Research framework.
\r\n\tOver the years, the concept of maintenance became more comprehensive, reducing fault occurrence and increasing industrial system availability. Besides, reliability, safety, and criticality requirements were associated with the system or equipment under analysis. Maintenance strategies or schemes can be classified as corrective (run-to-break), preventive (time-based), and predictive (condition-based maintenance). Corrective maintenance is only performed after an occurrence of a fault. Therefore, it involves unexpected breakdowns, high costs, changes in the production chain, and it could lead to catastrophic events. Preventive maintenance and interventions occur based on a scheduled maintenance plan or the equipment's mean time between failures. Although it is more effective than corrective maintenance, unexpected failure may still occur by preventing most failures. Additionally, the process cost is still high, especially the costs associated with labor, inventory, and unnecessary replacement of equipment or components.
\r\n\tOn the other hand, predictive maintenance analyses the equipment condition so that a possible fault can still be identified at an early stage. Predictive maintenance aims to identify a machine anomaly so that it does not result in a fault. Such maintenance involves advanced monitoring, processing, and signal analysis techniques, which are generally performed non-invasively and, in many cases, in real-time. In the case of machines or processes, these techniques can be developed based on vibration, temperature, acoustic emission, or electrical current signal monitoring. It should be noted that monitoring such signals or parameters to verify the operating condition is called condition monitoring. Condition monitoring aims to observe the machine's current operational condition and predict its future condition, keeping it under a systematic analysis during its remaining life. In this sense, a fault condition can be detected and identified from systematic machine condition monitoring. A diagnosis procedure can be established, whereby properly investigating the fault symptoms and prognosis.
\r\n\t
\r\n\tThis book will aim to merge all these ideas in a single volume, aggregate new maintenance experiences, apply new techniques and approaches, and report field experiences to establish new maintenance processes and management paradigms.
\r\n\t
Construction projects involve participants from different specialties working together which makes the cooperation among them designed around extensive, disparate and interrelated processes [1]. Such complexity is also increased by other external factors such as political, legal, cultural, technological and financial, which resulted in project risk. Project Management Institute (PMI) defines project risk as “an uncertain event or condition that, if it occurs, has a positive or negative effect on a project objective. … there will be a consequence on the project cost, schedule, or quality” [2]. Due to the increasing size and complexity, a wide variety of risks impact the successful completion of the construction projects. In other words, risks are threats to project success [3]. Despite trying to eliminate all the risks in construction projects is impossible, a formal risk management process is required to manage them effectively [4].
\nIn this regard, a systematic risk management process can help construction companies to identify not only the involved risks of projects but also to mitigate impacts of those uncertainties in different phases of projects [5]. The term “risk management” can be broadly defined as work that classifies, analyses and responds to unpredictable risks that exist in the processes of project implementation [6]. Risk management is about defining sources of uncertainty (risk identification), estimating the consequences of uncertain events/conditions (risk analysis), generating response strategies in the light of expected outcomes and, finally, based on the feedback received on actual outcomes and risks emerged, carrying out identification, analysis and response generation steps repetitively throughout the life cycle of a project to ensure that the project objectives are met [7]. Briefly, a traditional risk management process consists of risk identification, risk analysis or assessment, risk response or mitigation and risk monitoring and control [2, 8].
\nThe initial step of risk management is risk identification. Risk identification is the process of identifying individual project risks as well as sources of overall project risk and documenting their characteristics [2]. Although it is difficult to define and measure, it is very important to identify potential risks as early as possible. In order to manage risks properly, risk identification should be performed along with the project’s initiation stage. Construction companies usually benefit from risk checklists [9, 10] and risk breakdown structures [9, 11, 12] for the identification.
\nRisk analysis/assessment is the process that focuses on evaluating and seeking the likelihood in which potential risks in the risk identification stage may occur [13] and it is implemented by two approaches: qualitative risk analysis and quantitative risk analysis. In qualitative risk analysis process, the main focuses are rating and prioritizing individual project risks for further analysis or action by assessing their probability of occurrence and severity of consequence/impact as well as other characteristics [2, 14]. On the other hand, quantitative risk analysis process focuses on numerically analyzing the combined effect of identified individual project risks and other sources of uncertainty on overall project objectives [2]. Researchers employed Delphi [15, 16, 17], AHP/fuzzy AHP [10, 17, 18, 19, 20, 21, 22, 23] and Monte Carlo simulation [24, 25, 26] to assess risks in their studies.
