wall to roof connection, absence of bond beams, large openings. However, construction of buildings by using local materials with poor workmanship on the base of traditional rules is the other reason of failures for these buildings. In this book chapter, earthquakes and reasons of damages arose from earthquakes for reinforced concrete and masonry structures were presented. In addition to this, appropriate solutions are suggested.",book:{id:"5499",slug:"earthquakes-tectonics-hazard-and-risk-mitigation",title:"Earthquakes",fullTitle:"Earthquakes - Tectonics, Hazard and Risk Mitigation"},signatures:"Burak Yön, Erkut Sayın and Onur Onat",authors:[{id:"192483",title:"Dr.",name:"Burak",middleName:null,surname:"Yön",slug:"burak-yon",fullName:"Burak Yön"},{id:"192486",title:"Dr.",name:"Erkut",middleName:null,surname:"Sayın",slug:"erkut-sayin",fullName:"Erkut Sayın"},{id:"192487",title:"Dr.",name:"Onur",middleName:null,surname:"Onat",slug:"onur-onat",fullName:"Onur Onat"}]},{id:"41478",title:"Monogenetic Basaltic Volcanoes: Genetic Classification, Growth, Geomorphology and Degradation",slug:"monogenetic-basaltic-volcanoes-genetic-classification-growth-geomorphology-and-degradation",totalDownloads:6195,totalCrossrefCites:71,totalDimensionsCites:142,abstract:null,book:{id:"3088",slug:"updates-in-volcanology-new-advances-in-understanding-volcanic-systems",title:"Updates in Volcanology",fullTitle:"Updates in Volcanology - New Advances in Understanding Volcanic Systems"},signatures:"Gábor Kereszturi and Károly Németh",authors:[{id:"51162",title:"Dr.",name:"Károly",middleName:null,surname:"Németh",slug:"karoly-nemeth",fullName:"Károly Németh"},{id:"62029",title:"Dr.",name:"Gabor",middleName:null,surname:"Kereszturi",slug:"gabor-kereszturi",fullName:"Gabor Kereszturi"}]},{id:"62769",title:"Disaster Mitigation Model of Eruption Based on Local Wisdom in Indonesia",slug:"disaster-mitigation-model-of-eruption-based-on-local-wisdom-in-indonesia",totalDownloads:1462,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Kelud is one of the most active volcanoes in Indonesia and suffered a major eruption in 2014. Although they are not part of the super volcano, the impact of the eruption is extraordinary. However, the eruption is not too worrying for the surrounding community. The lack of disaster victims caused by the eruption in 2014 became a successful representation of disaster mitigation models owned by local communities in answering the eruption problem. The easy evacuation process and quickly post-eruption rehabilitation illustrate a pattern of environmental adaptation around the volcano. This discussion focuses on how the people behavior around the volcano in responding to the challenge of eruption? How the role of local government in preparing the community in the face of an eruption, and what actions are done so that the rehabilitation process can take place quickly? To answer all these questions, the researchers collected relevant data through observation, documentation, and interviews with the local communities and local government representatives directly involved in disaster mitigation measures. In addition, the researchers also revealed local traditions that are considered capable of supporting the process of preparing the community in answering the eruption challenges and becoming part of disaster mitigation in the volcanic region.",book:{id:"6821",slug:"natural-hazards-risk-assessment-and-vulnerability-reduction",title:"Natural Hazards",fullTitle:"Natural Hazards - Risk Assessment and Vulnerability Reduction"},signatures:"Eko Hariyono and Solaiman Liliasari",authors:[{id:"214360",title:"Dr.",name:"Eko",middleName:null,surname:"Hariyono",slug:"eko-hariyono",fullName:"Eko Hariyono"},{id:"219699",title:"Prof.",name:"Liliasari",middleName:null,surname:"S",slug:"liliasari-s",fullName:"Liliasari S"}]}],onlineFirstChaptersFilter:{topicId:"106",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81241",title:"Physiological and Molecular Adaptation of Sugarcane under Drought vis-a-vis Root System Traits",slug:"physiological-and-molecular-adaptation-of-sugarcane-under-drought-vis-a-vis-root-system-traits",totalDownloads:21,totalDimensionsCites:0,doi:"10.5772/intechopen.103795",abstract:"Among various abiotic stresses, water is reported as a rare entity in many parts of the world. Decreased frequency of precipitation and global temperature rise will further aggravate the situation in future. Being C4 plant, sugarcane requires