IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
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IntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
With the desire to make book publishing more relevant for the digital age and offer innovative Open Access publishing options, we are thrilled to announce the launch of our new publishing format: IntechOpen Book Series.
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Designed to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
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After a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
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Our innovative Book Series format brings you:
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Topic Focused Publications - Each topic showcases high impact subject areas
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Renowned Editorial Expertise - Series Editors, Topic Editors, and a team of international Board Members that permanently support each Book Series
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Fast Publishing - quick turnaround which is unique for book publishing
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The benefit of ISSN and ISBN for increased citation and indexing possibilities
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IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\n
IntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
We invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
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Note: Edited in October 2021
\n'}],latestNews:[{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"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"},{slug:"intechopen-identified-as-one-of-the-most-significant-contributor-to-oa-book-growth-in-doab-20210809",title:"IntechOpen Identified as One of the Most Significant Contributors to OA Book Growth in DOAB"}]},book:{item:{type:"book",id:"6380",leadTitle:null,fullTitle:"Cytotoxicity",title:"Cytotoxicity",subtitle:null,reviewType:"peer-reviewed",abstract:"The book Cytotoxicity is aimed to be an essential reading to all medical students, biologists, biochemists and professionals involved in the field of toxicology. This book is a useful and ideal guide for novice researchers interested in learning research methods to study cytotoxic bioactive compounds. The parts of this book describe the replacement and different applications of the cytotoxic agents. All chapters are written by paramount experts in cytotoxicity research. This will hopefully stimulate more research initiatives, funding, and critical insight into the already increasing demand for cytotoxicity researches that have been evidenced worldwide.",isbn:"978-1-78923-431-2",printIsbn:"978-1-78923-430-5",pdfIsbn:"978-1-83881-443-4",doi:"10.5772/intechopen.69919",price:119,priceEur:129,priceUsd:155,slug:"cytotoxicity",numberOfPages:278,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"60d61573c9a66207b8bc54613cac5716",bookSignature:"Tülay Aşkin Çelik",publishedDate:"July 25th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/6380.jpg",numberOfDownloads:22493,numberOfWosCitations:40,numberOfCrossrefCitations:29,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:58,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:127,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"June 14th 2017",dateEndSecondStepPublish:"July 5th 2017",dateEndThirdStepPublish:"October 1st 2017",dateEndFourthStepPublish:"December 30th 2017",dateEndFifthStepPublish:"February 28th 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"74041",title:"Dr.",name:"Tulay",middleName:null,surname:"Askin Celik",slug:"tulay-askin-celik",fullName:"Tulay Askin Celik",profilePictureURL:"https://mts.intechopen.com/storage/users/74041/images/system/74041.png",biography:"Dr. Tülay AŞKIN ÇELİK gained her PhD from Fırat University, Art and Science Faculty, Department of Biology, Elazığ/TURKEY. Presently she is an Associate Professor at Aydın Adnan Menderes University, Art and Science Faculty, Department of Biology, Aydın/TURKEY in the field of genetics. She has been a referee for more than 25 international scientific journals and she worked as a researcher and project manager in 13 projects. She is a referent for issues related to the fields of genetic toxicology and anticancer and antioxidant plants. In 2008, she became a member of the European Association for Cancer Research (EACR) and Molecular Cancer Research Association (MOKAD) and in 2018, she became a member of the Medical Biology and Genetics Association (TBGDER). Currently, her scientific interests include bioactive phytochemicals and plant extracts on their cytogenetic and gentotoxic effects on chromosomes and cancer cells and in vivo /in vitro biological activities. Furthermore, she is also investigating the genotoxic and cytotoxic effects of environmental pollutants such as pesticides. She has authored one book and two book chapters in reputed books published by IntechOpen Access Publisher.",institutionString:"Aydın Adnan Menderes University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Adnan Menderes University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1208",title:"Medical Toxicology",slug:"medical-toxicology"}],chapters:[{id:"61438",title:"Introductory Chapter: Cytotoxicity",doi:"10.5772/intechopen.77244",slug:"introductory-chapter-cytotoxicity",totalDownloads:1346,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Tülay Aşkin Çelik",downloadPdfUrl:"/chapter/pdf-download/61438",previewPdfUrl:"/chapter/pdf-preview/61438",authors:[{id:"74041",title:"Dr.",name:"Tulay",surname:"Askin Celik",slug:"tulay-askin-celik",fullName:"Tulay Askin Celik"}],corrections:null},{id:"57702",title:"Cytotoxicity Caused by Asbestos Fibers and Acquisition of Resistance by Continuous Exposure in Human T Cells",doi:"10.5772/intechopen.72064",slug:"cytotoxicity-caused-by-asbestos-fibers-and-acquisition-of-resistance-by-continuous-exposure-in-human",totalDownloads:983,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The cytotoxic effects of asbestos fibers on human T cells and the acquisition of resistance against asbestos-induced apoptosis have been studied. These analyses are based on the establishment of a continuous and relatively low-dose exposure model of human immune cells exposed to asbestos that resembles actual exposure in the human body. The MT-2 T cell line was selected as the candidate for the investigations. A transient and high-dose exposure to chrysotile resulted in apoptosis with production of reactive oxygen species (ROS) and activation of the mitochondrial apoptotic pathway. However, sublines continuously exposed to low dose of asbestos exhibited resistance to asbestos-induced apoptosis. The mechanism of resistance acquisition involved excess production of IL-10, activation of STAT3, and enhanced expression of Bcl-2 located downstream of STAT3. These changes were also found in a subline continuously exposed to crocidolite. Furthermore, sublines showed a marked decrease in the expression of forkhead box O1 (FoxO1) transcription factor. FoxO1 is known to regulate apoptosis and various other cellular processes. Regarding apoptosis, sublines continuously exposed to asbestos showed reduction of FoxP1-driven proapoptotic genes. This pathway is also considered one of the mechanisms that result in resistance to asbestos-induced apoptosis in sublines. These sublines also exhibited several characteristics suggesting reduction of antitumor immunity.",signatures:"Hidenori Matsuzaki, Suni Lee, Naoko Kumagai-Takei, Yu Min,\nNagisa Sada, Kei Yoshitome, Yasumitsu Nishimura, Megumi Maeda\nand Takemi Otsuki",downloadPdfUrl:"/chapter/pdf-download/57702",previewPdfUrl:"/chapter/pdf-preview/57702",authors:[{id:"34101",title:"Prof.",name:"Takemi",surname:"Otsuki",slug:"takemi-otsuki",fullName:"Takemi Otsuki"},{id:"48627",title:"Dr.",name:"Naoko",surname:"Kumagai-Takei",slug:"naoko-kumagai-takei",fullName:"Naoko Kumagai-Takei"},{id:"48631",title:"Dr.",name:"Yasumitsu",surname:"Nishimura",slug:"yasumitsu-nishimura",fullName:"Yasumitsu Nishimura"},{id:"104893",title:"Dr.",name:"Suni",surname:"Lee",slug:"suni-lee",fullName:"Suni Lee"},{id:"104894",title:"Dr.",name:"Hidenori",surname:"Matsuzaki",slug:"hidenori-matsuzaki",fullName:"Hidenori Matsuzaki"},{id:"219725",title:"Dr.",name:"Kei",surname:"Yoshitome",slug:"kei-yoshitome",fullName:"Kei Yoshitome"},{id:"222581",title:"MSc.",name:"Yu",surname:"Min",slug:"yu-min",fullName:"Yu Min"},{id:"222582",title:"Dr.",name:"Nagisa",surname:"Sada",slug:"nagisa-sada",fullName:"Nagisa Sada"},{id:"222583",title:"Prof.",name:"Megumi",surname:"Maeda",slug:"megumi-maeda",fullName:"Megumi Maeda"}],corrections:null},{id:"58055",title:"The Cytotoxic, Antimicrobial and Anticancer Properties of the Antimicrobial Peptide Nisin Z Alone and in Combination with Conventional Treatments",doi:"10.5772/intechopen.71927",slug:"the-cytotoxic-antimicrobial-and-anticancer-properties-of-the-antimicrobial-peptide-nisin-z-alone-and",totalDownloads:7259,totalCrossrefCites:7,totalDimensionsCites:11,hasAltmetrics:0,abstract:"Nisin is an antimicrobial peptide commonly used as a food preservative since 1969. This peptide has potent antimicrobial activity against several Gram-positive bacterial strains, including clinically important and resistant pathogens. The combination of nisin with conventional antibiotics has been shown to improve the antimicrobial activity of these antibiotic agents. Apart from the antimicrobial properties of nisin, this AMP also displays promising anticancer potential towards several types of malignancies. The nisin Z variant is able to induce selective cytotoxicity in melanoma cells compared to non-malignant cells. It was shown that nisin Z disrupts the cell membrane integrity of melanoma cells and that cytotoxicity is likely due to the activation of an apoptotic pathway. In addition, when used in combination with the conventional chemotherapeutic agents, nisin Z has the potential to enhance the cytotoxicity of these chemotherapeutic agents against cultured melanoma cells. Nisin Z has great potential for clinical application considering its low cytotoxicity to non-malignant cells and its effectiveness against Gram-positive bacterial strains and certain cancers.",signatures:"Angélique Lewies, Lissinda H. Du Plessis and Johannes F. Wentzel",downloadPdfUrl:"/chapter/pdf-download/58055",previewPdfUrl:"/chapter/pdf-preview/58055",authors:[{id:"214707",title:"Dr.",name:"Johannes",surname:"Wentzel",slug:"johannes-wentzel",fullName:"Johannes Wentzel"},{id:"216091",title:"Dr.",name:"Angélique",surname:"Lewies",slug:"angelique-lewies",fullName:"Angélique Lewies"},{id:"216092",title:"Prof.",name:"Lissinda",surname:"Du Plessis",slug:"lissinda-du-plessis",fullName:"Lissinda Du Plessis"}],corrections:null},{id:"58788",title:"Cytotoxic Colchicine Alkaloids: From Plants to Drugs",doi:"10.5772/intechopen.72622",slug:"cytotoxic-colchicine-alkaloids-from-plants-to-drugs",totalDownloads:1412,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Plants produce and store many organic compounds like amino acids, proteins, carbohydrates, fats, and alkaloids, which are usually treated as secondary metabolites. Many alkaloids are biologically active for humans. For thousand years, extracts from plants containing alkaloids had medicinal use as drugs and they owe their powerful effects thanks to presence of alkaloids. Alkaloids have anti-inflammatory, antibacterial, analgesic, local anesthetic, hypnotic, psychotropic, antimitotic, and antitumor activity. Nowadays, alkaloids from plants are still of great interest to organic chemists, pharmacologists, biologists, biochemists, and pharmacists. Plants of Liliaceae family contain colchicine as the main alkaloid, which has cytotoxic activity. Colchicine has limited pharmacological application because of its toxicity, but many derivatives have been synthesized and their cytotoxic activity and tubulin-binding properties have been tested. Many of the synthetic derivatives showed good cytotoxic activity.",signatures:"Joanna Kurek",downloadPdfUrl:"/chapter/pdf-download/58788",previewPdfUrl:"/chapter/pdf-preview/58788",authors:[{id:"214632",title:"Dr.",name:"Joanna",surname:"Kurek",slug:"joanna-kurek",fullName:"Joanna Kurek"}],corrections:null},{id:"58539",title:"Natural Products as Cytotoxic Agents in Chemotherapy against Cancer",doi:"10.5772/intechopen.72744",slug:"natural-products-as-cytotoxic-agents-in-chemotherapy-against-cancer",totalDownloads:1485,totalCrossrefCites:5,totalDimensionsCites:7,hasAltmetrics:0,abstract:"Nature continues to produce a great wealth of natural molecules endowed with cytotoxic activity toward a large panel of tumor cells. Some of these molecules are used in chemotherapy, and others have shown great anti-tumor and anti-metastatic potential in preclinical trials. This review discusses some examples of these molecules that have been studied in our laboratory and others. We report a differential cytotoxic activity of some monoterpenes (carvacrol, tymol, carveol, carvone, and isopulegol) against a panel of tumor cell lines. The carvacrol was the most cytotoxic molecule both in vitro and in vivo as demonstrated by preclinical studies using the DBA2/P815 mice model. On the other hand, polyphenols were also studied with respect to their cytotoxic effects. Interestingly, these compounds showed a prominent cytotoxic activity toward a panel of cancer cells with differential molecular mechanisms. In addition, we report a very strong antitumor efficacy of artemisinin, a sesquiterpen lactone from Artemisia annua, together with an antimetastatic potential as demonstrated by preclinical experiments. Furthermore, some of the molecular mechanisms involved in these effects are described.",signatures:"Abdelmajid Zyad, Inass Leouifoudi, Mounir Tilaoui, Hassan Ait\nMouse, Mouna Khouchani and Abdeslam Jaafari",downloadPdfUrl:"/chapter/pdf-download/58539",previewPdfUrl:"/chapter/pdf-preview/58539",authors:[{id:"187827",title:"Dr.",name:"Inass",surname:"Leouifoudi",slug:"inass-leouifoudi",fullName:"Inass Leouifoudi"},{id:"204146",title:"Prof.",name:"Abdelmajid",surname:"Zyad",slug:"abdelmajid-zyad",fullName:"Abdelmajid Zyad"},{id:"216446",title:"Prof.",name:"Hassan",surname:"Ait Mouse",slug:"hassan-ait-mouse",fullName:"Hassan Ait Mouse"},{id:"216447",title:"Prof.",name:"Mouna",surname:"Khouchani",slug:"mouna-khouchani",fullName:"Mouna Khouchani"}],corrections:null},{id:"58323",title:"Cytotoxicity and Apoptosis Induction by Coumarins in CLL",doi:"10.5772/intechopen.72446",slug:"cytotoxicity-and-apoptosis-induction-by-coumarins-in-cll",totalDownloads:1158,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Chronic lymphocytic leukemia (CLL) is one of the leukemia types. Leukemia is cancer of the body's blood-forming cells. Cancer is a disease that is often characterized by too little apoptosis and uncontrolled duplicate of body cells. Apoptosis, or programmed cell death, is a normal component of the development and health of multicellular organisms. Cells die in response to a variety of stimuli during apoptosis. During cancer, pathophysiology apoptosis of the cancerous cells is disrupted, so one of the strategies for cancer chemotherapy is inducing apoptosis in cancerous cells. Myeloid cell leukemia type 1 (Mcl-1) is one of the antiapoptotic Bcl-2 family proteins. It has been shown that the expression of Mcl-1 in CLL is significantly associated with a failure to achieve complete remission following cytotoxic therapy, so regulation of Mcl-1 expression by coumarins could be one of the mechanisms of CLL chemotherapy. Coumarins consist of a large class of phenolic substances found in plants. Different pharmacologic effects of coumarins were reported. One of these effects is cytotoxicity and apoptosis induction in cancerous cells by coumarins. In this chapter, the cytotoxic activity of coumarins and their role in Mcl-1 regulation are discussed.",signatures:"Omid Gholami",downloadPdfUrl:"/chapter/pdf-download/58323",previewPdfUrl:"/chapter/pdf-preview/58323",authors:[{id:"214865",title:"Dr.",name:"Omid",surname:"Gholami",slug:"omid-gholami",fullName:"Omid Gholami"}],corrections:null},{id:"58914",title:"Cyto(Geno)Toxic Endpoints Assessed via Cell Cycle Bioassays in Plant Models",doi:"10.5772/intechopen.72997",slug:"cyto-geno-toxic-endpoints-assessed-via-cell-cycle-bioassays-in-plant-models",totalDownloads:1022,totalCrossrefCites:2,totalDimensionsCites:5,hasAltmetrics:0,abstract:"Environmental pollution is a matter of great concern. Therefore, researches that aim to access the risk of toxicity of these potential pollutants are welcome in the scientific community. The most common strategy to detect toxic agents is through chemical analysis. However, in the last years, the biological assays are often important for risk assessments. Among the bioassays using living organisms to detect toxicity of a compound, plant models have been highlighted as it is easy to be conducted, has low cost, high sensitivity and