\nRisk response process consists of developing options, selecting strategies and agreeing on actions to address overall project risk exposure, as well as to treat individual project risks, and finally implementing agreed-upon risk response plans [2]. Dealing with negative consequences, risk response is also referred to as risk mitigation, risk elimination, risk prevention and risk reduction [8]. Appropriate risk response strategies must be selected to reduce risk exposure once the risks have been identified and analyzed [27]. Researchers widely agree that the selection of risk response strategy is an important issue in project risk management [28, 29, 30]. These strategies are avoiding, reducing or accepting project risks.
\nRisk monitoring and control process is the process of monitoring the implementation of agreed-upon risk response plans, tracking identified risks, identifying and analyzing new risks and evaluating risk process effectiveness throughout the project [2]. This step ensures that all information generated by risk management process is captured, used and maintained throughout the construction period [31].
\nThe subject of risk management in construction projects has been increasingly studying since the 1980s. Most of these studies have focused on how risks are identified or analyzed/assessed in different countries such as Australia [32, 33], China [23, 34, 35], Ghana [36], Hong Kong [37, 38], India [39, 40], Indonesia [41, 42], Italy [43], Korea [44], Malaysia [31, 45], Mexico [46], New Zealand [47, 48], Nigeria [49, 50], Poland [51], Singapore [52, 53], Spain [54], Sri Lanka [55], Tanzania [56], the United Kingdom [57, 58], the United States of America [59, 60], Vietnam [61, 62] and Zambia [63]. These studies mostly used survey/interviews or case studies. Additionally, researchers proposed that various theoretical and mathematical models are also proposed for managing risks effectively and efficiently.
\nWhile literature is rich in papers addressing risk management in construction projects, few papers have researched what has already been presented. Edwards and Bowen’s [64] research is one of the exceptional studies which analytically reviews the construction risk literature over the period from 1960 to 1997. Given that two decades have passed since then, it is appropriate to review the progress in risk management research in construction. In this regard, this paper aims to analyze current literature and provide a guide for future studies on risk management in construction projects.
\nTo review the risk management literature comprehensively, a twofold procedure was adopted in this study. At first, a systematic literature review was conducted to identify the key scientific contributions in the risk management domain. The findings of the review, then, were statistically synthesized through a meta-analytical approach which is an associated procedure of systematic literature review.
\nSystematic literature review adopts a replicable, scientific and transparent process that aims to minimize bias through exhaustive literature searches of published studies [65]. On the other hand, meta-analysis helps to analyse these studies by interrelating focused areas and identifying emerging or neglected themes [66].
\nIn this regard, this study has been organized in two stages represented in Figure 1.
\nStages of the systematic literature review.
The first stage concentrates on searching for relevant papers using scientific databases, namely, American Society of Civil Engineers (ASCE), Elsevier, Emerald and Taylor & Francis. From these databases, relevant papers were searched in the following construction and built environment-related journals: Automation in Construction (AC), International Journal of Project Management (IJPM), Journal of Cleaner Production (JCP), Architectural Engineering and Design Management (AEDM), Construction Management and Economics (CME), International Journal of Construction Education and Research (JCER), International Journal of Construction Management (IJCM), Journal of Civil Engineering and Management (CEM), Journal of Construction Engineering and Management (JCEM), Journal of Management in Engineering (JME), Journal of Legal Affairs and Dispute Resolution in Engineering and Construction (LADR), Journal of Professional Issues in Engineering Education and Practice (PEEP), Journal of Architectural Engineering (JAE), Engineering Construction and Architectural Management (ECAM), Construction Innovation (CI), Journal of Financial Management of Property (JFMP), Facilities (F), Built Environment Project and Asset Management (BEPAM), Journal of Facilities Management (JFM), International Journal of Building Pathology and Adaptation (JBPA) and Management Decision (MD).