generous water for the proper growth. Plant root system primarily supports above-ground growth by anchoring in the soil and facilitates water and nutrients uptake from the soil. The plasticity and dynamic nature of roots endow plants for the uptake of vital nutrients from the soil even under soil moisture conditions. In sugarcane, the major part of root system are generally observed in the upper soil layers, while limited water availability shifts the root growth towards the lower soil layer to sustained water uptake. In addition, root traits are directly related to physiological traits of the shoot to cope up with water limited situations via reduction in stomatal conductance and an upsurge in density and deep root traits, adaptations at biochemical and molecular level which includes osmotic adjustment and ROS detoxification. Under stressed conditions, these complex interactive systems adjust homeo-statically to minimize the adverse impacts of stress and sustain balanced metabolism. Therefore, the present chapter deals with physiological and biochemical traits along with root traits that helps for better productivity of sugarcane under water-limited conditions.",book:{id:"11131",title:"Drought - Impacts and Management",coverURL:"https://cdn.intechopen.com/books/images_new/11131.jpg"},signatures:"Pooja Dhansu, Arun Kumar Raja, Krishnapriya Vengavasi, Ravinder Kumar, Adhini S. Pazhany, Ashwani Kumar, Naresh Kumar, Anita Mann and Shashi Kant Pandey"},{id:"79973",title:"Impacts of Drought on Homestead Plant Diversity in Barind Tract of Bangladesh",slug:"impacts-of-drought-on-homestead-plant-diversity-in-barind-tract-of-bangladesh",totalDownloads:6,totalDimensionsCites:0,doi:"10.5772/intechopen.101885",abstract:"Homestead is a great place for household food access, diet, and nutrition. Drought affects homestead plant diversity and reduces production, availability, and diversity that lead toward less supply and consumption. Drought detains moisture and degrades the soil that supports plant growth. Homestead provides regular bread and income in the rural areas with an effective means for both economic and environmental well-being. People are getting a good amount of subsidiary income without any extra care and effort. In managing homestead land and drought, the household needs necessary technical and managerial training. In reducing drought effects to the homestead, action research needs to be carried out on available knowledge, effective practices, water management, and the adoption of local varieties and knowledge to develop effective homestead integration. Government initiatives, community engagement and not harming the environment, and efficient uses of water could be great solutions for the adverse effects of drought on the homestead plant diversity.",book:{id:"11131",title:"Drought - Impacts and Management",coverURL:"https://cdn.intechopen.com/books/images_new/11131.jpg"},signatures:"Md. Shafiqul Islam and Md. Nazrul Islam Mukul"},{id:"82110",title:"Hydrological Drought Index Based on Discharge",slug:"hydrological-drought-index-based-on-discharge",totalDownloads:28,totalDimensionsCites:0,doi:"10.5772/intechopen.104625",abstract:"Drought is a natural phenomenon causing disasters and its period of occurrence can be predicted in recent times based on several methods using the same or different variables. The prediction is usually associated with the climate interactions in the form of rainfall or discharge patterns which can be analyzed using the return period. Therefore, this research was conducted in four different stages of data acquisition and validation, drought analysis method based on the data, drought prediction method based on hydrology, and sample applications to determine the debit availability in other watersheds. Historical rainfall data converted to dependable rainfall at 80% probability were used as input for the rainfall-discharge analysis while the hydrological drought analysis was conducted using the drought threshold value. Moreover, the drought was predicted using an artificial neural network model while historical data were used to verify the hydrological character of the prediction model. The results of the analysis conducted were further used to predict the water balance in different river areas due to the fact that each area has a different hydrological character. Meanwhile, the watersheds used as case research showed that the model has reliability of up to 80%.",book:{id:"11131",title:"Drought - Impacts and Management",coverURL:"https://cdn.intechopen.com/books/images_new/11131.jpg"},signatures:"R. Rintis Hadiani, Bambang Suharto, Agus Suharyanto and Suhardjono"},{id:"81203",title:"Climate Change: A Real Danger to Human and Animal Survival",slug:"climate-change-a-real-danger-to-human-and-animal-survival",totalDownloads:42,totalDimensionsCites:0,doi:"10.5772/intechopen.103022",abstract:"Some countries in Southern Africa where hit by either a storm or cyclone or both in 2019 alone manifesting a changing climate. Infrastructure and cropping land was destroyed, both animal and human lives were lost due to the flooding events. Drought is a common phenomenon in this region, often occurring once in three years. This has affected food, feed and nutritional security of both humans and livestock. Saline soils unsuitable for agriculture, other animal and plant life are expanding fast due to insufficient precipitation. Soil degradation is on the rise, leaving soils with poor water holding capacity to support sustainable agriculture. Climate change is changing the environment and new pests and diseases for both crops and livestock are emerging. World governments, industries and general populace should find better ways of reducing air pollution by greenhouse gases which have a net effect of damaging the ozone layer and increasing atmospheric temperatures. At the same time, plant and animal breeding should aim at improving crop cultivars and animal breeds that resist to the constraints such as drought and heat stress brought by climate change. The human population is increasing at an alarming rate and need both food and nutritional security.",book:{id:"11131",title:"Drought - Impacts and Management",coverURL:"https://cdn.intechopen.com/books/images_new/11131.jpg"},signatures:"Godwill Makunde, Nation Chikumba, Walter Svinurai and Xavier Mhike"},{id:"81810",title:"Water Shortages: Cause of Water Safety in Sub-Saharan Africa",slug:"water-shortages-cause-of-water-safety-in-sub-saharan-africa",totalDownloads:27,totalDimensionsCites:0,doi:"10.5772/intechopen.103927",abstract:"This chapter highlights a high rate of water crisis across sub-Saharan Africa (SSA) despite its huge hydro-potential. Factors contributing to water stress include rainfall deficit and drought, increased water requirements, population growth, urbanization, and poverty. Coupled with the uneven distribution of water resources and mismanagement of water facilities, the gap between the demand for water and available supply has deepened. 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He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"426586",title:"Dr.",name:"Oladunni A.",middleName:null,surname:"Daramola",slug:"oladunni-a.-daramola",fullName:"Oladunni A. Daramola",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Federal University of Technology",country:{name:"Nigeria"}}},{id:"357014",title:"Prof.",name:"Leon",middleName:null,surname:"Bobrowski",slug:"leon-bobrowski",fullName:"Leon Bobrowski",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Bialystok University of Technology",country:{name:"Poland"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"354126",title:"Dr.",name:"Setiawan",middleName:null,surname:"Hadi",slug:"setiawan-hadi",fullName:"Setiawan Hadi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Padjadjaran University",country:{name:"Indonesia"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"332603",title:"Prof.",name:"Kumar S.",middleName:null,surname:"Ray",slug:"kumar-s.-ray",fullName:"Kumar S. Ray",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Statistical Institute",country:{name:"India"}}},{id:"415409",title:"Prof.",name:"Maghsoud",middleName:null,surname:"Amiri",slug:"maghsoud-amiri",fullName:"Maghsoud Amiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Allameh Tabataba'i University",country:{name:"Iran"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}}]}},subseries:{item:{id:"13",type:"subseries",title:"Plant Physiology",keywords:"Plant Nutrition, Plant Hormone, Photosynthesis, Respiration, Plant Stress, Multi-omics, High-throughput Technology, Genome Editing",scope:"Plant Physiology explores fundamental processes in plants, and it includes subtopics such as plant nutrition, plant hormone, photosynthesis, respiration, and plant stress. 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Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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