presents good correlation with other test systems, including mammals. Besides, it is in accordance with the Toxicology Guidelines for the twenty-first century, which claims for bioassays that could substitute the ones that use animals as models. At cellular level, the cytotoxicity, genotoxicity, and mutagenicity are the parameters determined by the endpoints as mitotic index, DNA fragmentation, induction of cell death, and malfunction of cellular structures leading to chromosome and cell cycle alterations. Each of these endpoints will be presented in details in this chapter.",signatures:"Larissa Fonseca Andrade Vieira and Graciele Lurdes Silveira",downloadPdfUrl:"/chapter/pdf-download/58914",previewPdfUrl:"/chapter/pdf-preview/58914",authors:[{id:"215258",title:"Prof.",name:"Larissa",surname:"Fonseca Andrade Vieira",slug:"larissa-fonseca-andrade-vieira",fullName:"Larissa Fonseca Andrade Vieira"},{id:"215260",title:"M.Sc.",name:"Graciele",surname:"Silveira",slug:"graciele-silveira",fullName:"Graciele Silveira"}],corrections:null},{id:"58235",title:"Role of Cytotoxicity Experiments in Pharmaceutical Development",doi:"10.5772/intechopen.72539",slug:"role-of-cytotoxicity-experiments-in-pharmaceutical-development",totalDownloads:1806,totalCrossrefCites:4,totalDimensionsCites:14,hasAltmetrics:0,abstract:"Through the twentieth century, the road from synthetizing a new drug molecule to become an actual product got longer than ever before. Cytotoxicity assays are a quick way to assess a certain chemical compound’s effects on a given human cell line. The most well-known techniques are the MTT- and the LDH-assays. These tests are cheap, easy to execute, but not very precise and dependent on various environmental factors and also, they show no detail about the time-dependency of the toxic effect. Cytotoxicity experiments are a crucial part of a modern pharmaceutical development process. They are a cheap and safe way to get vital information about a new molecule’s biological attributes focusing on its basic tolerability. These studies not only save human lives and test animals, but they save the time and resources to be spared on a test molecule which is a complete failure having no in vitro safety.",signatures:"Ildikó Bácskay, Dániel Nemes, Ferenc Fenyvesi, Judit Váradi, Gábor\nVasvári, Pálma Fehér, Miklós Vecsernyés and Zoltán Ujhelyi",downloadPdfUrl:"/chapter/pdf-download/58235",previewPdfUrl:"/chapter/pdf-preview/58235",authors:[{id:"215449",title:"Dr.",name:"Ildikó",surname:"Bácskay",slug:"ildiko-bacskay",fullName:"Ildikó Bácskay"},{id:"215453",title:"Dr.",name:"Dániel",surname:"Nemes",slug:"daniel-nemes",fullName:"Dániel Nemes"},{id:"215454",title:"Dr.",name:"Zoltán",surname:"Ujhelyi",slug:"zoltan-ujhelyi",fullName:"Zoltán Ujhelyi"},{id:"215456",title:"Dr.",name:"Ferenc",surname:"Fenyvesi",slug:"ferenc-fenyvesi",fullName:"Ferenc Fenyvesi"},{id:"215457",title:"Dr.",name:"Judit",surname:"Váradi",slug:"judit-varadi",fullName:"Judit Váradi"},{id:"215458",title:"Dr.",name:"Gábor",surname:"Vasvári",slug:"gabor-vasvari",fullName:"Gábor Vasvári"},{id:"215459",title:"Dr.",name:"Pálma",surname:"Fehér",slug:"palma-feher",fullName:"Pálma Fehér"},{id:"215460",title:"Dr.",name:"Miklós",surname:"Vecsernyés",slug:"miklos-vecsernyes",fullName:"Miklós Vecsernyés"}],corrections:null},{id:"61672",title:"Biocompatibility of Doped Semiconductors Nanocrystals and Nanocomposites",doi:"10.5772/intechopen.77197",slug:"biocompatibility-of-doped-semiconductors-nanocrystals-and-nanocomposites",totalDownloads:1077,totalCrossrefCites:6,totalDimensionsCites:9,hasAltmetrics:0,abstract:"Exposure of humans and environment to nanocrystals are inevitable, and nanotoxicological analyses are a requirement. The wide variety of nanocrystals with different applications is increasing, and characterization of their effects after exposure includes their potential toxicity and uses. This review summarizes the characterization of doped nanocrystals and nanocomposites, Ca-doped ZnO, Ag- and Eu-doped ZnO and Ni-doped ZnO NCs, their biocompatibility and applications. This review uncovers how these nanocrystals present desirable biocompatible properties, which can be useful as antitumoral and antimicrobial inducing agents, which differ markedly from toxic properties observed in other general nanocrystals.",signatures:"Anielle Christine Almeida Silva, Mariana Alves Pereira Zóia, Lucas Ian Veloso Correia,\nFernanda Van Petten Vasconcelos Azevedo, Aline Teodoro de\nPaula, Larissa Prado Maia, Layara Santana de Carvalho, Loyna\nNobile Carvalho, Maria Paula Camargo Costa, Layssa Carrilho\nGiaretta, Renata Santos Rodrigues, Veridiana de Melo Ávila, Luiz\nRicardo Goulart and Noelio Oliveira Dantas",downloadPdfUrl:"/chapter/pdf-download/61672",previewPdfUrl:"/chapter/pdf-preview/61672",authors:[{id:"13001",title:"Dr.",name:"Noelio",surname:"Oliveira Dantas",slug:"noelio-oliveira-dantas",fullName:"Noelio Oliveira Dantas"},{id:"217672",title:"Prof.",name:"Anielle",surname:"Silva",slug:"anielle-silva",fullName:"Anielle Silva"},{id:"227086",title:"MSc.",name:"Fernanda",surname:"Van Petten Vasconcelos Azevedo",slug:"fernanda-van-petten-vasconcelos-azevedo",fullName:"Fernanda Van Petten Vasconcelos Azevedo"},{id:"227087",title:"MSc.",name:"Mariana",surname:"Alves Pereira Zóia",slug:"mariana-alves-pereira-zoia",fullName:"Mariana Alves Pereira Zóia"},{id:"227089",title:"BSc.",name:"Lucas Ian",surname:"Veloso Correia",slug:"lucas-ian-veloso-correia",fullName:"Lucas Ian Veloso Correia"},{id:"227090",title:"Dr.",name:"Aline",surname:"Teodoro De Paula",slug:"aline-teodoro-de-paula",fullName:"Aline Teodoro De Paula"},{id:"227099",title:"Prof.",name:"Renata",surname:"Santos Rodrigues",slug:"renata-santos-rodrigues",fullName:"Renata Santos Rodrigues"},{id:"227100",title:"Prof.",name:"Veridiana",surname:"De Melo Ávila",slug:"veridiana-de-melo-avila",fullName:"Veridiana De Melo Ávila"},{id:"227101",title:"Prof.",name:"Luiz Ricardo",surname:"Goulart",slug:"luiz-ricardo-goulart",fullName:"Luiz Ricardo Goulart"},{id:"227368",title:"Ms.",name:"Maria Paula",surname:"Camargo Costa",slug:"maria-paula-camargo-costa",fullName:"Maria Paula Camargo Costa"},{id:"227369",title:"Ms.",name:"Layssa",surname:"Carrilho Giaretta",slug:"layssa-carrilho-giaretta",fullName:"Layssa Carrilho Giaretta"}],corrections:null},{id:"57853",title:"Toxicity of Titanate Nanosheets on Human Immune Cells",doi:"10.5772/intechopen.72234",slug:"toxicity-of-titanate-nanosheets-on-human-immune-cells",totalDownloads:936,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Titanium oxide is regarded as a bio-inert material, but studies concerning the toxic effects of titanium dioxide (TiO2), particularly nano-scaled TiO2 particles, have been accumulating that indicate nano-scaled TiO2 particles show more harm and cause greater alteration of immune functions compared with large particles. Inorganic nanosheets have been the focus of increasing interest because of their ultrathin structure, as well as diversity of compounds and structures leading to various functions. Oxide nanosheets are included in the group comprising inorganic nanosheets, and titanate nanosheets (TiNSs) represent a form of oxide nanosheets. We therefore examined the toxicity of nano-scaled 2D materials of TiNSs on human immune cells. Our study revealed that TiNSs have the potential to cause harm through caspase-dependent apoptosis of human peripheral blood mononuclear cells (PBMCs) to the same degree as asbestos. Furthermore, isolated monocytes developed marked vacuoles prior to cell death upon exposure to TiNSs, which were found in the vacuoles and indicated engulfment of TiNSs. A consideration of these findings with the co-localization of vacuoles with endocytosed fluorescence-labeled dextran indicates that TiNSs entered the endosomal pathway, leading to the formation of vacuoles in monocytes and subsequent cell death. TiNSs might therefore affect immune functions through interference of endo-lysosomal functions.",signatures:"Yasumitsu Nishimura, Daisuke Yoshioka, Naoko Kumagai-Takei,\nSuni Lee, Hidenori Matsuzaki, Kei Yoshitome and Takemi Otsuki",downloadPdfUrl:"/chapter/pdf-download/57853",previewPdfUrl:"/chapter/pdf-preview/57853",authors:[{id:"48631",title:"Dr.",name:"Yasumitsu",surname:"Nishimura",slug:"yasumitsu-nishimura",fullName:"Yasumitsu Nishimura"}],corrections:null},{id:"58365",title:"General Cytotoxicity and Its Application in Nanomaterial Analysis",doi:"10.5772/intechopen.72578",slug:"general-cytotoxicity-and-its-application-in-nanomaterial-analysis",totalDownloads:1560,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:0,abstract:"The recent increasing interest in the use of different nanoparticles in biological and medical applications encouraged scientists to analyse their potential impact on biological systems. The biocompatibility analyses of novel materials for medical applications are conducted using quantitative and qualitative techniques collected by the International Standards Organization (ISO). The well-known assays, such as tetrazolium-based assays used for mitochondrial function monitoring, LDH for membrane permeability determination and neutral red uptake (NRU) describing lysosome function, need to be optimised due to specific properties of wide range of nanomaterials. Physicochemical properties of nanoparticles (NPs) such as size, composition, concentration, shape and surface (e.g., charge, coating, aspect ratio), as well as the cell type play a crucial role in determining the nanomaterial toxicity (also uptake pathway(s) of NPs). Different nanomaterials exhibit different cytotoxicity from relatively non-toxic hexagonal boron nitride to rutile TiO2 NPs that induce oxidative DNA damage in the absence of UV light. Finally, the results of the nanomedical analysis can be enriched by holographic microscopy that gives valuable information about the doubling time (DT), cell segmentation, track cell movement and changes in cell morphology. The results can be also completed by phenotype microarrays (PMs) and atomic force microscopy (AFM) techniques that fulfil experimental data.",signatures:"Magdalena Jedrzejczak-Silicka and Ewa Mijowska",downloadPdfUrl:"/chapter/pdf-download/58365",previewPdfUrl:"/chapter/pdf-preview/58365",authors:[{id:"186478",title:"Dr.",name:"Magdalena",surname:"Jedrzejczak-Silicka",slug:"magdalena-jedrzejczak-silicka",fullName:"Magdalena Jedrzejczak-Silicka"},{id:"231014",title:"Prof.",name:"Ewa",surname:"Mijowska",slug:"ewa-mijowska",fullName:"Ewa Mijowska"}],corrections:null},{id:"61587",title:"Review of In vitro Toxicity of Nanoparticles and Nanorods: Part 1",doi:"10.5772/intechopen.76365",slug:"review-of-in-vitro-toxicity-of-nanoparticles-and-nanorods-part-1",totalDownloads:1101,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The specific use of engineered nanostructures in biomedical applications has become very attractive, due to their ability to interface and target specific cells and tissues to execute their functions. Additionally, there is continuous progress in research on new nanostructures with unique optical, magnetic, catalytic, and electrochemical properties that can be exploited for therapeutic or diagnostic methods. On the other hand, as nanostructures become widely used in many different applications, the unspecific exposure of humans to them is also unavoidable. Therefore, studying and understanding the toxicity of such materials is of increasing importance. Previously published reviews regarding the toxicological effects of nanostructures focuses mostly on the cytotoxicity of nanoparticles and their internalization, activated signaling pathways, and cellular response. Here, the most recent studies on the in vitro cytotoxicity of NPs, nanowires, and nanorods for biomedical applications are reviewed and divided into two parts. The first part considers nonmagnetic metallic and magnetic nanostructures. While part 2 covers carbon structures and semiconductors. 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Additionally, there is continuous progress in research on new nanostructures with unique optical, magnetic, catalytic and electrochemical properties that can be exploited for therapeutic or diagnostic methods. On the other hand, as nanostructures become widely used in many different applications, the unspecific exposure of humans to them is also unavoidable. Therefore, studying and understanding the toxicity of such materials are of increasing importance. Previously published reviews regarding the toxicological effects of nanostructures focus mostly on the cytotoxicity of nanoparticles and their internalization, activated signaling pathways and cellular response. Here, the most recent studies on the in-vitro cytotoxicity of NPs, nanowires and nanorods for biomedical applications are reviewed and divided into two parts. The first part considers nonmagnetic metallic and magnetic nanostructures, while, the second part covers carbon structures and semiconductors. 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1. Introduction
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Microscopic findings involving lymphocytic infiltration surrounding the excretory ducts in combination with the destruction of acinar tissue are representative for both minor and major salivary glands and are pathognomonic changes for SS. Parotid, lip, or sublingual salivary gland biopsy is performed in the diagnosis and monitoring of SS, but currently only labial salivary gland biopsy (LSGB) is included into classification criteria of SS. LSGB is used for the diagnosis of Sjögren’s syndrome (SS). The current classification criteria of SS, approved by the American College of Rheumatology (ACR) and the European League against Rheumatism (EULAR) in 2016, include LSGB as a part of weighted sum of five items [1]. The presence of focal lymphocytic sialadenitis (FLS) with a focus score of 1 foci/4 mm2 glandular tissue is a positive score of LSGB. Lip salivary glands are widely distributed in the labial mucosa of the oral cavity. They are largely used for assisting the diagnosis of SS, because they are easily accessible and lie above the muscle layer. They are separated from the oral mucous membrane by a thin layer of fibrous connective tissue. Orientation and identification of glandular tissue is the easiest. The risk of excessive postoperative bleeding is decreased because the arterial supply to the lip lies deep. These anatomical implications and pathognomic changes predispose of labial salivary glands to the biopsy [1, 2, 3, 4, 5, 6, 7].
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2. Surgical technique and possible complications of LSGB
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Labial salivary gland biopsy is considered a minor surgical procedure and can be performed on the ambulatory basis. There is no standardized technique that yields adequate tissue for analysis and minimizes adverse effects. The lack of uniformity in methodology and potential adverse effects of LSGB hinders its application. LSGB is treated as a safe and simple surgical procedure without severe postoperative complications. One of the most severe complications of LSGB is sensitive nerve injury. This localized sensory alternation can be described as an anesthesia, a reduced or partial loss of sensation, a transitory numbness, or a hypoesthesia. These sensations can last for a few months or can be permanent. Persistent lip numbness occurs in up to 6% of biopsies performed in the lower lip [8]. The branches of the mental nerve in the lower lip are closely associated with the salivary glands, and this anatomical relationship increases the risk of postoperative sensory sensations. Additionally, the branch of the mental nerve usually divides into two sub-branches: a horizontal and a vertical, which have an ascending course toward the vermillion border and are in close relation to the labial salivary glands. Incisional biopsies shorter than 2 cm performed with a scalpel have reported complications ranging from 0 to 9.3%, whereas those using larger incisions (2–3 cm) have described complications in the range of 3.7–31%. Transient disorders of lip sensitivity are found to occur in up to 11.7% of procedures. Persistent lower lip hypoesthesia is reported in about 3.4–4% of cases. Larger incisional biopsies and punch biopsies are associated with a higher risk of both transient and persistent lower lip numbness. Other possible complications of LSGB are less severe, usually transient or temporary, and are associated with localized postoperative inflammation or improper healing. The symptoms of postoperative inflammations are local pain and swelling. Blood vessel injuries result in hematoma. The possible delayed complications are the formation of granulomas, internal scarring, and cheloid formation. Labial salivary gland injuries can result in mucous extravasation cysts. Some patients can report burning or tingling sensations, and functional deficits during the immediate postbiopsy period such as eating, sleeping, or speech difficulties [9, 10, 11, 12].