\nThe keywords for searching were designated as “risk management” and “construction projects,” and these keywords were searched in title/abstract/keyword fields of the selected journals in the time period between 1980 and 2018. At this point, a total of 471 papers, excluding book reviews, forums and editorials, were retrieved for further analysis. Eventually, 247 papers were considered as the most relevant to the research aim and were subject to a detailed review.
\nIn the second stage, a meta-classification framework, adopted from Betts and Lansley [66], was designed as presented in Table 1. Accordingly, the framework has nine categories, such as year, scientific database, journal, keyword, research focus, level of analysis, source of information, research output and future directions with their related subcategories.
\nCategory | \nSubcategory | \n
---|---|
Year | \nPublication date of the article | \n
Scientific database | \nASCE, Elsevier, Emerald, Taylor & Francis | \n
Journal | \nName of the journals | \n
Keyword | \n“Risk management” and “construction projects” | \n
Research focus | \nRisk identification Risk assessment/analysis Risk evaluation Risk response Risk monitoring and control | \n
Level of analysis | \nProject level Firm level Sector level | \n
Source of information | \nReview Case study Survey/interview | \n
Research output | \nGeneral insights and descriptions Statistical results Theoretical model Mathematical model Experimental/prototype model | \n
Future directions | \nFuture research identified in the articles | \n
Research framework.
The 247 papers were analyzed according to this framework and classified by one of these subcategories. In some cases, a paper may be classified in multiple subcategories, resulting in the sum of the papers distributed among the subcategories exceeding the number of papers analyzed.
\nRisk management in construction projects was analysed according to the meta-classification framework given in Table 1. It is found that 247 papers have been published on “risk management” in the specified time period in the widely accepted construction and built environment-related peer-reviewed journals.
\nTable 2 shows the chronological distribution of the selected papers by a 5-year time period. Accordingly, risk management subject shows an increasing tendency over the years. In addition, half of these papers have been published in the ASCE’s Journal of Construction Engineering and Management.
\nDatabase | \nJournal | \n≤1995 | \n1996–2000 | \n2001–2005 | \n2006–2010 | \n2011–2015 | \n>2015 | \n
---|---|---|---|---|---|---|---|
Elsevier | \nAC | \n\n | \n | \n | 3 | \n4 | \n\n |
IJPM | \n1 | \n1 | \n2 | \n4 | \n4 | \n1 | \n|
JCP | \n\n | \n | \n | \n | \n | 3 | \n|
Taylor & Francis | \nAEDM | \n\n | \n | \n | 1 | \n1 | \n1 | \n
CME | \n1 | \n4 | \n2 | \n6 | \n2 | \n\n | |
JCER | \n\n | \n | \n | 1 | \n1 | \n\n | |
IJCM | \n\n | \n | 1 | \n1 | \n4 | \n5 | \n|
CEM | \n\n | \n | \n | 1 | \n6 | \n3 | \n|
ASCE | \nJCEM | \n6 | \n9 | \n12 | \n27 | \n29 | \n23 | \n
JME | \n\n | \n | 1 | \n2 | \n11 | \n11 | \n|
LADR | \n\n | \n | \n | \n | \n | 2 | \n|
PEEP | \n\n | 2 | \n\n | 3 | \n2 | \n\n | |
JAE | \n\n | 1 | \n\n | \n | \n | \n | |
Emerald | \nECAM | \n\n | 3 | \n3 | \n2 | \n6 | \n6 | \n
CI | \n\n | \n | \n | \n | \n | 2 | \n|
JFMP | \n\n | \n | \n | 4 | \n\n | 1 | \n|
F | \n\n | \n | \n | \n | 1 | \n2 | \n|
BEPAM | \n\n | \n | \n | \n | 2 | \n1 | \n|
JFM | \n\n | \n | 1 | \n1 | \n4 | \n1 | \n|
JBPA | \n\n | \n | 1 | \n\n | \n | \n | |
MD | \n\n | \n | 1 | \n\n | \n | \n | |
Total | \n8 | \n20 | \n24 | \n56 | \n77 | \n62 | \n
Distribution of the selected papers within the time span.
Table 3 presents the research focus of the published papers over the years. As given in Table 3, research focus was classified into ten categories. These categories include four processes of risk management and their multiple combinations. It is noticeable that researchers studied the risk management subject whether discussing one of the processes, such as risk identification, risk analysis/assessment, risk response and risk monitoring and control, or examining them through a holistic approach. Despite most of the papers focused only on risk analysis/assessment, a considerable amount of papers studied other risk management processes together with risk analysis/assessment subject. Besides, risk response and risk monitoring and control seem to be neglected processes of risk management. Recently, it is seen that these processes have started to be mentioned in risk management-related researches. Still, they do not have similar impact in the construction risk management literature compared with risk identification and risk analysis/assessment processes.
\nAnalysis of selected papers according to the research focus.
RI: risk identification, RA: risk analysis/assessment, RR: risk response, RMC: risk monitoring & control.
Most commonly used keywords in the analyzed papers are given in Table 4. It is not surprising that “risk management” keyword has the largest rate with 28.9%. The second highly rated keyword is risk (financial, political, design, economic, social, legal, safety) with the rate of 23.8%. This is followed by other keywords such as construction management/project management (11.6%), risk assessment including risk prioritization, risk score and risk rating (11.2%); risk analysis (6.0%); risk identification including checklist, risk mapping and risk breakdown structure (5.8%); cost-related issues (4.7%); risk allocation/distribution (2.0%); risk modeling (1.3%); risk response (1.1%); risk control (0.6%); risk mitigation (0.6%); risk perception/attitude (0.6%); risk strategy (0.4%); risk interruptions (0.2%); risk paths (0.2%); and risk propagation (0.2%).
\nKeywords | \nNumber of papers | \nFrequency (%) | \n
---|---|---|
Risk management | \n129 | \n28.99 | \n
Risk | \n106 | \n23.82 | \n
Construction management/project management | \n52 | \n11.68 | \n
Risk assessment | \n50 | \n11.23 | \n
Risk analysis | \n27 | \n6.06 | \n
Risk identification | \n26 | \n5.84 | \n
Cost related issues | \n21 | \n4.71 | \n
Risk allocation/distribution | \n9 | \n2.02 | \n
Risk modeling | \n6 | \n1.34 | \n
Risk response | \n5 | \n1.12 | \n
Risk control | \n3 | \n0.67 | \n
Risk mitigation | \n3 | \n0.67 | \n
Risk perception/attitude | \n3 | \n0.67 | \n
Risk strategy | \n2 | \n0.44 | \n
Risk interruptions | \n1 | \n0.22 | \n
Risk paths | \n1 | \n0.22 | \n
Risk propagation | \n1 | \n0.22 | \n
Analysis of selected papers according to the keywords.
The papers are analyzed according to the study levels as project level, firm level and sector level. Figure 2 shows the distribution of these levels within the time span. As seen in Figure 2, the majority of the papers are studied in the project level. This is resulted from researchers mostly focused how risk is managed within a construction project rather than concentrating on the risks and their effect within a construction company or in the construction sector. Especially beginning with 2006, a huge focus has given to construction risk management studies at the project level. However, there are few studies which concentrate risk management related issues by discussing them through the firm and sector level.
\nAnalysis of selected papers according to the level of analysis.
Different sources of information are used in the analyzed papers which were classified as case studies, survey/interviews and reviews. As illustrated in Figure 3, among these, case studies and survey/interviews are the leading sources. After 2005, case studies and survey/interviews show a rapid increase. This reveals that secondary data and data collected from sector professionals are the main sources of information in the analyzed papers. On the other hand, reviews are relatively less preferred information source for risk management researches.
\nAnalysis of selected papers according to the sources of information.
The main outputs of the papers are shown in Figure 4, which were classified into five categories as general insights and descriptions, statistical results, theoretical model, mathematical model and experimental/prototype model. The main contribution is statistical results followed by mathematical model. Since most of the papers adopted a research methodology based on case studies and survey/interviews, it is reasonable that the research output shows a high tendency in statistical results. General insights and descriptions, theoretical models and experimental/prototype models are less adopted methodologies compared with other ones.
\nAnalysis of selected papers according to the research output.
No construction project is risk-free: risk can be managed, minimized, shared, transferred or accepted; but it cannot be ignored [67]. Construction companies should adopt an appropriate risk management approach not only to complete their projects in compliance with their project objectives but also to keep their competitiveness in the construction industry. Although researchers have drawn huge attention on every step of the risk management process, in this chapter, it is aimed to present the state-of-the-art literature by analyzing research contributions in the risk management domain.