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Labial glands biopsy may be an excisional or incisional technique. The most recommended site is normal-appearing mucosa of the lower lip. Usually, it is a scalpel biopsy. A wide range of surgical approaches have been described for harvesting a few accessory glands from the lower lip using different instruments such as a scalpel, a punch, or cup forceps. The use of a forceps with a fenestrated active end to stabilize the lip has also been suggested. The excisional biopsy is carried out by excising an ellipse of oral mucous membrane down to the muscle layer. Ideally, 6–8 minor glands must be harvested and sent for histopathologic examination. The wound should be closed with 4-0 silk sutures, which are removed after 4–5 days. The modification of this method is the technique with a mucosal excision of 3.0 × 0.75 cm. Another recommended technique is a 1.0–1.5-cm-wedge-shaped excision of the mucosa between the midline and commissure. The incisional biopsy is described as a 1.5–2.0-cm linear incision of mucosa, parallel to the vermillion border and lateral to the midline. Gorson and Ropper reported a 1-cm vertical incision just behind the wet line through the mucosa and submucosa [31]. It is usually that case that the lateral lip compartments are advocated for biopsy, because of the glandular-free zone in the center of the lower lip. Berquin et al. described an oblique incision, starting 1.5 cm from the midline and proceeding latero-inferiorly to avoid the central glandular-free zone. The vertical incision technique is associated with less pain, less swelling, less scar formation, and less difficulty in eating when compared with the horizontal incision technique. There is insufficient evidence to support the superiority of one technique over the others, and the shape and the size of the incision can be considered a matter of preference. The incision shape includes elliptical, circular, linear, horizontal, vertical, and wedge shapes, and the incision length varies from a few millimeters to 2 cm.
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Another recommended modification is using loupe operation glasses to precisely excise the salivary glands without disturbing the direct underlying sensible nerves. The alternative technique to scalpel biopsy is the minor salivary gland punch biopsy. This biopsy can be performed by a single operator, and it is less expensive than classical scalpel biopsy. This technique consists of obtaining the biopsy from the buccal side of the lower lip, which is stabilized by the patient him/herself using a 4–5 mm punch, which permits the retrieval of a cylinder of tissue up to 8 mm in length. The punch biopsy is suggested because of the absence of risk to the patient and because of its simplicity. However, the punch biopsies do not provide enough material for the diagnosis of Sjögren’s syndrome. Moreover, the findings of this study strongly discouraged the punch technique for minor salivary gland lip biopsy and provided information on the superiority of the linear incisional biopsy in terms of neural damage [12, 13, 14, 15, 16].
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Based on our own clinical experience, a 1.0–1.5-cm linear, horizontal incision of mucosa parallel to the vermillion border and lateral to the midline with the tip of a 15 scalpel is worth to recommend. The lower lip should be retracted and everted under tension to expose the inner surface and allow visualization of the minor salivary glands just to the depth of the mucosa. Local anesthesia injected submucosally with 0.5–1.0 ml of 1% lidocaine with 1:200,000 epinephrine is sufficient. The anesthesia hydrodissects and lifts the mucosa away from the salivary glands, provides delivery of local anesthetic directly to sensory nerve fibers, and temporarily displaces small vessels deep in the glands to promote hemostasis and visualization during the dissection. In this technique, both margins of incision should be gently crafted to access the submucosal layer. This stage of procedure can be performed using blunt-tipped iris scissors or a scalpel by spreading in a plane perpendicular to the mucosal incision and parallel to the direction of the sensory nerve fibers. This technique is fast, simple, and leaves a small scar. The linear incision secures a good adherence of wound margins and proper and fast healing. Unfortunately, this method is not effective in small amounts of salivary glands. Sometimes, it is difficult to find the sufficient amount of labial glands. Moreover, it may be difficult to harvest a sufficient number of labial salivary glands in atrophic mucosa of patients with long-standing SS. In these cases, the recommended method is a 1-cm lenticular incision of mucosa, lateral to the midline, and removal of the mucosa to uncover the submucosal layer and obtain a few adjacent salivary glands. This technique ensures good visibility into the operating field to avoid blood vessels and nerve injures. This incision provides adequate glandular tissue for diagnosis. The wound should be closed by a few nonresorbable, single, interrupted stitches. One very important issue is to harvest only labial salivary glands without muscular or other tissues. It is the most valuable specimen for histopathological examination, because it only includes glandular tissue. Additionally, this technique decreases the risk of nerve damage and postoperative pain and assures successful healing. Sensory nerve fibers are almost always visible just below the plane of dissection, and care should be taken to identify and preserve them. The next very important issue is not to puncture the labial glands to reduce the risk of mucous extravasation cyst formation. It is even better to remove all visible labial salivary glands from the operating field before suturing in order not to damage the glands or their ducts. Patients should also avoid taking steroids before the biopsy. The factors potentially contributing to a false-negative rate include the use of oral steroids that may result in immunosuppression and confound histopathologic results. The tissue specimens should be immediately placed in a wide-mouthed container, coded, and fixed in a generous amount of 10% formalin buffered saline for 24 h (Figures 1 and 2).
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Figure 1.
Linear incision and scalpel biopsy of labial salivary gland biopsy. A few labial salivary glands exposed and visible in the operating field.
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Figure 2.
Labial salivary gland specimen.
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3. Histologic criteria for diagnosis of SS on labial salivary gland biopsies
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Labial salivary gland biopsy is an objective test of SS and plays a significant role in the diagnostic process. In fact, the presence of either anti-SSA/SSB seropositivity or a positive lip biopsy is a requirement for an individual to be classified as having SS. The microscopic confirmation of SS is based on the presence of focal lymphocytic sialadenitis (FLS) with a focus score ≥ 1 per 4 mm2 of glandular tissue. According to the revised American-European Consensus Group’s (AECG) classification criteria and the ACR classification criteria for SS, an LSGB is considered positive if minor salivary glands demonstrate FLS, with a focus score of 1 or more, as evaluated by an expert histopathologist. A lymphocytic focus is defined as a dense aggregate of 50 or more lymphocytes adjacent to normal-appearing mucous acini in salivary gland lobules that lacked ductal dilatation. Focal lymphocytic sialadenitis is applied to specimens that show the presence of 1 or more foci of lymphocytes located in periductal and perivascular locations. The foci can contain plasma cells, but these must be a minority constituent of the inflammatory infiltrate. The focus score can be calculated for those specimens showing the histopathologic appearance of FLS. The number of lymphocytic foci is then determined for all the gland lobules in a single tissue section. The focus score is then calculated as the number of foci per square millimeter of glandular tissue multiplied by four, which then yields foci/4mm2. A focus score of 1 equates to 1 focus/4 mm2. To determine the focus, a calibrated eyepiece grid or image analysis software with a closed polygon tool is used. FLS has to be distinguished from nonspecific chronic sialadenitis. The symptoms of nonspecific sialadenitis are mild to moderate acinar atrophy, interstitial fibrosis, and ductal dilatation, with lymphocytes and macrophages often scattered in the parenchyma, but not forming dense aggregates of 50 or more lymphocytes immediately adjacent to normal-appearing acini. In addition to the focus score (FS), two scoring systems for salivary glands are in use for the diagnosis and classification of SS. These systems are based on the presence of foci [7]. Grading according to Tarpley’s system involves destruction of acinar tissue and fibrosis (Table 1). Grading according to the Chisholm and Mason system is based on the presence of infiltrates from slight to one or more foci (Table 2) [16, 17].
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Grade
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Description
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0
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Normal
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1
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1 or 2 Aggregates
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2
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>3 Aggregates
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3
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Diffuse infiltrate with partial destruction of acinar tissue with or without fibrosis
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4
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Diffuse infiltrate with or without fibrosis destroying the lobular architecture completely
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Table 1.
Grading systems for salivary gland biopsies of Tarpley.
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Grade
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Description
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0
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Absent
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1
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Slight infiltrate
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2
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Moderate infiltrate or less than one focus
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3
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One focus
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4
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More than one focus
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Table 2.
Grading systems for salivary gland biopsies of Chisholm and Mason.
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Focus: a cluster of 50 or more lymphocytes and histiocytes.
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Aggregate: approximately 50 cells (lymphocytes, plasma cells, or histiocytes).
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4. Differentiation of focus lymphocytic sialadenitis
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Focus lymphocytic sialadenitis should be differentiated with other microscopic findings:
Nonspecific chronic sialadenitis NSCS
Sclerosing chronic sialadenitis SCS
Granulomatous inflammation
Infiltrates within normal limits
Marginal zone (MALT) lymphoma
Germinal center
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Nonspecific chronic sialadenitis (NSCN) is characterized by scattered or focal infiltrates of lymphocytes, macrophages, and plasma cells that are not adjacent to normal-appearing acini and located in gland lobules that exhibit some combination of acinar atrophy, interstitial fibrosis, duct dilation, and luminal inspissated mucus.
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Sclerosing chronic sialadenitis (SCS) is an advanced stage of NSCS in which interstitial fibrosis, various patterns of chronic inflammation, and acinar atrophy predominate.
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Granulomatous inflammation is present when there are clusters of CD68 positive macrophages, with or without occasional multinucleated giant cells and absent necrosis.
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Infiltrates within normal limits can be diagnosed in minor salivary glands with normal appearing architecture and scattered plasma cells, but without acinar atrophy and few if any lymphocytes.
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Marginal zone (MALT) lymphoma is diagnosed in minor salivary glands exhibiting diffuse lymphocytic infiltration with loss of glandular architecture and composed of sheets of CD20 positive cells without follicular distribution, few scattered CD3 positive cells, and few if any follicular dendritic (CD21 or CD23 positive) cells.
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Germinal center presence is estimated in hematoxylin and eosin (H&E) stained sections by the presence of a cluster of relatively clear staining cells within a lymphocytic focus. More specific identification of germinal centers requires immunohistochemical staining for follicular dendritic cells with anti-CD21 or CD23 [4, 9].
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There is no standardization of labial salivary gland biopsies in SS, but there are several points of importance in LSGB. The first issue refers to a sufficient amount of glandular tissue. A reasonable compromise is four glands, although a minimum sized evaluable surface area (8 mm2) may be achieved with 2–3 glands. The largest possible area to be sampled would give the best results, but a larger operative field increases the surgical risk. On the other hand, some glands may be atrophic or damaged, and the volume of the material obtained through the biopsy should be sufficient to overcome this artifact and achieve a valid result. It is more recommended to evaluate multiple different lobules than to concentrate on a single abnormal lobule, which may not be typical of the entire gland. In routine management, H&E staining is used in order to determine these structures. For clinical trials, additional staining with CD21 as well as CD20 and CD3 is required. CD21 is a marker of follicular dendritic cells. Germinal centers should be reported and pathologists are advised to use caution in order to avoid overestimating germinal centers by relying solely on CD21. Furthermore, the distribution of the inflammatory cells in the gland may be uneven. Considering this uneven distribution, a single tissue section may result in underdiagnosis. While increasing the number of sections has the potential to reduce this problem, the optimal number of sections has yet to be determined. Some research suggests taking labial salivary glands at different depths from the same incision. Focus score can change significantly at different tissue depths within the minor salivary glands. Multiple sections for LSGB increase the diagnostic value and are more representative than a single section [7, 10] (Figure 3).
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Figure 3.
Confirmation of SS in LSGB. Focus score 4 (staining H&E, magnitude 10×).
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5. Limitations of the assessment of focus score
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Differentiation of FLS with nonspecific chronic sialadenitis and sclerosing chronic sialadenitis
Severe acinar atrophy, interstitial fibrosis, and increase in fat cells in biopsy specimens
Age-related features in biopsy specimens (increased fibrosis, acinar atrophy, and adipose tissue
There are also other histopathological features in the labial glands that are associated with SS and therefore might be indicative of this disease. Lymphoepithelial lesions (LELs) are striated ducts, which are infiltrated by lymphocytes with concurrent hyperplasia of the epithelial cells. They are found both in parotid and labial glands, and are more representative of parotid glands than labial glands.
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Severity of the LELs can be classified into three stages: stage 1: a partial LEL (affecting <50% of the epithelium), stage 2: developed LELS (affecting 50–100% of the epithelium), and stage 3: occluded LELs (fully circumferentially affected epithelium without lumen).
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Besides LELs, the salivary gland of SS patients also presents a relative decrease in IgA + plasma cells. Several studies showed that a relative decrease of <70% IgA + plasma cells was more sensitive and more disease specific than the FS. Both features can help assess the salivary gland biopsies for the diagnosis of SS, especially when the FS in the biopsy is <1 [7, 19, 20, 21, 22, 23].
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7. Alternative types of salivary gland biopsies in SS
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The main alternative types of salivary gland biopsies in SS are parotid gland biopsy and sublingual gland biopsy. Parotid gland biopsy allows the clinician to monitor the disease progression and to assess the effect of an intervention treatment in SS. Parotid tissue can be harvested easily, repeated biopsies from the same parotid gland are possible, and the histopathologic results can be compared with other diagnostic results derived from the same gland, such as secretory function, sialographic appearance, and ultrasonography. Furthermore, parotid biopsy is better in the identification of lymphomas. The main possible complications are facial nerve damage, Frey’s syndrome, and development of sialoceles and salivary fistulae. A temporary change in sensation in the skin area of the incision is also a well-documented complication after parotid biopsy. Some patients might also develop preauricular hypothesis, although this is usually temporary. Furthermore, in SS, the salivary gland tissue is replaced by fatty tissue, and the risk of harvesting fatty tissue is thereby increased if done by inexperienced physicians. Parotid biopsy is particularly recommended in pediatric patients in whom SS is suspected and who have a negative minor salivary gland biopsy result. Incisional biopsy of the parotid gland overcomes most of the disadvantages of labial biopsy. When evaluating the parotid and labial biopsy, sensitivity and specificity are comparable, estimated to be 78 and 86%, respectively. Comparative studies suggest that both procedures—sublingual and parotid biopsy—retain a diagnostic potential comparable to that of lip biopsy and may be associated with lower postoperative morbidity. A comparison of sublingual gland biopsy with labial gland biopsy is better than that of labial gland biopsy, whereas the specificity of the latter is greater than that of the former. Sublingual gland biopsy is a relatively safe procedure, although the postoperative complications of sublingual salivary gland biopsy include ligaturing the Wharton duct, resulting from the placement of sutures, bleeding, and swelling in the floor of the mouth. Damage to the lingual nerve related to this biopsy technique has never been reported in the literature. No specialized histopathologic criteria have been established for the diagnosis of SS after a sublingual gland biopsy, and researchers merely used the criteria for labial gland biopsies [24, 25, 26, 27, 28].
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8. Oral involvement and xerostomia
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The rate of dry mouth in SS ranged from 41% at initial diagnosis to 84% 10 years after diagnosis. Hyposalivation or xerostomia measured by sialometry is one of the objective clinical criteria in the diagnosis of SS. According to the current classification criteria of SS, an unstimulated salivary flow rate of 0.1 ml/minute in sialometry gives a score of 1 to the weighted sum of 5 items. Dryness is also a subjective symptom of SS and is associated with many clinical implications. There are two possible sources of hyposalivation. The first possible origin is the presence of mononuclear cell aggregates around the ducts and acini of salivary glands resulting in functional and structural alterations of these glands and impairing their secretory function. In addition to the direct relationship between mononuclear cell infiltrations and secretory function, there are alternative pathways, such as induction of apoptosis of epithelial glands, alterations in aquaporin distribution, or inhibition of neurotransmission by antimuscarinic antibodies, lead to impaired glandular homeostasis. The second proposed hypothesis is the destruction of the duct and acinar cells of the salivary glands, and neural degeneration and/or the inhibition of nerve transmission. Hyposialia or decreased salivation can lead to xerostomia with clinical oral symptoms [29]. Dry mouth is associated with both objective and subjective signs and symptoms. The most common complaints related to dry mouth are presented in Table 3.
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A dryness of the mouth in the morning and at night A frequent need to sip water A lip dryness, exfoliation, fissuring A predisposition to aphthae, ulcers, and mouth sores A burning sensation in the mouth A dysphagia A dysgeusia
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Table 3.
The most common complaints related to dry mouth.
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In SS, the gingiva and mucosa of the oral cavity are not protected by salivary mucins, leading to less lubrication of the tissues. This can cause signs such as oral mucosal inflammation, mucosal sloughing, erythematous mucosa, and traumatic ulcers. Patients may demonstrate depapillation of the tongue in advanced cases. With time, the concentration of lactoferrin, potassium and cystatin C in saliva grows, while the amylase and carbonic anhydrase concentration drops. Decreased secretion of saliva, the loss of its buffer properties, and a lower concentration of saliva proteins such as histatins, mucins, IgA, and proteins rich in proline and statherins increase the risk of opportunistic infections, mainly fungal infections by Candida albicans. The prevalence of Candida albicans is >68% in patients with SS. Oral candidiasis may be asymptomatic or may show as fissured tongue, rhomboid mid-tongue, nonspecific ulcerations, prosthetic stomatopathies, or generalized candidiasis. It most often takes the form of chronic candidiasis, and less often of pseudodiphtheritic candidiasis. Candida infections often present as atrophic or erythematous candidiasis and are associated with a burning mouth, which is described by approximately one-third of patients with SS. In SS patients, C. albicans, C. tropicalis, C. glabrata, and C. parapsilosis are mainly isolated. Apart from oral candidiasis, a number of other changes and symptoms regarding the oral mucosa may occur (Table 4).