\nDespite risk management subject found in the literature has reached saturation point, construction researchers have still been studying different aspects of risk management through implementing various research methodologies. A majority of these researches concentrated on one of the risk management processes that is found in risk identification and risk analysis/assessment. On the other hand, the remaining processes of risk management, namely, risk response and risk monitoring and control, are seemed to be neglected.
\nIn the review, highly mentioned risk-related keywords are revealed as risk management; various risk types; construction management/project management; risk assessment including prioritization, risk score and risk rating; risk analysis; risk identification and its methods such as checklist, risk mapping and risk breakdown structure; cost-related issues; risk allocation/distribution; risk modeling; risk response; risk control; and risk mitigation, respectively. As the results showed that risk response and risk monitoring and control are disregarded areas, their related keywords are less mentioned than the other ones.
\nSince researchers focused how risk is managed within a construction project instead of concentrating on the risks and their effect within a construction company or in the construction sector, a huge number of papers deal with risk management at the project level. Accordingly, studies on risk management at the firm level and sector level seem to be neglected. Besides, as much of the risk management researches in the past decades focused on identification and analysis/assessment of risks within a particular construction project, they mostly adopted survey/interview and case study approaches. This case has resulted in frequent appearance of statistical results as the main research outputs.
\nTo conclude, the review has confirmed that the researchers are directed only on the first two steps of risk management process. In addition to these directions, future studies should also discuss risk response and risk monitoring and control which are the remaining ones. Besides, it is revealed that the literature lacks a comprehensive risk management process. Future studies should adopt a holistic perspective which addresses the risk management process by identifying, analyzing/assessing, responding and monitoring and control from initiation to the completion of construction projects. Similarly, future studies should be directed to risk management-related issues by discussing them at the firm and sector level as well. This systematic review is expected to contribute to the construction profession by enlightening the research gaps in the literature and by providing future directions for potential studies.
\nThe authors of this book chapter declare no “conflict of interest.”
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It describe the bioactive compounds derived from natural resources, its phytochemical analysis, characterization and pharmacological investigation. It focuses on the success of these resources in the process of finding and discovering new and effective drug compounds that can be useful for human resources. From many years, natural products have been acting as a source of therapeutic agents and have shown beneficial uses. Only natural product drug discovery plays an important role to develop the scientific evidence of these natural resources. Research in drug discovery needs to develop robust and viable lead molecules, which step forward from a screening hit to a drug candidate through structural elucidation and structure identification through GC–MS, NMR, IR, HPLC, and HPTLC. The development of new technologies has revolutionized the screening of natural products in discovering new drugs. Utilizing these technologies gives us an opportunity to perform research in screening new molecules using a software and database to establish natural products as a major source for drug discovery. It finally leads to lead structure discovery. Powerful new technologies are revolutionizing natural herbal drug discovery.",book:{id:"8290",slug:"pharmacognosy-medicinal-plants",title:"Pharmacognosy",fullTitle:"Pharmacognosy - Medicinal Plants"},signatures:"Akshada Amit Koparde, Rajendra Chandrashekar Doijad and Chandrakant Shripal Magdum",authors:[{id:"268668",title:"Dr.",name:"Akshada",middleName:"Amit",surname:"Koparde",slug:"akshada-koparde",fullName:"Akshada Koparde"}]},{id:"48805",title:"Biopharmaceutics and Pharmacokinetics",slug:"biopharmaceutics-and-pharmacokinetics",totalDownloads:26121,totalCrossrefCites:2,totalDimensionsCites:7,abstract:null,book:{id:"4491",slug:"basic-pharmacokinetic-concepts-and-some-clinical-applications",title:"Basic Pharmacokinetic Concepts and Some Clinical Applications",fullTitle:"Basic Pharmacokinetic Concepts and Some Clinical Applications"},signatures:"S. Lakshmana Prabu, T.N.K. Suriyaprakash, K. Ruckmani and R.\nThirumurugan",authors:[{id:"91590",title:"Dr.",name:"Sakthivel",middleName:null,surname:"Lakshmana Prabu",slug:"sakthivel-lakshmana-prabu",fullName:"Sakthivel Lakshmana Prabu"},{id:"128690",title:"Dr.",name:"Suriyaprakash",middleName:null,surname:"Tnk",slug:"suriyaprakash-tnk",fullName:"Suriyaprakash Tnk"}]}],onlineFirstChaptersFilter:{topicId:"219",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81238",title:"Artificial Intelligence in Healthcare: An Overview",slug:"artificial-intelligence-in-healthcare-an-overview",totalDownloads:32,totalDimensionsCites:0,doi:"10.5772/intechopen.102768",abstract:"The healthcare industry is advancing ahead swiftly. For many healthcare organizations, being able to forecast which treatment techniques are likely to be successful with patients based on their makeup and treatment framework is a big step forward. Artificial intelligence has the potential to help healthcare providers in a variety of ways, including patient care and administrative tasks. The technology aims to mimic human cognitive functions, as it offers numerous advantages over traditional analytics and other clinical decision-making tools. Data becomes more precise and accurate, allowing the healthcare industry to have more insights into the theranostic processes and patient outcomes. This chapter is an overview of the use of artificial intelligence in radiology, cardiology, ophthalmology, and drug discovery process.",book:{id:"10882",title:"Smart Drug Delivery",coverURL:"https://cdn.intechopen.com/books/images_new/10882.jpg"},signatures:"Syed Shahwar Anwar, Usama Ahmad, Mohd Muazzam Khan, Md. Faheem Haider and Juber Akhtar"},{id:"79411",title:"Phospholipid Based Nano Drug Delivery Systems of Phytoconstituents",slug:"phospholipid-based-nano-drug-delivery-systems-of-phytoconstituents",totalDownloads:123,totalDimensionsCites:0,doi:"10.5772/intechopen.101040",abstract:"The development of phytochemistry and phyto-pharmacology has enabled elucidation of composition and biological activities of several medicinal plant constituents. However phytoconstituents are poorly absorbed due to their low aqueous solubility, large molecular size and poor membrane permeability when taken orally. Nanotechnology based drug delivery systems can be used to improve the dissolution rate, permeability and stability of these phytoconstituents. The current chapter aims to present the extraction of phytoconstituents, their identifications, and development/utilization of phospholipid based nano drug delivery systems (PBNDDS). The content of the chapter also provides characteristic features, in-vitro, in-vivo evaluations and stability performance of PBNDDS. The results from the UHPLC and GC-MS showed different phytoconstituents in the extracted samples with quantitative value. Dynamic light scattering (DLS) data showed PBNDDS of different phytoconstituents in the range of 50–250 nm with PDI value of 0.02–0.5, which was also confirmed by the electron microscopic data. Phytoconstituents loading or entrapment for PBNDDS was in the range of 60–95%. PBNDDS exhibited better in-vitro and in-vivo performance with improved Physico-chemical stability.",book:{id:"10882",title:"Smart Drug Delivery",coverURL:"https://cdn.intechopen.com/books/images_new/10882.jpg"},signatures:"Mohammad Hossain Shariare and Mohsin Kazi"},{id:"79292",title:"Aliphatic Polyester Nanoparticles for Drug Delivery Systems",slug:"aliphatic-polyester-nanoparticles-for-drug-delivery-systems",totalDownloads:109,totalDimensionsCites:0,doi:"10.5772/intechopen.100977",abstract:"Drug delivery systems using aliphatic polyester nanoparticles are usually prepared via an emulsion process. These nanoparticles can control drug release and improve pharmacokinetics. Aliphatic polyesters are linear polymers containing ester linkages, showing sensitivity to hydrolytic degradation. The byproducts then promote autocatalytic degradation. These byproducts could enter the Krebs cycle and be eliminated from the body, resulting in the high biocompatibility of these nanoparticles. The properties of these polyesters are linked to the drug release rate due to biodegradation, i.e., polymer crystallinity, glass transition