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Candidiasis Angular cheilitis Simple cheilitis Exfoliative cheilitis Aphthae Aphthoid lesions Nonspecific ulcerations Paleness of the oral mucosa Staphylococcal infection
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Table 4.
Symptoms of oral mucosa in the Sjögren’s syndrome.
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Angular cheilitis may be accompanied with fungal infection. In simple cheilitis, dominant manifestations are lip exfoliation and cracking, their proneness to bleeding, periodic swelling, and burning. The lesions are mostly limited to lip vermillion, less often labial mucosa or the facial skin around the vermillion is affected. In exfoliative cheilitis, thick brown keratin plaques are also formed. Skin redness over the lip vermillion and swelling are more often observed [29].
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SS patients are predisposed to rampant caries and traumatic oral lesions. Lack of antibacterial salivary proteins results in severe tooth caries, especially on the unexposed tooth spaces. Rampant cervical caries is the most typical manifestation to SS.
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9. Laryngological and otological manifestations of SS
\n
The lymphocytic infiltrations are representative for all salivary glands and have other possible consequences. Although the sicca syndrome prevails, in a clinical presentation, a bilateral parotid swelling induced by progressive lymphocyte infiltration leads both to ductal inflammation and acinar destruction in about 50% of patients. Recurrent swelling and inflammations of the parotid or submandibular glands in SS are well documented. Slow salivary flow, acinar destruction, and lymphocytic infiltrations predispose to inflammation and salivary gland enlargement. This enlargement should be distinguished from lymphomas. The most significant complication of SS is the development of lymphoproliferative malignancy, which occurs in about 5% of SS patients. Malignant lymphoma, particularly mucosa-associated lymphoid tissue (MALT) lymphoma, is relatively a frequent complication of SS with an incidence ranging between 5 and 10% and a median time from SS to lymphoma diagnosis of 7.5 years. Lymphomas accompanying SS can be confirmed by histopathological examination of salivary gland biopsy. The detection of germinal centers (GC) in salivary gland biopsy can be a very sensitive and predictive feature for lymphogenesis. Antigen-driven B cell selection normally takes place in GC within secondary lymphoid organs, but there is conclusive evidence that also ectopic GC in the salivary glands of SS patients allow affinity maturation of GC B cells with somatic Ig gene hypermaturation. Parotid gland biopsy is more recommended for diagnosis of lymphomas than labial salivary glands [7, 18, 19, 20, 21, 22, 23].
\n
Dryness of the mucosa of the upper respiratory tract is a predominant symptom and results in nasal, oropharynx, nasopharynx, laryngopharynx, vocal cord dryness, and dryness of the skin of the external auditory meatus. The main laryngological symptoms accompanying SS include the following:
Dry nose with congestion, crusting, and epistaxis
Dryness, crusting, or atrophy of the nasal mucosa
Soreness and/or dryness of the throat
Viscid secretions on the posterior pharyngeal wall and tenacious mucus over the vocal cords
Dry wax and a “milky” appearance of the tympanic membrane
Dysphagia
Hoarseness
Otalgia
Tinnitus
A chronic dry cough
Dyspnea
Gastrotracheal reflux
Otitis externa
Myringitis
Sensorineural hearing loss
Facial hypaesthesia and trigeminal nerve neuropathy, and multiple cranial neuropathy [30, 31, 32, 33]
\n
Other possible laryngological manifestations of SS are early and progressive hearing loss and symptoms related to neuropathy of the eighth cranial nerve. Approximately, a quarter of patients suffer from high-frequency hearing loss of cochlear origin, as detected by impedance audiometry or auditory brainstem procedures. The immunologic theory of sensorineural hearing loss (SNHL) in SS is based on antibody activity and cytotoxic T-cell-mediated apoptosis in the inner ear. It has been suggested that these autoantibodies induce thrombosis in the labyrinthine vessels, thereby causing damage to the inner ear, resulting in SNHL. The majority of primary SS patients exhibit hearing impairments of cochlear origin, principally at high frequencies. Sensorineural damage may be attributable to vasculitis or neuritis, or may represent an ototoxic effect of the drugs used to treat primary SS. Although there is no evidence of damage to the central auditory pathways in SS, these patients tend to have a higher prevalence of sensorineural hearing impairment compared with the general population. Idiopathic hearing loss may represent the initial manifestation of systemic vasculitis, including SS. The pathomechanisms underlying cranial neuropathy in SS have not yet been explained, except for trigeminal neuropathy due to ganglionopathy. The two possible mechanisms, vascular origin with damage to the vasa nervorum, and an immunologic cause inducing lymphocytic infiltration of the nerve have been suggested in nerve palsies related to SS. Vasculitis in peripheral neuropathy and ganglionopathy in trigeminal or ataxic neuropathies have been reported as the main pathogenic etiology. The rapid and almost complete recovery from nerve palsy after therapy with corticosteroids and azathioprine suggests that lymphocytic infiltrate, rather than a vasculitic process, was the cause of cranial neuropathy in SS [33, 34, 35, 36, 37, 38, 39, 40].
\n
\n\n',keywords:"Sjögren’s syndrome, hearing loss, cranial nerve neuropathy, xerostomia",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/66367.pdf",chapterXML:"https://mts.intechopen.com/source/xml/66367.xml",downloadPdfUrl:"/chapter/pdf-download/66367",previewPdfUrl:"/chapter/pdf-preview/66367",totalDownloads:881,totalViews:0,totalCrossrefCites:1,totalDimensionsCites:1,totalAltmetricsMentions:0,impactScore:1,impactScorePercentile:50,impactScoreQuartile:3,hasAltmetrics:0,dateSubmitted:"January 30th 2019",dateReviewed:"March 6th 2019",datePrePublished:"April 3rd 2019",datePublished:"September 11th 2019",dateFinished:"March 26th 2019",readingETA:"0",abstract:"Sjögren’s syndrome (SS) affects numerous different areas, and many specialists may be involved in the diagnosis and treatment of SS. Otolaryngological and dental manifestations, neurological impairment, and hearing loss may be the initial symptoms of SS. This chapter describes the most common otolaryngological and oral manifestations of SS, its pathomechanism and possible etiology. Dryness accompanying SS is associated with many clinical implications. The rate of dry mouth in SS ranged from 41% at initial diagnosis to 84% 10 years after diagnosis. An unstimulated salivary flow rate of 0.1 ml/min in sialometry gives a score of 1 to the weighted sum of 5 items according to the current EULAR/ACR criteria. The presence of mononuclear cell aggregates around the ducts and acini of salivary glands results in functional and structural alterations at the level of these glands and impairs their secretory function. The most common oral signs and symptoms are dental caries, tooth decay, fungal infections, traumatic oral lesions, dysphagia, dysgeusia, and inflammation of the salivary glands. Saliva in SS is characterized by the increased concentration of lactoferrin, potassium and cystatin C and the decreased concentration of amylase, carbonic anhydrase, mucins, histatines, IgA, statherins, proline-rich proteins, and the loss of salivary buffer properties. The lack of these physiological defense mechanisms increases the risk of opportunistic infections, mainly fungal infections by Candida albicans. Candidiasis accompanies angular cheilitis, simple cheilitis, and exfoliative cheilitis. The salivary glands of SS patients are characterized by chronic inflammation with the presence of lymphocytic infiltrates located around the striated ducts. These periductal foci may lead to the development of organized ectopic lymphoid structures resembling secondary lymphoid organs with segregated T- and B-cell areas, and high endothelial venules. These structures become an active center of immune response. The presence of foci in labial salivary glands is a hallmark of SS, and their histopathologic analysis is an important item in the diagnosis and classification. A biopsy can be taken from either the labial or the parotid salivary gland, but currently according to the diagnostic criteria, only labial salivary gland biopsy (LSGB) is recommended to confirm the diagnosis of SS. The authors present their own experience and recommendations in taking labial salivary gland biopsy, the main surgical approaches, and the main limitations for this diagnostic method and describe the possibilities and principles of histopathological examination in SS. The authors present the main ultrasonic signs of SS major salivary glands and perspectives of the usage of salivary gland ultrasonic examination in the diagnosis and monitoring of SS. The presented chapter also includes the most common laryngological manifestations associated with SS: nose dryness, crusting, or atrophy of the nasal mucosa, dryness of the throat, dysphagia, hoarseness, otalgia and tinnitus, gastro-esophageal reflux, and chronic cough. Patients with SS tend to have a higher prevalence of sensorineural hearing impairment compared with the general population. Idiopathic hearing loss may represent the initial manifestation of SS. Furthermore, authors present and discuss the main neurological symptoms of SS. Neurological manifestations are reported in about 20% of patients with SS. In patients with SS, neurological manifestations may occur, such as peripheral neuropathy and other forms of neuropathies, including sensory ataxia, painful sensory neuropathy without sensory ataxia, multiple mononeuropathy, multiple cranial neuropathy, autonomic neuropathy, radiculoneuropathy and intra- and extraoral paresthesias, facial hypaesthesia, and trigeminal nerve neuropathy.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/66367",risUrl:"/chapter/ris/66367",book:{id:"7099",slug:"chronic-autoimmune-epithelitis-sjogren-s-syndrome-and-other-autoimmune-diseases-of-the-exocrine-glands"},signatures:"Bartłomiej Kamiński and Katarzyna Błochowiak",authors:[{id:"293810",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Kamiński",fullName:"Bartłomiej Kamiński",slug:"bartlomiej-kaminski",email:"bartl.kaminski@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"295583",title:"Dr.",name:"Katarzyna",middleName:null,surname:"Błochowiak",fullName:"Katarzyna Błochowiak",slug:"katarzyna-blochowiak",email:"kasia@naszdentysta.com.pl",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Poznan University of Medical Sciences",institutionURL:null,country:{name:"Poland"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Surgical technique and possible complications of LSGB",level:"1"},{id:"sec_3",title:"3. Histologic criteria for diagnosis of SS on labial salivary gland biopsies",level:"1"},{id:"sec_4",title:"4. Differentiation of focus lymphocytic sialadenitis",level:"1"},{id:"sec_5",title:"5. Limitations of the assessment of focus score",level:"1"},{id:"sec_6",title:"6. Other histopathological features of LSGB",level:"1"},{id:"sec_7",title:"7. Alternative types of salivary gland biopsies in SS",level:"1"},{id:"sec_8",title:"8. Oral involvement and xerostomia",level:"1"},{id:"sec_9",title:"9. Laryngological and otological manifestations of SS",level:"1"}],chapterReferences:[{id:"B1",body:'Shiboski CH, Shiboski SC, Seror R. 2016 America College of Rheumatology/European League Against Rheumatism Classification Criteria for primary Sjögren’s syndrome. 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Clinical and laboratorial profile and histological features on minor salivary glands from patients under investigation for Sjögren’s syndrome. Medicina Oral, Patología Oral y Cirugía Bucal. 2014;19:e237-e241\n'},{id:"B6",body:'Kim J, Sun D, Ozl R, Graderbeck T, Birnbaum J, Akpek EK, et al. A validated method of labial minor salivary gland biopsy for the diagnosis of Sjögren’s syndrome. The Laryngoscope. 2016;126:2041-2046\n'},{id:"B7",body:'Kroese F, Haacke E, Bombardieri M. The role of salivary gland histopathology in primary Sjögren’s syndrome: Promises and pitfalls. Clinical and Experimental Rheumatology. 2018;36(Suppl 112):222-233\n'},{id:"B8",body:'Delli K, Vissink A, Spijkervet FKL. Salivary gland biopsy for Sjögren’s syndrome. Oral and Maxillofacial Surgery Clinics of North America. 2014;26(1):23-33\n'},{id:"B9",body:'Franceschini F, Cavazzana I, Andreoli L, Tincani A. The 2016 classification criteria for primary Sjogren’s syndrome: What’s new? BMC Medicine. 2017;15:69\n'},{id:"B10",body:'Sarioğlu S, Küҫük Ŭ, Cetin P, Sari I, Bĭrlĭk AM. Minor salivary gland evaluation: Sjögren’s syndrome. Turk J Med Sci. 2016;46:63-65\n'},{id:"B11",body:'Varela-Centelles P, Sanchez-Sanchez M, Seoane J. Lip biopsy for the diagnosis of Sjögren’s syndrome: Beware of the punch. International Journal of Oral and Maxillofacial Surgery. 2014;43(1):127-130\n'},{id:"B12",body:'Giovelli RA, Santos MCS, Serrano E, Valim V. Clinical characteristics and biopsy accuracy in suspected cases of Sjögren’s syndrome referred to labial salivary gland biopsy. BMC Musculoskeletal Disorders. 2015;16:30\n'},{id:"B13",body:'Bamba R, Sweiss NJ, Langerman AJ, Taxy JB, Blair EA. The minor salivary gland biopsy as a diagnostic tool for Sjögren’s syndrome. The Laryngoscope. 2009;119:1922-1926\n'},{id:"B14",body:'Langerman AJ, Blair EA, Sweiss NJ, Taxy JB. Utility of lip biopsy in the diagnosis and treatment of Sjögren’s syndrome. The Laryngoscope. 2007;117(6):1004-1008\n'},{id:"B15",body:'Van Stein-Callenfels D, Tan J, Bloemena E, van Vugt RM, Voskuyl AE, Santana NT, et al. The role of labial salivary gland biopsy in the diagnostic procedure for Sjögren’s syndrome; a study of 94 cases. Medicina Oral, Patología Oral y Cirugía Bucal. 2014;19(4):e372-e376\n'},{id:"B16",body:'Tarpley TM Jr, Anderson LG, White CL. Minor salivary gland involvement in Sjögren’s syndrome. Oral Surgery, Oral Medicine, and Oral Pathology. 1974;37(1):64-74\n'},{id:"B17",body:'Chisholm DM, Mason DK. Labial salivary gland biopsy in Sjögren’s disease. Journal of Clinical Pathology. 1968;21(5):656-660\n'},{id:"B18",body:'Keszler A, Adler LI, Gandolfo MS, Masquijo Bisio PA, Smith AC, Vollenweider CF, et al. MALT lymphoma in labial salivary gland biopsy from Sjögren syndrome: Importance of follow-up in early detection. Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology. 2013;115:e28-e33\n'},{id:"B19",body:'Theander E, Vasaitis L, Baecklund E, Nordmark G, Warfvinge G, Liedholm R, et al. Lymphoid organisation in labial salivary gland biopsies is a possible predictor for the development of malignant lymphoma in primary Sjögren’s syndrome. Annals of the Rheumatic Diseases. 2011;70:1363-1368\n'},{id:"B20",body:'Bende RJ, Slot LM, Hoogeboom R, Wormhoudt TA, Adeoye AO, Guikema JE, et al. Stereotypic rheumatoid factors that are frequently expressed in mucosa-associated lymphoid tissue-type lymphomas are rare in the labial salivary glands of patients with Sjögren’s syndrome. Arthritis & Rhematology. 2015;67:1074-1083\n'},{id:"B21",body:'Ferro F, Marcucci E, Orlandi M, Baldini C, Bartoloni-Bocci E. One year in review 2017: Primary Sjögren’s syndrome. 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Annals of the Rheumatic Diseases. 2001;60:724-725\n'},{id:"B37",body:'Ashraf VV, Bhasi R, Kumar RP, Girija AS. Primary Sjögren’s syndrome manifesting as multiple cranial neuropathies: MRI findings. Annals of Indian Academy of Neurology. 2009;12:124-126\n'},{id:"B38",body:'Sakai K, Hamaguchi T, Yamada M. Multiple cranial nerve enhancement on MRI in primary Sjögren’s syndrome. Internal Medicine. 2010;49:857-859\n'},{id:"B39",body:'Tucci M, Quatraro C, Silvestris F. Sjögren’s syndrome: An autoimmune disorder with otolaryngological involvement. Acta Otorhinolaryngologica Italica. 2005;25:139-144\n'},{id:"B40",body:'Birnbaum J. Facial Weakness, Otalgia, and Hemifacial Spasm: A Novel Neurological Syndrome in a Case-Series of 3 Patient\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Bartłomiej Kamiński",address:"bartl.kaminski@gmail.com",affiliation:'
Department of Otolaryngology, District Hospital, Skarzysko-Kamienna, Poland
Department of Oral Surgery, Poznan University of Medical Sciences, Poland
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1. Introduction
Drug discovery and development grew into a wide interdisciplinary field during the last decades and many factors played and play an important role in the successful evolution from a bioactive compound, or so-called new molecular entity (NME), into a potential drug [1]. Herein, we discuss the drug discovery and development (DDD) process where the pharmacokinetic profiling in terms of ADME assessment is concerned. Therefore, we provide a short overview of the in vitro, ex vivo, and in vivo state-of-the-art techniques used in academy and industry with special emphasis on how recent advances in computer science paved the path for in silico prediction in the DDD process for small molecules. However, the discussion of the whole topic is out of the scope of this review, which only aims to give insights into the principle process of (computer-aided) drug discovery and development.
The current state of pharmaceutical DDD estimates that only up to ten compounds out of thousand screened hits would result in optimized leads and enter preclinical testing, with a chance of 9.6% to pass the clinical testing phase [1, 2]. Additionally, the drug approval process is estimated to last in average 15 years, with major expenses in phases II and III of clinical trials, which highlights the drawback a failure in (pre-) clinical testing causes [3, 4, 5, 6], where the overall DDD cost for each drug can reach as high as ~$2.56 billion preapproval rising to $2.87 billion including postapproval investments [6, 7, 8]. From the initial small molecule screened as hit to the optimized lead, a variety of in vitro tests are performed to guarantee efficacy and safety, but also to find structure-activity relationships (SAR), which can then be connected to specific physicochemical properties of the compound and further aid in the lead optimization phase [8, 9, 10].
The drug development phase starts with preclinical testing followed by the clinical stage comprising phase I–III human trials. Each of the phases aims to answer a specific question. Initially, preclinical trials are conducted in animals and can provide information about whether a drug is toxic or not. Compounds that show no toxicity in animals then advance to phase I trials, which will study whether the drug is also safe in healthy humans and provide an initial idea for appropriate dosage. In phase II, the efficacy of the drug is examined in parallel to potential side effects to answer the question if it principally meets the expected performance. Phase II presents the biggest hurdle with a transition success rate as low as 30%. Ultimately, drug candidates enter clinical phase III in which the preliminary results found so far need to be proofed and any adverse reactions monitored to make sure that the drug really helps treating the disease [2, 11].
Starting from the generation of a lead compound assessment, and optimization of pharmacokinetic properties and correlation to pharmacodynamic effects increases in importance as one of the three major attrition causes among toxicity and efficacy [8, 12]. In this sense, it is not surprising that the period between lead and the clinical candidate is sometimes referred to as “valley of death” due to the often occurring failures and dead ends during this time of the DDD process, which results in high costs and missing deadlines [13].
2. Role of computer-aided techniques in drug discovery
In a long ongoing effort, more and more in silico techniques are being integrated into several points of DDD with different purposes. In silico techniques can ease the process of SAR assessment as well as the generation of compound series by guiding combinatorial chemistry since they allow fast and easy evaluation of compounds prior to synthesis from big libraries. For instance, combinatorial chemistry offered an option to readily produce a broad range of potentially pharmaceutical active small molecules in a short time, while SAR data in combination with complex mathematical algorithms, such as regression analyses based or machine-learning–based approaches, allow to determine the potential effects of the analogues and derivative’s structures a priori [8].
Latter approach can save time and resources by eliminating in early stages molecules that have predicted low efficacy against the target or to suggest the next round of chemical modifications [14, 15]. Still, lead generation and/or optimization will eventually also include in vivo testing after no toxic side effect was shown in vitro. In vivo efficacy testing will be carried out as proof of concept followed by PK assessment and ultimately animal models of human disease to find correlations between preliminary data and potential performance later on in humans [12].
In silico ADME prediction aims to generate tools and models based on experimental data to calculate in vivo behavior of compounds by finding quantitative structure-property relationships (QSPRs), which connect structural information to physical and chemical characteristics or even biological behavior (quantitative structure-activity relationship; QSAR). Gained empirical data are then related to descriptors/properties thereby supporting the process of hit-to-lead optimization [10, 16].
When using in silico methods for prediction, it is important to keep in mind that algorithms and tools applied are only models thus being only as good as the data and idea they are based on. That implies a continuous experimental validation and improvement as a basic principle that is supported by an interdisciplinary team. In this sense, frequently used models include QSPR predictors, matched molecular pair (MMP), and data trend analysis since they allow comparably easy application and are based on a high amount of (end) point data. For instance, some experiments offer highly convenient data but do not contribute much to model design, whereas others show high variability but lead to impactful models. Considering the nature of data, it is important to know which type can be used as input from different sources (low variability biological and activity data or homogeneously calculated chemical descriptors) in contrast to data that should only be used from one source (Caco-2, MDCK). A sophisticated approach to generate reliable data or to determine differences between individual experiments is to use assays with control compounds [10]. The target property must be obtained under the same experimental condition and, in the best scenario, obtained from the same laboratory aiming to avoid interlaboratory and interpersonal data noise [17].
Furthermore, the choice of the number and type of molecular descriptors has a high impact, since it influences the accuracy and interpretability of the model. One would expect that using the maximum number of descriptors would be beneficial, but in reality, the risk of overfitting the data or losing the interpretability is a trade-off. This leads to the point that it is fundamental for a “good” model to find the perfect compromise between quality and quantity. Nevertheless, it is crucial to test and train a model and to evaluate its predictability by different means, such as statistical measures and internal and external validation as recommended by organizations as OECD [18], and also includes outlier analysis to reduce the noise in the model. An extensive review of different adequate validation methods is discussed in [19].
As a result of newly achieved advances in computational capability, more complex models and algorithms can now be applied. Despite this, it is still a challenge to create a model for the pharmacokinetic and pharmacodynamic phenomena and interactions within an organism as complex as a mammal, let alone humans [10]. Finally, notwithstanding the apparent linearity, the development of a new chemical entity into a drug is an iterative process, even more, where modeling is concerned, with data from failed attempts being integrated into the new predictions [13].
3. How specific parameters shape the pharmacology studies
Pharmacology is a major part of the DDD process and describes the interaction of an organism and the drug. It can be divided into two main branches: while pharmacodynamics (PD) describes what the drug does to the body, pharmacokinetics (PK) is interested in what the body does to the drug [20]. The main processes of PK are absorption, distribution, metabolism, and excretion (ADME), finally complemented by toxicity (ADMET). While ADME tries to maximize the pharmacological performance of a small molecule, toxicology aims to ensure that it causes no harm in any kind of side effect [21].
The big hurdle to overcome is to combine appropriate physicochemical properties of the drug, which would drive its interaction with the organism and show biological activity [22]. Or according to Hodgson: “A chemical cannot be a drug, no matter how active nor how specific its action, unless it is also taken appropriately into the body (absorption), distributed to the right parts of the body, metabolized in a way that does not instantly remove its activity, and eliminated in a suitable manner—a drug must get in, move about, hang around, and then get out” [21].
As already reviewed [23] and suggested by the FDA, PK/PD assessment is one of the main focuses for optimization in the drug development process. This is apparently an idea that was shared among many: whereas ADME evaluation was previously addressed in the late stages of preclinical development, currently it became a major concern throughout the whole DDD process, starting from the very beginnings in drug discovery approaches until the very last steps in lead optimization [21, 24].
For each step in the drug’s path through the body, several parameters determine the destination of the drug. In respect to this, each of those parameters would be addressed directly and individually. Unfortunately, to address experimentally each potential parameter is timely unviable, due to the complexity of the human body where all those parameters influence each other. This is not only restricted to mechanisms within the body between different compartments but also extends to interpersonal variations introduced through gender, age, genetic state, disease, etc. To find an approximation, most of the important variables are indirectly evaluated by either models or surrogates (Table 1). In an approach to characterize the properties of compounds, facilitate calculations, and allow standardization between experiments, descriptors are introduced as numerical representations encoding aspects of the chemical information of a molecule. Examples of descriptors and properties include molecular weight and H-bond donors/acceptors and they can be directly obtained from experimental or generated by computational techniques [25].
In vitro
Ex vivo/cells
In vivo
In silico
Absorption
Physicochemical properties Dissolution and solubility Cell monolayers Artificial membranes
MDCK Caco-2 Transfected cells
Mouse model Knock-out/down mice Humanized mice
QSPR/QSAR pKa logP, logD Binding and expression of transporters Inhibition of efflux pumps
Distribution
PAMPA IAM HAS-coupled (RP-) HPLC
Plasma/tissue binding
Vd Plasma protein binding
Vd Plasma protein binding Activity and expression of transporters
Metabolism
S9 fraction Liver microsomes Recombinant enzymes
Hepatocytes (HepG2) Isolated tissue Isolated organ
Humanized animals
Half-life Activity and expression of transporters
Excretion
Isolated tissue Isolated organ Transfected cells
Urine analysis
Half-life prediction
Table 1.
Tools for ADME evaluation.
For instance, although the perfect approach of PK profiling would also reflect the kinetics of drug administration and concentration at the site of action, most in vivo systems rely on plasma sampling as a medium of drug equilibrium since it is easily accessible. As a consequence, results are highly influenced by intrinsic and extrinsic factors such as interpersonal variances as already stated above [20].
Each compound possesses individual physicochemical properties, such as solubility or lipophilicity, which are influenced by biochemical properties of the body as the different pH of tissues. Although they can be similar, each compound will behave differently, and it is futile to address in vivo behavior without any preliminary knowledge of the basic PK parameters in vitro [26].
Furthermore, every PK assessment varies depending on the route of administration and requires different models and assays. While some routes depend on absorption mechanisms like oral and transdermal administration, others (i.e., intravenous) directly target the bloodstream and the bioavailability is essentially equal to 100%. Hereafter, we will discuss oral administration parameters of small molecules as the most common form due to many advantages like reliability, safety, price, their experimental approaches, and most common prediction modes [27, 28].
Passive transport across membranes is defined as permeability, which is dependent on lipophilicity, since biological membranes are virtually lipid bilayers, and is by far the most important transport for small molecules, especially in oral absorption [8, 24, 29]. Nonlipophilic compounds normally do not traverse membranes passively, while highly lipophilic molecules run the risk to get stuck within the membranes [30].
Properties utilized for measuring lipophilicity are the logarithm of the partition coefficient (logP) and the distribution coefficient (logD) with the first not differentiating between ionized and nonionized species. Both are normally applied for n-octanol/water representing an organic and aqueous phase, respectively [21, 26].
Ionizability and lipophilicity provide a strong indication if a compound is likely to be orally absorbed or not [21].
Ultimately, also the molecular size of the compound is involved in successful absorption due to the aforementioned effects on permeability and solubility [31]. Usually, increasing molecular weight by adding new chemical moieties leads to decreased solubility in aqueous solutions [32] and while big lipophilic compounds partition passively along membranes (transcellular), small charged molecules can also cross membranes via tight junctions (paracellular) [26]. For oral absorption in terms of permeability, Lipinski and collaborators already proposed in 1997 [33, 34] that orally active compounds should fit at least three of observed four parameters: molecular weight < 500 g mol−1, logP < 5; number of hydrogen bond acceptors <10; number of hydrogen bond donors <10; the well-known Lipinski’s rule of 5 (Ro5). In other words, Ro5 stated a physicochemical space in which molecules outside its domain has a low probability to become orally active. Other rules, as Veber rules [35], Daina and Zoete [36], Egan and collaborators [37], Lovering et al. [38], and Ritchie and colleagues’ [39] works for example, also included other properties as the sum of hydrogen bond acceptor and donors, rotatable bonds count, polar surface area, number of aromatic rings, and fraction of sp3 carbon atoms.
Despite the criticism and overinterpretation of Lipinski and derived rules, the influence of physicochemical parameters on oral bioavailability and related parameters (as logP and aqueous solubility) is notable. Moreover, these rules are still being employed nowadays in virtual screening campaigns aiming to reduce the number of compounds from massively large available libraries (e.g., ZINC, which contains more than 750 millions of compounds) [40, 41, 42]. Furthermore, those initial steps instigate the generation of more complex models to predict not just oral bioavailability but other PK-related parameters as Caco-2 permeability, aqueous solubility, and logP as indirectly related properties as well as other direct parameters as intestinal absorption, metabolism, clearance, etc.
3.1 Aqueous solubility and lipophilicity
As already mentioned, ionizability is one of the most important properties in PK, thus making pKa the physicochemical property with the highest impact.
Early attempts to increase the efficiency of pKa evaluation were reported by Morgan and colleagues by scaling down the classical titration and spectrophotometric methods introducing microscale versions [43].
These alterations, however, could not overcome the principle demands of each technique, which are moderate precision and frequent calibration (potentiometric), and the need for a chromophore within the analyte (spectrophotometric) [44]. Starting in 1998, capillary electrophoresis (CE) was effectively used to determine pKa of many compounds and was further upgraded from Pfizer by implementing pressure-assisted capillary electrophoresis (PACE) as a standard method, which is nowadays readily applied in industry settings showing superior features compared to the aforementioned methods [44, 45]. Other variants such as vacuum-assisted multiplexed capillary electrophoresis also exist (VAMCE) [46]. A different approach better suited for HTS is called pH gradient titration offered from Sirius Analytical Instruments but is still limited due to the UV spectroscopy technology [30].
It is well established that solubility in aqueous media is one of the most important physicochemical properties to be evaluated in oral administration. It is not only necessary for absorption in the GI tract but also a requirement for almost all in vitro and in vivo assays, which depend on a solved compound. Poor solubility can affect the reproducibility of assay results by introducing high variability and further increase development costs of leads with low solubility [26, 47]. Traditionally, solubility measurements were conducted via labor-intensive potentiometric techniques [48] or equilibrium solubility (thermodynamic; e.g., shake flask) [26]. HTS alternatives comprise laser nephelometric scans (kinetic) [47] and LC-MS/HPLC techniques, which can also be performed with DMSO solutions of the compound—the standard for HTS applications [47, 49]. It should be noted, though, that aqueous solubility, as described above, is not an optimal model for GI solubility since it does not consider the composition of the GI fluids [49].
On the other hand, generally speaking, lipophilicity is the ability of a compound to dissolve in lipids and/or organic solvents thus being able to pass biological membranes. Descriptors for lipophilicity are the logarithm of the partition coefficient (logP) or distribution coefficient (logD). Classically, logP was determined using the shake flask method applying n-octanol/water phases. Later, UV spectroscopy became the standard, which unfortunately is not applicable for compounds without absorption in the UV range [50]. Today, RP-HPLC methods are frequently in use due to superior properties [25, 51]. As with many methods, comparison of results obtained under different conditions and in different laboratories proves to be difficult with RP-HPLC. A solution offers the implementation of a standardized lipophilicity value, for example, the chromatographic hydrophobicity index (CHI).
In recent years, a great effort has been made to improve the ability of in silico models to accurately predict aqueous solubility. One of the most developed model is Yalkowsky and Jain’s [52] general solubility equation (GSE), which is based on the melting point (m.p. °C − 25) and logP (the octanol-water partition coefficient of the un-ionized molecule) of a chemical substance (Eq. (1)), with a relevant prediction power as represented by the coefficient of determination (R2) = 0.96 and root-mean-square error (RMSE) = 0.53 in a dataset of 1026 organic compounds [53].
General solubility equation as proposed by Yalkowsky and Jain’s [52]:
logS=0.5−0.01m.p.°C−25–logPE1
Modifications in terms of the GSE have been proposed, for instance with the SCRATCH model, which replaces the melting point by molar aqueous activity coefficient, with comparable accuracy (R2 = 0.956, RMSE = 0.859 in a dataset of 883 compounds) [54]. Ali and collaborators suggested replacing the melting point descriptor of the GSE with TPSA, aiming to overcome the issues with compounds with high melting points and also to explicitly take into account the effect of polar and polarizable atoms on the aqueous solubility [55].
The argument that real drugs are actually more soluble than drug-like molecules, filtered by Lipinski’s rule of five [56], pointed out the studies in the direction of more complex models. Indeed, nowadays, the quantitative structure-property relationship (QSPR) models correlating the aqueous solubility with various molecular descriptors are often employed. As an example, Chevillard et al. reported the use of a random forest protocol to select the most accurate model among several available, both in commercial or free software packages, for each compound [57]. They report that the multimodel approach can enlarge the applicability domain given that more accurate results for solubility prediction were obtained in comparison to using individual models. This approach agrees with other reports that consensus of local QSAR models can generate predictive workflows, especially for datasets with large structural diversity [58, 59]. It is worth noting that Lipinski himself recently revisited his own rules [60], in vision of new potential classes of drugs, such as natural products, peptide-like, and fragments, which, despite the validated effect, would defy the original Ro5 limits.