temperature, polymer hydrophobicity, and molecular weight (MW), all of which relatively influence hydrolysis. Mathematical equations have been used to study the factors and mechanisms that affect drug dissolution compared to experimental release data. The equations used as models for predicting the kinetics of drug release include the zero-order, first-order, Higuchi, Hixson-Crowell, and Korsmeyer-Peppas equations. Aliphatic polyester-based controlled drug delivery has surrounded much of the current activity in the estimation parameters of nanoparticles and stimulated additional research. Polymeric nanoparticles have potential in a wide range of applications, such as in biotechnology, vaccine systems, and the pharmaceutical industry. The main goal of this chapter is to discuss aliphatic polyester nanoparticles as drug carrier systems.",book:{id:"10882",title:"Smart Drug Delivery",coverURL:"https://cdn.intechopen.com/books/images_new/10882.jpg"},signatures:"Narumol Kreua-ongarjnukool, Nopparuj Soomherun, Saowapa Thumsing Niyomthai and Sorayouth Chumnanvej"},{id:"78844",title:"Targeted Nano-Drug Delivery System to Colon Cancer",slug:"targeted-nano-drug-delivery-system-to-colon-cancer",totalDownloads:124,totalDimensionsCites:0,doi:"10.5772/intechopen.100059",abstract:"Cancer has been considered as the most cause of death in world. Employing of nanocarriers as drug delivery systems provide a platform for delivering drugs with increasing the anti-cancer efficacy, enhancing bioavailability of drugs, reducing side effects, enhancing the circulation half-life of drugs, improving the distribution of drugs and overcoming drug resistance. A number of nanocarriers have been studied as drug delivery systems for improving the treatment of cancer including liposomes, micelle, polymeric nanoparticles, carbon nanotubes, dendrimers, solid lipid nanoparticle (SLN) and nanostructure lipid carrier (NLC). In order to enhance recognition and internalization of nanocarriers by the target tissues, their surfaces can be modified with targeting ligands such as integrins, transferrin, folic acid, polysaccharides and antibodies. In this chapter, we are going to introduce the targeted nanocarriers for improving the cytotoxic action of drugs with further attempt of decreasing dose to achieve higher anticancer activity. Targeted nanocarriers would provide a promising therapeutic approach for cancer.",book:{id:"10882",title:"Smart Drug Delivery",coverURL:"https://cdn.intechopen.com/books/images_new/10882.jpg"},signatures:"Eskandar Moghimipour and Somayeh Handali"},{id:"78619",title:"Strategies to Develop Cyclodextrin-Based Nanosponges for Smart Drug Delivery",slug:"strategies-to-develop-cyclodextrin-based-nanosponges-for-smart-drug-delivery",totalDownloads:130,totalDimensionsCites:1,doi:"10.5772/intechopen.100182",abstract:"In recent years, the development of various cyclodextrin (CD)-based nanosponges (NSs) has gained great importance in the controlled and-or targeted release of drugs due to their versatility and simple preparation. In this chapter, an introduction of different administration routes is explained. Further, different ways to obtain CD-NSs and their classification are shown with a brief explanation of the characterization of the inclusion complexes. Finally, illustrative examples in diverse processes or diseases will be reviewed and explained to demonstrate the potential of CD-NSs. Therefore, this division will serve to compile information on CD-NSs in recent years and to illustrate to readers how to generate and apply different derivatives of interest.",book:{id:"10882",title:"Smart Drug Delivery",coverURL:"https://cdn.intechopen.com/books/images_new/10882.jpg"},signatures:"Gjylije Hoti, Silvia Lucia Appleton, Alberto Rubin Pedrazzo, Claudio Cecone, Adrián Matencio, Francesco Trotta and Fabrizio Caldera"},{id:"78313",title:"Smart Drug-Delivery Systems in the Treatment of Rheumatoid Arthritis: Current, Future Perspectives",slug:"smart-drug-delivery-systems-in-the-treatment-of-rheumatoid-arthritis-current-future-perspectives",totalDownloads:206,totalDimensionsCites:0,doi:"10.5772/intechopen.99641",abstract:"Rheumatoid arthritis (RA) is a progressive autoimmune inflammatory disorder characterized by cellular infiltration in synovium causing joint destruction and bone erosion. The heterogeneous nature of the disease manifests in different clinical forms, hence treatment of RA still remains obscure. Treatments are limited owing to systemic toxicity by dose-escalation and lack of selectivity. To overcome these limitations, Smart drug delivery systems (SDDS) are under investigation to exploit the arthritic microenvironment either by passive targeting or active targeting to the inflamed joints via folate receptor, CD44, angiogenesis, integrins. This review comprehensively deliberates upon understanding the pathophysiology of RA and role of SDDSs, highlighting the emerging trends for RA nanotherapeutics.",book:{id:"10882",title:"Smart Drug Delivery",coverURL:"https://cdn.intechopen.com/books/images_new/10882.jpg"},signatures:"Largee Biswas, Vikas Shukla, Vijay Kumar and Anita Kamra Verma"}],onlineFirstChaptersTotal:7},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:320,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:133,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:16,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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",coverUrl:"https://cdn.intechopen.com/series/covers/3.jpg",latestPublicationDate:"June 30th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:8,editor:{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:3,paginationItems:[{id:"1",title:"Oral Health",coverUrl:"https://cdn.intechopen.com/series_topics/covers/1.jpg",editor:{id:"173955",title:"Prof.",name:"Sandra",middleName:null,surname:"Marinho",slug:"sandra-marinho",fullName:"Sandra Marinho",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGYMQA4/Profile_Picture_2022-06-01T13:22:41.png",biography:"Dr. Sandra A. Marinho is an Associate Professor and Brazilian researcher at the State University of Paraíba (Universidade Estadual da Paraíba- UEPB), Campus VIII, located in Araruna, state of Paraíba since 2011. She holds a degree in Dentistry from the Federal University of Alfenas (UNIFAL), while her specialization and professional improvement in Stomatology took place at Hospital Heliopolis (São Paulo, SP). Her qualifications are: a specialist in Dental Imaging and Radiology, Master in Dentistry (Periodontics) from the University of São Paulo (FORP-USP, Ribeirão Preto, SP), and Doctor (Ph.D.) in Dentistry (Stomatology Clinic) from Hospital São Lucas of the Pontifical Catholic University of Rio Grande do Sul (HSL-PUCRS, Porto Alegre, RS). She held a postdoctoral internship at the Federal University from Jequitinhonha and Mucuri Valleys (UFVJM, Diamantina, MG). She is currently a member of the Brazilian Society for Dental Research (SBPqO) and the Brazilian Society of Stomatology and Pathology (SOBEP). Dr. Marinho's experience in Dentistry mainly covers the following subjects: oral diagnosis, oral radiology; oral medicine; lesions and oral infections; oral pathology, laser therapy and epidemiological studies.",institutionString:null,institution:{name:"State University of Paraíba",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"267724",title:"Dr.",name:"Febronia",middleName:null,surname:"Kahabuka",slug:"febronia-kahabuka",fullName:"Febronia Kahabuka",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZpJQAW/Profile_Picture_2022-06-27T12:00:42.JPG",institutionString:null,institution:null}]},{id:"2",title:"Prosthodontics and Implant Dentistry",coverUrl:"https://cdn.intechopen.com/series_topics/covers/2.jpg",editor:{id:"179568",title:"Associate Prof.",name:"Wen Lin",middleName:null,surname:"Chai",slug:"wen-lin-chai",fullName:"Wen Lin Chai",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRHGAQA4/Profile_Picture_2022-05-23T14:31:12.png",biography:"Professor Dr. Chai Wen Lin is currently a lecturer at the Department of Restorative Dentistry, Faculty of Dentistry of the University of Malaya. She obtained a Master of Dental Science in 2006 and a Ph.D. in 2011. Her Ph.D. research work on the soft tissue-implant interface at the University of Sheffield has yielded several important publications in the key implant journals. She was awarded an Excellent Exchange Award by the University of Sheffield which gave her the opportunity to work at the famous Faculty of Dentistry of the University of Gothenburg, Sweden, under the tutelage of Prof. Peter Thomsen. In 2016, she was appointed as a visiting scholar at UCLA, USA, with attachment in Hospital Dentistry, and involvement in research work related to zirconia implant. In 2016, her contribution to dentistry was recognized by the Royal College of Surgeon of Edinburgh with her being awarded a Fellowship in Dental Surgery. She has authored numerous papers published both in local and international journals. She was the Editor of the Malaysian Dental Journal for several years. 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