3.2 Ionization state and pKa prediction
Early pKa measurement proves beneficial in lipophilicity assessment since logD values at any pH can be calculated from the pKa and logP values [25, 50]. Although octanol/water logP is similar to most components in the body, not all biological partition processes (i.e., blood-brain barrier and gastrointestinal absorption) can be easily modeled by it [25].
The prediction of ionization state of compounds, which is indicated by the pKa value, is relevant to derive several other physicochemical and ADME properties of drugs, including solubility, lipophilicity, and pharmacokinetic profile. The use of pKa prediction can be placed in two different stages along the DDD, in the beginning with fast models for larger libraries, intending to generate all possible state populations of particular compounds, and/or later on with more refined semiempirical and, computationally expensive, the density functional theory (DFT), in which more accurate ionization states can be accessed. Examples of fast prediction methods for ionization states, which are available as computer programs, are SPARC [61], MoKa [62], and Epik, which use the Hammett and Taft approaches for the pKa prediction [63]. On the other hand, once smaller subsets of molecules are being addressed, the use of semiempirical or density functional theory (DFT) with more computationally expensive models was reported to accurately incorporate the structural features and diversity into the pKa prediction [64, 65].
3.3 Permeability and the use of cellular and noncellular models
As already seen, lipophilicity (logP, logD) is highly involved in membrane permeability. Apart from the already described in vitro methods for logP and logD determination, systems for ex vivo/in situ but also in vivo assessment exist as “direct empirical” determination of permeability. When talking about permeability, the difference between passive diffusion and transporter-mediated active transport needs to be considered.
Cell culture methods have been applied to study intestinal absorption for several decades already [66]. Finding the correct model or cell line is crucial to assess the desired parameters such as passive or active transport. In general, it cannot be distinguished between the different transport mechanisms when using cell culture approaches, but several models exist to shift the focus on one of the parameters.
Two main cell lines are in use as models for intestinal absorption: Caco-2 and MDCK cells. Caco-2 cells are derived from a human colorectal carcinoma and possess many of the typical properties of the small intestine, therefore representing a well-established and validated assay system for absorption, permeability, and secretion studies [21, 67]. This assay is mainly used for rank ordering of compounds in terms of oral absorption and permeability in early phases of drug design. Unfortunately, results obtained in different batches and laboratories vary heavily due to several reasons, which make control compound usage necessary and represent a drawback of the technique [26]. Additional disadvantages include long preparation times (about 3 weeks) and no specific permeation mechanism evaluation. Caco-2 assays are usually used as a primary assay followed and complemented by other in vitro and ex vivo methods [68]. Recently, a 3D version of the Caco-2 assay, “Caco-2 3D spheroid permeability assay” was reported, increasing the overall performance and correlation to a human in vivo data [69].
As already stated above, transcellular permeation either occurs passively via diffusion of lipophilic molecules or is driven by membrane transporters. Important transporter includes ATP-dependent efflux transporter such as MRP2, BCRP, and P-gp and the organic solute transporter and the multidrug resistance protein 3 (MRP3) on the luminal and basolateral membranes, respectively [26].
Madin-Darby canine kidney (MDCK) cells are an alternative to Caco-2 cell-based assays and the next most common cell line for passive permeability assessment as well as drug-receptor interaction [70]. MDCK cells also are ideal for transfection and overexpression experiments with human transporters and receptors due to the lack of P-glycoprotein [68, 71]. For instance, the MDCK-MDR1 cell line overexpresses the multidrug resistance protein 1 (MDR1, P-glycoprotein) and can be used in concert with other cell-based assays to specifically address the influence of MDR1 in drug efflux [72].
Immobilized artificial membranes (IAMs) were already used very early on for lipophilicity determination and are gaining interest again in recent years for direct permeability measures [25]. IAMs are also intensively used in the measurement of the volume of distribution to mimic in vivo binding to phospholipids and phospholipid bilayers (membranes). Therefore, IAMs are discussed in more detail in the following section.
The parallel artificial membrane permeability assay (PAMPA) [73] is a cheap and fast in vitro alternative to cellular-based assay systems. A very comprehensive review of recent PAMPA methodologies and applications is available [74]. In principle, PAMPA was developed to overcome cellular-based systems (Caco-2, MDCK, etc.) for passive permeability evaluation, which are error-prone, more difficult, and labor and time intensive and tend to report false negatives. Another advantage of PAMPA over conventional cell-based assays is the ability to selectively measure passive permeability, while in cell-based systems influence of membrane transporters cannot be left out. PAMPA assays can be readily applied in high throughput processes or scales and different variants exist to address ionic and H-bonding with membranes that influence permeability and complement the use of Caco-2 and other cell assays [73]. Bermejo and colleagues also showed a significant correlation between Caco-2, in situ rat perfusion, and PAMPA assay data underlining applicability of the method for ADME assessment [75].
Although high-throughput applications of newly developed and standardized techniques allow gathering of an exorbitant amount of data, it is crucial to also (cor)relate the physicochemical and biomimetic properties to structural features of the compound. This will facilitate the development of QSPRs and allows the construction of in silico models ultimately guiding the medicinal chemistry efforts [25].
When dealing with oral administration, it is important to note that the drug is not only confronted with the hurdles of solubility and permeability in the absorption process but is also facing metabolizing mechanisms (i.e., enzymes) in the gastrointestinal tract, which are referred to as first-pass metabolism [24, 76]. These include but are not limited to P-glycoproteins, uridine diphosphate glucuronosyltransferase, and mainly cytochrome P450s (CYP450) [24]. This will be discussed more deeply in the Metabolism section.
Permeability has a direct influence on the drug absorption rate and, as discussed, despite the several in vitro cellular models available (e.g., Caco-2, PAMPA, and MDCK), the high costs justify the use of in silico prediction. Further, QSPR study developed using a large compound dataset of Caco-2 permeability data (1272 compounds) presented good apparent permeability prediction accuracy (R2 = 0.81 for the test set) using the polar volume, number hydrogen bond donors, and the surface area as main descriptors [77].
However, we are far from a model that can predict overall permeability and, the current status, rather focuses on individual compartments and tissues, such as the gastrointestinal (GI) tract, skin, buccal membrane, and the blood-brain barrier (BBB). Since the first BBB permeability correlations with logP in 1977 [78], models to predict BBB permeability, particularly logBB (Eq. (2)), have greatly advanced. Current models using an array of machine-learning methods such as multilinear regression, support vector machine (SVM), and artificial neural network (ANN) against a dataset of 320 unique compounds had good predictive power (R2 = 0.89) [79]. The work of Shen et al. developed SVM models using 1593 compounds (1283 BBB+ and 310 BBB−) by using different pattern selection methods and obtained the overall accuracy of 98.2% [80]. Both methods have the limitation of unbalanced datasets (where the number of BBB+ is higher than the BBB− within the training set), which was addressed on the work of Wang et al. by using resampling methods coupled with the machine-learning techniques, to achieve accuracy rates of 0.919 in external test data [81]. Wang and collaborators compiled a dataset of 439 unique molecules, which were employed to generate a diverse set of QSAR models and consensus (R2 = 0.504 for external dataset prediction). They also reported the use of transporter profiles as additional biological descriptors to develop hybrid QSAR BBB models, with an improved correlation coefficient R2 = 0.526 for external validation [82].
LogBB can be calculated by the log of the ratio between the concentration within the brain (Cbrain) by the bloodstream concentration (Cblood) of the determined chemical entitiy
logBB=logCbrainCbloodE2
Finally, beyond the usual ADME parameters of interest in DDD, there are several other unusual ones that also can be predicted; as examples, we here point the permeability of the models for skin permeability, which evolved from simple diffusion models based on molecular weight and n-octanol/water partition coefficient [83, 84], until more sophisticated models, such as (non)-linear QSPR models and even molecular dynamics simulation (as extensively reviewed by [85, 86]).
4. ADME properties: experimental approaches and in silico models
4.1 Absorption
Oral bioavailability is defined as the amount of drug that reaches the site of action after oral administration and is influenced by factors like drug solubility and dissolution, chemical and enzymatic stability in the gastric and intestinal lumen, interacting luminal contents (food), gastrointestinal transit time, enterocyte permeability, and intestinal and hepatic metabolism [24]. Recently, bioavailability has been also described as the rate and speed of the drug to reach systemic bloodstream, considering the initial formulation as the starting point.
Oral administration includes a pharmaceutical phase—prior to PK and PD phases—that comprises disintegration and dissolution of the dosage form. When using oral dosage forms, the shape and chemical composition (e.g., tablets) play an important role since they contribute to the time needed for disintegration and dissolution.
Following the pharmaceutical phase, absorption is the first step in the pharmacokinetic phase and is defined as the movement of the drug from the site of administration to the bloodstream. The main properties determining the rate of oral absorption for small molecules are permeability and solubility [87].
As such, the rate of dissolution and ionization, which are described by the Noyes-Whitney and Henderson-Hasselbalch equation, respectively, is the key factors in lead optimization for oral administration and is complemented by lipophilicity as an additional factor influencing membrane permeation and solubility of the compound [31].
Dissolution can be expressed by a function of the aqueous solubility of a compound, the surface area of the administered tablet (or the particles in other solid formulation), and a specific dissolution rate constant. Altering any of these parameters directly affects the dissolution profile [26]. While solubility is an endpoint value indicating the amount of a compound that is soluble in a solvent, dissolution describes the kinetic process of a compound being solved in a solvent [88].
On the other hand, ionization reflects if a compound is present in the charged or uncharged state and is at least influenced by two major parameters. The physicochemical property responsible for ionization is the pKa and describes the ionization state of that entity at a given pH. It is also referred to as aqueous ionization constant [30]. Thereby, it is directly influenced by the pH of the environment, the second parameter, which drastically changes on the way through the GI tract, from about pH 1 to 8 in the stomach and ileum, respectively.
The determination of the ionization state of a compound in the gastrointestinal system (stomach, jejunum, ileum, and colon) is crucial for absorption since it not only influences the solubility of a compound but also the lipophilicity and permeability [26, 30, 89]. About 60–70% of all drugs (effective 1999) are ionizable, which underlines the role that ionization plays in ADME assessment [30, 90]. While charged molecules easily dissolve in aqueous systems (GI tract), they do not permeate membranes via passive diffusion and are reliant on active transport. The contrary is true for uncharged molecules, which pass biological membranes passively but show low solubility in aqueous solutions. Mechanisms of drug absorption include passive diffusion, active transport, and receptor-mediated endocytosis, which are influenced by different factors and can themselves influence the bioavailability.
Similar to model and prediction, the absorption of a drug is a complex process, which is influenced not only by the physicochemical properties of drugs themselves but also by the physiological state of the tissue in question. As such, there are a large number of prediction models available, which were generated based on the physicochemical properties involved in the absorption process, such as membrane permeability and drug solubility. These models can help formulation scientists to optimize drugs with poor absorption due to low aqueous solubility.
Initial absorption models can be separated into dispersion and compartmental models [91]. While dispersion models treat the GI as a continuous system, with variable pH and surface area, compartmental models take into account physiological factors such as transporters. The compartmental absorption transit (CAT) was one of the first models to regard distinct physiological properties, such as the minimal absorption in the stomach and colon, while assuming some mathematical simplifications, such as the instant dissolution of the drug and linear kinetics [92]. CAT was further modified as advanced CAT (ACAT), by including nonlinear absorption kinetics and the effects of the first-pass metabolism. ACAT also considers the gastrointestinal tract as nine subsections, each with unique physicochemical properties, such as pH, allowed solubility, particle size, and permeability [93]. Novel developments have included other absorption routes other than the GI, which have been recently included in commercially available software, such as oral absorption for the development of sublingual zolpidem tablets [94]. The absorption constant (Ka, expressed in terms of h−1 min−1), or also called first-order absorption rate constant (to not be confounded with pKa), is employed in most of the aforementioned models and is determined as a result from the changes in mass of absorbable drug over time at the site of administration. Ka can be derived from the decrease in the drug amount of absorbable present at the site of administration over time; however, it is often indirectly determined by the drug amounts measured in the blood and/or urine.
Along physicochemical models, which have a global application, machine-learning techniques were extensively employed to model absorption (as comprehensively reviewed by Kumar et al. [95]) and are inclined to be local models, since they are mostly based on a small, homogeneous dataset that influences their applicability domain.
4.2 Distribution and the role of plasma-binding proteins
After being absorbed and entering the circulatory system, the drug moves reversibly between different compartments within the body, which is described as distribution and influenced by several physicochemical properties of the drug and biological factors of the body. One of the most important properties is lipophilicity, and as such logP/logD, since it reflects the ability of the compound to pass biological membranes to reach other sites, tissues, and organs within the body [25]. Additional factors include phospholipid and (plasma) protein binding, which reduces the free drug concentration within the body, can prevent the migration to the receptor side/side of action, and causes drug-drug interactions [25, 96]. Interestingly, binding to plasma proteins can also prolong the drug action by releasing the drug over a longer period of time. It is also important to note that the influence of lipophilicity on plasma protein binding is hypothesized to be higher for acidic compounds than for bases, meaning that negative charges contribute highly to plasma protein binding and prevent tissue binding, which leads to diminished volumes of distribution (Vd, Eq. (3)). The Vd is the amount of drug that is freely available in the blood, thus not bound to plasma proteins or other components [25, 97, 98]. Vd is an apparent volume that increases proportionally to the extravascular drug binding and not an anatomically defined volume. Consequently, extensive drug binding outside the bloodstream leads to increasing values of volume distribution.
Volume distribution (Vd) is defined by the ratio between the amount of drug in the body (A) and the drug concentration in plasma (C, comprising both free drug and protein-bound drug):
Vd=ACE3
The parameter describing protein binding is the plasma protein affinity constant Ki. Many efforts to determine distribution led to chromatography-based methods, such as (RP-)HPLC to mimic n-octanol/water logP or lipophilicity to measure distribution. In general, chromatographic methods are believed to resemble biological partition processes more than octanol/water partition [25]. In the beginning, stationary phases in (RP-)HPLC were either silica-based or polymer-based but both had difficulties to reproduce logP and logD values despite several additives in the mobile phases [99]. The introduction of biomimetic (stationary) phases coated with human serum albumin (HAS), α1 acid glycoprotein (AGP), or immobilized artificial membranes (IAM) revolutionized the methodology since they allowed a better approximation of the biological system [25, 100].
A method to address plasma protein binding is the use of HSA and other plasma proteins (e.g., α1 acid glycoprotein) coupled with RP-HPLC [25, 101]. On the other hand, HPLC combined with IAMs is a popularly accepted technique for phospholipid interaction and partition and several IAM columns are commercially available for DDD projects. Both techniques represent good assay systems to model in vivo Vd in high-throughput scale [98]. Problems with HPLC techniques, which are also true for biomimetic phases, include the lack of a gold standard that is needed to calibrate and later standardize results to make a comparison possible [25].
In vitro standard methods for unbound plasma fraction calculation include equilibrium dialysis and ultrafiltration among several others as the two most commonly used methods and are considered the gold standard for binding assessment [26].
To calculate the Vd “a priori”/nonexperimentally, plasma protein binding, experimental logD and pKa are necessary. Then again, based on the Vd, the half-life (t1/2) of a compound can be calculated [102]. Apart from protein binding, tissue binding is also involved in the distribution of the compound. Generally, “tissue” here comprises several components of the human body such as lipids, DNA, or RNA and is also referred to as nonspecific binding [26].
In silico models to predict the Vd are often based on lipophilicity and solubility descriptors, which correlate with the fractions of the drugs that are either bound to plasma proteins or freely available. The work of del Amo et al. not just accurately predicts Vd and unbound drug fraction but also compares the model’s performance against the commercially available software VolSurf+ with comparable accuracy (R2 = 0.70 and 0.71, respectively) [103].
Expanding these studies, the work of Lombardo and Jing generated a set of models to predict the Vd in the steady state (Vss), using a dataset of 1096 diverse compounds [104]. They compared models generated by linear (PLS) with nonlinear (Random Forest) models, recommending the latter, with 33 descriptors, as the optimal method for Vss prediction.
The Vd of drugs is greatly influenced by binding to plasma proteins with several machine-learning–based models generated to predict this interaction. Protein-protein interaction (PPI) information derived from molecular docking was employed to derive a PPI-QSAR model for a small dataset of antibiotics (65 unique compounds), which resulted in an accurate model (R2 = 0.86 for the test set) [105]. Additionally, global quantitative models using an array of classification and regression models using physicochemical and molecular descriptors derived from a dataset of 794 compounds were shown to correctly classify the binding status of the test set compounds and could be used as a prescreening [106]. Another recent QSAR study using an extensively curated training set of 967 diverse pharmaceuticals aimed to predict plasma protein-bound fractions (fb) using models generated by six machine-learning algorithms with 26 molecular descriptors [107]. This study is particularly interesting where the applicability domain is concerned allowing to differentiate whether the classification derives from (un-)favorable regions.
del Amo et al. recently reported one of the first QSPR models to predict intravitreal volume of distribution and clearance of small molecules [108]; the model relies on the LogD and hydrogen bond capacity to understand phenomena such as intraocular pressure and guide drug discovery. Complementarily, the prediction of the drug passage through the blood-ocular barrier was described to be an important factor to evaluate volume distribution in this organ [109].
Recently, as a novel approach bridging the animal experiments with human results, it was shown that in PXB mice, a chimeric mice linage with a humanized liver, plasma concentration-time profiles could be used to infer human’s compound half-life [110].
Volume of distribution is also closely related to half-life and clearance parameters. As the Vd is a relative measurement of the free concentration of drug in the blood, this same amount could be excreted by kidneys in the glomerular filtration (clearance). Consecutively, the rate of clearance (discussed below in Excretion section) directly influences the amount of available drug. Naturally, the concentration of free drug that can bind its molecular target is related to the therapeutic dosage and the half-life of the administered drug (as seen in Eq. (4)).
Half-life definition. Half-life is calculated by a ratio between the Napierian logarithm multiplied by the volume of distribution (Vd) and renal clearance (CL):
t1/2=Ln2.VdCLE4
4.3 Metabolism
Drug metabolism normally involves enzymatic modification or degradation of the compound to facilitate excretion via one of the major clearance organs: liver, kidney, spleen, or bile. While phase I enzymatic reactions include modifications such as oxidation, hydrolysis, and reduction to either introduce a functional group to the molecule or make it accessible, phase II reactions are conjugation mechanisms (e.g., methylation, acetylation, glutathione conjugation, amino acid conjugation, and others) that result in polar products that can be actively effluxed [26]. Thus, isozymes of the CYP450 family and efflux transporters such as P-glycoprotein and members of the multidrug resistance transporter MRP family are highly involved in the metabolism of drugs as well as drug-drug interactions, which are a major attrition cause. For instance, CYP3A4, CYP2C9, and CYP2D6 together catalyze the hepatic metabolism of about 50% of drugs, which underlines the importance of the superfamily. Interestingly, when CYP3A4 is expressed, usually P-glycoprotein is as well [8, 10, 14, 24, 111]. An approximation for metabolic behavior analysis is the use of either liver microsomes or S9 fractions although also recombinantly expressed proteins are partially in use [24, 26].
When available, the 3D structure of those proteins could be employed in molecular docking and molecular dynamics simulations aiming to predict the binding affinity of drugs or drug candidates aiming the estimation of a PK profile [112]. The metabolism prediction combines mathematical models to predict whether the target compound could be a substrate of a specific enzyme in combination with metabolism site predictions. Usually, those initial predictions are followed by molecular docking simulations and quantum mechanics simulations due to the dependency of electronics structure from both substrate and enzyme in catalyzed reaction [113, 114].
Nowadays, several attempts have been made to develop in silico models for predicting drug metabolism, specifically site-of-metabolism (SOM), and quite often are also converted into online server prediction tools for general use, for instance, the FAst MEtabolizer (FAME) model, which was generated from a diverse chemical datasets of more than 20,000 molecules and their respective experimentally determined metabolism sites. FAME prediction rates were comparable to other metabolism site predictors focused on specific enzyme families, despite using only seven chemical descriptors [115]. Similarly, SMARTCyp server, which initially relied on the 2D structure of the molecule, without considering electronic properties or generating 3D structures, to predict CYP2D6 [116], was later expanded for other CYP isoforms. A more refined version was later updated to include the atomic solvent accessible surface area, which is independent of 3D coordinates, slightingly improving the overall prediction accuracy for different CYP isoforms [117]. The newest SMARTCyp version (3.0) uses the activation energies calculated by the density functional theory (DFT), meaning the difference between the energy of the transition state and the reactant complex, to predict SOMs of molecular fragments of the query in an unsupervised fashion. SMARTCyp 3.0 also calculates the similarity between the query molecule and the model fragment [118].
IDSite approach aims to overcome the ligand-based bias of SOM prediction by using it as a part of a large framework, more precisely by combining it with molecular docking, where an atom can be considered a significant SOM by a P450 enzyme when accessible to the reactive heme iron center, and/or quantum calculations, where the candidate atom must have some degree of reactivity in the absence of the enzyme [119]. Similarly, the work of Kingsley et al. combined different approaches into a framework to predict CYP2C9 substrates. They validated the predictions from SMARTCyp in an ensemble docking, followed by a QSAR model to account for influences of both the inherent reactivity of each atom and the physical structure of the CYP2C9 binding site [120]. This combined approach resulted in 88% of true SOMs accurately predicted among the top ranked sites.
4.4 Excretion
Excretion is guided by one of the major clearance organs, and the assessment of clearance behavior sometimes involves isolated organs or tissues [24]. Humans rely on the kidney clearance as a major route for xenobiotic excretion, despite other available routes such as feces, bile, sweat, and breath. The excretion pathways directly impact the concentration of available drugs and are often measured in terms of half-life and the initial administered dose.
The renal clearance of a drug is another important parameter, which is usually employed to predict drug excretion. Experimentally, clearance is defined by the drug concentration drug along a defined time of renal excretion by a linear equation (Eq. (5)).
Equation for renal clearance. m is the substance’s mass generation rate, K is the clearance and C is the concentration at the time, and V is the volume where the drug is distributed, or for systemic approaches the total body water.
V.dCdt=−K.C+mE5
Gombar et al. developed SVM- and MLR-based QSAR models to predict both systemic clearance and apparent volume of distribution from intravenous data [121] using as input structural fingerprints and electro-topological states (so-called E-states), respectively. The model performed with high accuracy, despite the highly diverse initial dataset employed for its generation, which points the importance of those models in early steps of the drug-discovery pipeline.
Also, the work of Kusama et al. established a chemoinformatic-based classification model to predict the major clearance pathways of 141 approved drugs based on four physicochemical parameters: charge, molecular weight, lipophilicity, and protein unbound fraction in plasma, resulting in a final model with an accuracy of 88% [122]. This model approach was further refined by using support vector machine and increasing the number of relevant descriptors [123]. In order to better model the biotransformation processes, often the major triggers of excretion, the work of Berellini et al. used ELASTICO (Enhanced Leave Analog-Structural, Therapeutic, Ionization Class Out) to provide an appropriate sampling during the validation process. Their partial least-square models resulted in a highly accurate model derived from 754 compounds [124].
On another topic, ABCB1, also known as P-glycoprotein (P-gp or MDR1), is a membrane protein member of the ATP-binding cassette (ABC) transporters superfamily. Together with the hERG channel and CYP3A4, P-gp is one of the most widely studied antitarget, where its inhibition could bring consequences for several processes, such as the absorption, distribution, and excretion of drugs. Classical studies used chemometric methods to describe bioavailability in terms of P-gp and CYP enzyme activities, generating QSAR models based on 805 unique drug molecules with high accuracy (R2 = 0.80 for the test set) [125]. Alternatively, an approach to predict P-glycoprotein inhibition using molecular interaction fields, derived from a literature collection of more than 1200 structures, generated a pharmacophore model for competitive P-gp inhibition [126].
The most recent reported studies involving prediction of drug clearance, both from human and rat hepatic in vitro systems, were based on microsomes, with a recent emphasis on the use of hepatocytes. Wood et al. discuss the inherent limitation of using human hepatocyte predictions, due to underprediction when compared to in vivo clearance data, and the comments on the potential causes for those divergences [127].
As the pinnacle of ADME in silico approaches, the holistic physiologically based pharmacokinetic (PBPK) modeling was initially conceptualized by Teorell [128], aiming to enable the prediction of drugs’ pharmacokinetic behavior in humans using preclinical data. Recent PBPK models benefit from the large amount of available ADME data not only to aid the drug discovery process and dose regiment selection but also to guide the risk assessment for regulatory reviews [129]. PBPK models are compartmentalized representations of the different organs, and each compartment can be described by a specific tissue volume and blood flow rate, which communicates with the blood (venous and arterial). Each organ/tissue has a unique volume, permeability, and eliminating anatomical constants and terms, which are determined independently from the studied drug, while other physiological drug-specific parameters are later incorporated, such as affinity toward plasma proteins, tissue-to-plasma distribution rate, and even on target activity (Km, Vmax, or binding kinetics).
One of PBPK models’ important features is the perspective for the mechanistic and prospective prediction of a drug’s pharmacokinetic profiles. The use of drug-dependent parameters includes, but is not limited to, physicochemical properties, solubility and permeability values, and also the role of individual enzymes and transporters in the metabolism. Those parameters can be determined in vitro or calculated from the compound structure with other in silico approaches, which allows the early use of PBPK in the DDD (the bottom-up approach). Concurrently, it is also noteworthy that the model construction and parameter fine-tuning are a source of knowledge for the hit development, where the predictions from the ongoing model can help to understand the model’s accuracy itself along the way (called as middle-out approach) and then prospectively be applied to simulate unstudied scenarios. Currently, there are several free-to-use and commercially available PBPK and ADME prediction options (Table 2), which are also extensively reviewed and discussed by the works of Madden et al. [130].
Name
Description
Link/reference
ADME prediction
vNN-ADMET
Public web server for ADMET property prediction based on 15 nearest neighbor models.
Comprises 10 different modules including PBPK modeling and in vitro vs. in vivo correlation, can be parameterized for different disease states and age groups.
PBK modeling tool with integrated database of anatomical and physiological parameters for humans, mouse, rat, dog, and monkey. Can model different scenarios depending on the chosen building blocks.
Incorporates databases of genetic, physiological, and epidemiological information to enable simulation of different populations and species, ultimately is able to predict ADME parameters.
Early PBPK models, such as the work of Varma et al., described another layer of complexity by including drug-drug interactions (DDI). The dosing time-dependent model considering the interaction between repaglinide with rifampicin was able to predict repaglinide plasma concentrations along a day. The model also predicted the drug interaction with other CYP3A4 and OATP1B1 inhibitors, which could result in further DDIs. Reports of DDI leading to complications in patients with particular genotype stimulated studies such as the one performed by Fermier et al. [131], where the effects of polymorphic cytochromes provided the basis for a more accurate DDI prediction.
5. Biological (large) molecules
During recent years, larger molecules (LM) have gained in significance and popularity, due to achievements and approvals, as new molecular entities. These “biologics” are normally biotechnologically synthesized or recombinantly produced compounds of biological origin such as peptides, antibodies, and nucleic acids [136]. From a historical perspective, drug discovery and development of LMs are heavily delayed in comparison to SMs with their first approved entity happening in the 1980s [137]. At about the same time, two major inventions allowed huge progress in pharmacokinetics assessment of small molecules, contributing to smaller drop-out rates in later DDD stages [136]. One of them was the improved understanding of CYP450 mechanism and the other, the invention of (HP)LC-MS technology, fueled the assessment of the ADME parameters. LMs’ discovery and development face many challenges, which demand high efforts to overcome but also offer unique opportunities in comparison to those of small molecules [138, 139].
The main differences between small and large molecules, despite the molecular weight, the number of heavy atoms, and torsions, can be found in the physicochemical properties, such as permeability, oral bioavailability, stability, specificity, and immunogenicity [138, 139]. New parameters, unique for large molecules, are also of interest, such as the physical particle size and the hydrodynamic radius, which has a dramatic effect on the absorption. Both parameters are related to the overall shape and correlate well with MW for globular proteins, but not necessarily for unstructured or highly modified entities. As a result, biologics are normally administered parenterally, only targeting extracellular structures; they are also more likely to trigger an immune response; and their production costs are considerably higher [139]. Interestingly, with the exception of the costs, these disadvantages can potentially be circumvented by appropriate delivery systems, for example, nanoparticle-based delivery to facilitate membrane permeation.
Other parameters, such as charges, which were previously modeled by pKa in case of small molecules, are heavily heterogeneous in LMs. The charge can be represented by the use of isoelectric points (pI), which are calculated from the available amino-acid sequence, and surface charge, which can use individual pKa’s and structural information to be inferred. Overall protein charge often influences the biologic excretion [140], since negatively charged molecules undergo less renal filtration disregarding size effect [141].
While representing difficulties in the development of new molecular entities, the aforementioned properties also offer special advantages that small molecules cannot cover. As such, LMs normally have longer t1/2, slower clearance, and higher selectivity; are multifunctional; and rarely expose drug interactions [139]. Apart from those, it was suggested that only 2–5% of the human genes can be targeted by small molecules, offering a niche for LMs’ application against several diseases [138].
The increasing effort and development of new technologies, driven by the belief in higher success rates, enabled the latest advances in the field [138]. For instance, currently, peptide drugs only account for ~2% of the drug market but are in use in a wide range of diseases such as acromegaly and multiple sclerosis, together with different cancer types such as prostate and breast cancer.
Several other biologics are currently in use, namely monoclonal antibodies (mAbs) and bispecific antibodies (bsAbs), as example agents that activate or enhance the immunologic response. Of special interest in cancer therapy is a subclass of bsAbs, so-called bispecific T-cell engager (BiTEs), which can recruit CD3 cells at the tumor site by binding to both cell types thereby directing the immunological response [142].
Other interesting examples for biologics comprise hormones (e.g., insulin), cytokines (such as erythropoietin, EPO; IL-1; IL-2; IL-6) [143], nucleic acids such as siRNA (ONPATTRO) [144], and aptamers (Pegaptanib) [145]. While such a broad spectrum of molecule classes offers also a wide range of treatments, at the same time, it exacerbates the need for new developments since every molecule type exhibits different properties. In the field of predicting the biologics activity against specific targets, classical modeling tools, such as Monte Carlo sampling, genetic algorithms, docking, and molecular dynamics simulation, were adapted or even developed anew to accommodate the specifics (as extensively reviewed by [146, 147]).
On the other hand, the absence of standard techniques to assess ADME properties hampers the PK profiling and thus further development [136]. In fact, the current knowledge of LM pharmacokinetics is even impaired compared to the basic knowledge of ADME principles for small molecules in the 1980s [136]. Although the basic PK principles are similar between SMs and LMs, the specific mechanisms influencing each step of ADME are different. To begin with, the route of administration between them can differ, which leads to different mechanisms of absorption and first-pass metabolism. Furthermore, LMs are not metabolized by CYPs but can still trigger the release of pro-inflammatory cytokines leading to heavy side effects known as cytokine storm [136, 139]. Also, other modifications play a role in biologics ADME, namely glycosylation, PEGylation, and neonatal Fc receptor (FcRn) interactions [139, 148]. Unfortunately, up until now, most of the evaluation of those factors is only addressed on in vivo level systems, which are not suited for HTS, are expensive and labor intensive, and require longer bioethics evaluation.
In this regard, the development of in vitro and in silico methods to evaluate ADME should be a high-profile goal. One of the main challenges will be to find a way to integrate as many of the biologics into the process in order to facilitate ADME assessment and guide large molecules’ DDD as already implemented for their smaller counterparts.
6. Conclusions
The main difficulties in PK profiling lie in the high costs and comparable low throughput of in vivo models. The extensive use of animals in DDD also raises ethical issues and is further affected since animal models not always translate readily to the humans, especially in terms of metabolism [149, 150]. Furthermore, the advent of combinatorial chemistry coupled with HTS for efficacy evaluation leads to an explosion in the number to an extent that the classical PK assays could not compensate [29, 47]. In vitro PK screens are supposed to offer a solution to the problem by complementing in vivo assessment to reduce costs while increasing efficiency, but they also suffer from shortcomings. In general, one must distinguish between two main forms of in vitro systems: static and dynamic models. Only dynamic models are suited for PK evaluation because they allow variation of compound concentrations, a key factor in pharmacokinetics. In this sense, diffusion-based dynamic in vitro models offer a solution but still are quite limited in terms of high throughput and costs. An alternative was presented by Lockwood and colleagues in the form of a 3D-printed fluidic device utilizing trans-well technique generating dynamic in vitro PK profiles also applicable for HTS infrastructure [149].
What distinguishes the DDD “then” and “now” is principally two main changes. First, in the past, pharmaceutical companies as well as academic laboratories were not that concerned with ADMET assessment in the early stages of drug discovery (hit and lead generation) and only addressed PK from preclinical stages on forward. Instead, HTS/HCS, genomics, and computational chemistry were high-profile areas. Today, almost all pharmaceutical big-players have shifted pharmacokinetic profiling to discovery phases. However, only the future will tell whether those changes will yield fruit.
Second, CADD became more and more part of the DDD pipeline in different stages facilitating fast screening of compounds in silico and supporting QSAR. Although bioinformatics techniques already substituted many in vitro tests, basically all of them require in vitro and/or in vivo validation and standardization to guarantee trustable predictions. Another important aspect, recently addressed by the work of Ferreria and Andricopulo [151], is the importance of translating those models into well-structured and user-friendly (online) platforms that can be accessed and used by the drug discovery community. Still, the efficacy and reliability of computer simulations increase permanently and drastically, and many see a future of solely virtual drug discovery. Thankfully, these failures resulted in the consequence of addressing safety and efficacy concern earlier in the drug discovery process, for instance, via in vitro screens to assess metabolic stability and absorption properties and diminish failure rates later on [13].
Acknowledgments
The authors would like to acknowledge the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP grants 2018/08820-0, 2017/03966-4, and 2015/26722-8). The authors would like to thank Prof Dr. José Eduardo Gonçalves for his valuable comments on the manuscript.
\n',keywords:"ADME, drug discovery, in silico prediction, pharmacokinetics prediction, QSAR",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/66969.pdf",chapterXML:"https://mts.intechopen.com/source/xml/66969.xml",downloadPdfUrl:"/chapter/pdf-download/66969",previewPdfUrl:"/chapter/pdf-preview/66969",totalDownloads:1623,totalViews:0,totalCrossrefCites:5,dateSubmitted:"September 25th 2018",dateReviewed:"April 3rd 2019",datePrePublished:"May 2nd 2019",datePublished:"March 11th 2020",dateFinished:"May 2nd 2019",readingETA:"0",abstract:"The drug discovery and development pipeline have more and more relied on in vitro testing and in silico predictions to reduce investments and optimize lead compounds. A comprehensive set of in vitro assays is available to determine key parameters of absorption, distribution, metabolism, and excretion, for example, lipophilicity, solubility, and plasma stability. Such test systems aid the evaluation of the pharmacological properties of a compound and serve as surrogates before entering in vivo testing and clinical trials. Nowadays, computer-aided techniques are employed not just in the discovery of new lead compounds but embedded as part of the entire drug development process where the ADME profiling and big data analyses add a new layer of complexity to those systems. Herein, we give a short overview of the history of the drug development pipeline presenting state-of-the-art ADME in vitro assays as established in academia and industry. We will further introduce the underlying good practices and give an example of the compound development pipeline. In the next step, recent advances at in silico techniques will be highlighted with special emphasis on how pharmacogenomics and in silico PK profiling can enhance drug monitoring and individualization of drug therapy.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/66969",risUrl:"/chapter/ris/66969",signatures:"Arne Krüger, Vinicius Gonçalves Maltarollo, Carsten Wrenger and Thales Kronenberger",book:{id:"7867",type:"book",title:"Drug Discovery and Development",subtitle:"New Advances",fullTitle:"Drug Discovery and Development - New Advances",slug:"drug-discovery-and-development-new-advances",publishedDate:"March 11th 2020",bookSignature:"Vishwanath Gaitonde, Partha Karmakar and Ashit Trivedi",coverURL:"https://cdn.intechopen.com/books/images_new/7867.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-78923-976-8",printIsbn:"978-1-78923-975-1",pdfIsbn:"978-1-78985-219-6",isAvailableForWebshopOrdering:!0,editors:[{id:"221897",title:"Dr.",name:"Vishwanath",middleName:null,surname:"Gaitonde",slug:"vishwanath-gaitonde",fullName:"Vishwanath Gaitonde"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"75830",title:"Prof.",name:"Carsten",middleName:null,surname:"Wrenger",fullName:"Carsten Wrenger",slug:"carsten-wrenger",email:"cwrenger@icb.usp.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Sao Paulo",institutionURL:null,country:{name:"Brazil"}}},{id:"175204",title:"Dr.",name:"Thales",middleName:null,surname:"Kronenberger",fullName:"Thales Kronenberger",slug:"thales-kronenberger",email:"kronenberger7@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"278208",title:"MSc.",name:"Arne",middleName:null,surname:"Krüger",fullName:"Arne Krüger",slug:"arne-kruger",email:"krueger.arne@icb.usp.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"278209",title:"Prof.",name:"Vinicius Gonçalves",middleName:null,surname:"Maltarollo",fullName:"Vinicius Gonçalves Maltarollo",slug:"vinicius-goncalves-maltarollo",email:"viniciusmaltarollo@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Role of computer-aided techniques in drug discovery",level:"1"},{id:"sec_3",title:"3. How specific parameters shape the pharmacology studies",level:"1"},{id:"sec_3_2",title:"3.1 Aqueous solubility and lipophilicity",level:"2"},{id:"sec_4_2",title:"3.2 Ionization state and pKa prediction",level:"2"},{id:"sec_5_2",title:"3.3 Permeability and the use of cellular and noncellular models",level:"2"},{id:"sec_7",title:"4. ADME properties: experimental approaches and in silico models",level:"1"},{id:"sec_7_2",title:"4.1 Absorption",level:"2"},{id:"sec_8_2",title:"4.2 Distribution and the role of plasma-binding proteins",level:"2"},{id:"sec_9_2",title:"4.3 Metabolism",level:"2"},{id:"sec_10_2",title:"4.4 Excretion",level:"2"},{id:"sec_12",title:"5. Biological (large) molecules",level:"1"},{id:"sec_13",title:"6. 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Corresponding authors will receive a 25% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters. A 20% discount for publishing a long-form monographs, 25% for compacts and 23% for short-form monographs.
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The University of Surrey is pledging funds via the Knowledge Unlatched program to ensure academics can publish Open Access content more easily.
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Virginia Polytechnic Institute and State University
Corresponding authors will receive a 25% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters. A 20% discount for publishing a long-form monographs, 25% for compacts and 23% for short-form monographs.
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CSIC affiliated authors can also take advantage of a central Open Access fund (amounting to 10,000 EUR) to cover up to 50% of the rest of the OAPF until it expires. Effective for chapters accepted from January 1, 2020.
Corresponding authors will receive a 25% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters. A 20% discount for publishing a long-form monographs, 25% for compacts and 23% for short-form monographs.
Corresponding authors will receive a 25% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters. A 20% discount for publishing a long-form monographs, 25% for compacts and 23% for short-form monographs.
Corresponding authors will receive a 25% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters. A 20% discount for publishing a long-form monographs, 25% for compacts and 23% for short-form monographs.
The Claremont Colleges are pledging funds via the Knowledge Unlatched program to ensure academics can publish Open Access content more easily.
\n\n
Corresponding authors will receive a 15% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters or monograph publications. To use the discount you will need to verify your institutional email address. These discounts are valid from 2020 to 2022.
The University of Massachusetts, Amherst is pledging funds via the Knowledge Unlatched program to ensure academics can publish Open Access content more easily.
\n\n
Corresponding authors will receive a 10% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters or monograph publications. To use the discount you will need to verify your institutional email address. These discounts are valid from 2020 to 2022.
The University of Surrey is pledging funds via the Knowledge Unlatched program to ensure academics can publish Open Access content more easily.
\n\n
Corresponding authors will receive a 10% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters or monograph publications. To use the discount you will need to verify your institutional email address. These discounts are valid from 2020 to 2022.
\n\n
\n\t
Virginia Polytechnic Institute and State University
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\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\t
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\r\n
\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
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\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
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\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
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\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
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\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
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In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},subseries:[{id:"22",title:"Applied Intelligence",keywords:"Machine Learning, Intelligence Algorithms, Data Science, Artificial Intelligence, Applications on Applied Intelligence",scope:"This field is the key in the current industrial revolution (Industry 4.0), where the new models and developments are based on the knowledge generation on applied intelligence. The motor of the society is the industry and the research of this topic has to be empowered in order to increase and improve the quality of our lives.",annualVolume:11418,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"13633",title:"Prof.",name:"Abdelhamid",middleName:null,surname:"Mellouk",fullName:"Abdelhamid Mellouk",profilePictureURL:"https://mts.intechopen.com/storage/users/13633/images/1567_n.jpg",institutionString:null,institution:{name:"Paris 12 Val de Marne University",institutionURL:null,country:{name:"France"}}},{id:"109268",title:"Dr.",name:"Ali",middleName:null,surname:"Al-Ataby",fullName:"Ali Al-Ataby",profilePictureURL:"https://mts.intechopen.com/storage/users/109268/images/7410_n.jpg",institutionString:null,institution:{name:"University of Liverpool",institutionURL:null,country:{name:"United Kingdom"}}},{id:"3807",title:"Dr.",name:"Carmelo",middleName:"Jose Albanez",surname:"Bastos-Filho",fullName:"Carmelo Bastos-Filho",profilePictureURL:"https://mts.intechopen.com/storage/users/3807/images/624_n.jpg",institutionString:null,institution:{name:"Universidade de Pernambuco",institutionURL:null,country:{name:"Brazil"}}},{id:"38850",title:"Dr.",name:"Efren",middleName:null,surname:"Gorrostieta Hurtado",fullName:"Efren Gorrostieta Hurtado",profilePictureURL:"https://mts.intechopen.com/storage/users/38850/images/system/38850.jpg",institutionString:null,institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},{id:"239041",title:"Prof.",name:"Yang",middleName:null,surname:"Yi",fullName:"Yang Yi",profilePictureURL:"https://mts.intechopen.com/storage/users/239041/images/system/239041.jpeg",institutionString:"Virginia Tech",institution:{name:"Virginia Tech",institutionURL:null,country:{name:"United States of America"}}}]},{id:"23",title:"Computational Neuroscience",keywords:"Single-Neuron Modeling, Sensory Processing, Motor Control, Memory and Synaptic Pasticity, Attention, Identification, Categorization, Discrimination, Learning, Development, Axonal Patterning and Guidance, Neural Architecture, Behaviours and Dynamics of Networks, Cognition and the Neuroscientific Basis of Consciousness",scope:"Computational neuroscience focuses on biologically realistic abstractions and models validated and solved through computational simulations to understand principles for the development, structure, physiology, and ability of the nervous system. This topic is dedicated to biologically plausible descriptions and computational models - at various abstraction levels - of neurons and neural systems. This includes, but is not limited to: single-neuron modeling, sensory processing, motor control, memory, and synaptic plasticity, attention, identification, categorization, discrimination, learning, development, axonal patterning, guidance, neural architecture, behaviors, and dynamics of networks, cognition and the neuroscientific basis of consciousness. Particularly interesting are models of various types of more compound functions and abilities, various and more general fundamental principles (e.g., regarding architecture, organization, learning, development, etc.) found at various spatial and temporal levels.",annualVolume:11419,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"13818",title:"Dr.",name:"Asim",middleName:null,surname:"Bhatti",fullName:"Asim Bhatti",profilePictureURL:"https://mts.intechopen.com/storage/users/13818/images/system/13818.jpg",institutionString:null,institution:{name:"Deakin University",institutionURL:null,country:{name:"Australia"}}},{id:"151889",title:"Dr.",name:"Joao Luis Garcia",middleName:null,surname:"Rosa",fullName:"Joao Luis Garcia Rosa",profilePictureURL:"https://mts.intechopen.com/storage/users/151889/images/4861_n.jpg",institutionString:null,institution:{name:"University of Sao Paulo",institutionURL:null,country:{name:"Brazil"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",fullName:"Yalcin Isler",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",institutionURL:null,country:{name:"Turkey"}}}]},{id:"24",title:"Computer Vision",keywords:"Image Analysis, Scene Understanding, Biometrics, Deep Learning, Software Implementation, Hardware Implementation, Natural Images, Medical Images, Robotics, VR/AR",scope:"The scope of this topic is to disseminate the recent advances in the rapidly growing field of computer vision from both the theoretical and practical points of view. Novel computational algorithms for image analysis, scene understanding, biometrics, deep learning and their software or hardware implementations for natural and medical images, robotics, VR/AR, applications are some research directions relevant to this topic.",annualVolume:11420,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"1177",title:"Prof.",name:"Antonio",middleName:"J. R.",surname:"Neves",fullName:"Antonio Neves",profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"220565",title:"Dr.",name:"Jucheng",middleName:null,surname:"Yang",fullName:"Jucheng Yang",profilePictureURL:"https://mts.intechopen.com/storage/users/220565/images/5988_n.jpg",institutionString:null,institution:{name:"Tianjin University of Technology",institutionURL:null,country:{name:"China"}}},{id:"29299",title:"Prof.",name:"Serestina",middleName:null,surname:"Viriri",fullName:"Serestina Viriri",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYOalQAG/Profile_Picture_1620817405517",institutionString:null,institution:{name:"University of KwaZulu-Natal",institutionURL:null,country:{name:"South Africa"}}},{id:"315933",title:"Dr.",name:"Yalın",middleName:null,surname:"Baştanlar",fullName:"Yalın Baştanlar",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002qpr7hQAA/Profile_Picture_1621430127547",institutionString:null,institution:{name:"Izmir Institute of Technology",institutionURL:null,country:{name:"Turkey"}}}]},{id:"25",title:"Evolutionary Computation",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization",scope:"Evolutionary computing is a paradigm that has grown dramatically in recent years. This group of bio-inspired metaheuristics solves multiple optimization problems by applying the metaphor of natural selection. It so far has solved problems such as resource allocation, routing, schedule planning, and engineering design. Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",annualVolume:11421,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"111683",title:"Prof.",name:"Elmer",middleName:"P.",surname:"Dadios",fullName:"Elmer Dadios",profilePictureURL:"https://mts.intechopen.com/storage/users/111683/images/system/111683.jpg",institutionString:"De La Salle University",institution:{name:"De La Salle University",institutionURL:null,country:{name:"Philippines"}}},{id:"106873",title:"Prof.",name:"Hongwei",middleName:null,surname:"Ge",fullName:"Hongwei Ge",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Dalian University of Technology",institutionURL:null,country:{name:"China"}}},{id:"171056",title:"Dr.",name:"Sotirios",middleName:null,surname:"Goudos",fullName:"Sotirios Goudos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9IuQAK/Profile_Picture_1622623673666",institutionString:null,institution:{name:"Aristotle University of Thessaloniki",institutionURL:null,country:{name:"Greece"}}},{id:"15895",title:"Assistant Prof.",name:"Takashi",middleName:null,surname:"Kuremoto",fullName:"Takashi Kuremoto",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLrqQAG/Profile_Picture_1625656196038",institutionString:null,institution:{name:"Nippon Institute of Technology",institutionURL:null,country:{name:"Japan"}}},{id:"125844",title:"Prof.",name:"Wellington",middleName:"Pinheiro Dos",surname:"Santos",fullName:"Wellington Santos",profilePictureURL:"https://mts.intechopen.com/storage/users/125844/images/4878_n.jpg",institutionString:null,institution:{name:"Federal University of Pernambuco",institutionURL:null,country:{name:"Brazil"}}}]},{id:"26",title:"Machine Learning and Data Mining",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",annualVolume:11422,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",institutionString:null,institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"43680",title:"Prof.",name:"Ciza",middleName:null,surname:"Thomas",fullName:"Ciza Thomas",profilePictureURL:"https://mts.intechopen.com/storage/users/43680/images/system/43680.jpeg",institutionString:null,institution:{name:"Government of Kerala",institutionURL:null,country:{name:"India"}}},{id:"16614",title:"Prof.",name:"Juan Ignacio",middleName:null,surname:"Guerrero Alonso",fullName:"Juan Ignacio Guerrero Alonso",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6HB8QAM/Profile_Picture_1627901127555",institutionString:null,institution:{name:"University of Seville",institutionURL:null,country:{name:"Spain"}}},{id:"3095",title:"Prof.",name:"Kenji",middleName:null,surname:"Suzuki",fullName:"Kenji Suzuki",profilePictureURL:"https://mts.intechopen.com/storage/users/3095/images/1592_n.jpg",institutionString:null,institution:{name:"University of Chicago",institutionURL:null,country:{name:"United States of America"}}},{id:"214067",title:"Dr.",name:"W. David",middleName:null,surname:"Pan",fullName:"W. David Pan",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSEI9QAO/Profile_Picture_1623656213532",institutionString:null,institution:{name:"University of Alabama in Huntsville",institutionURL:null,country:{name:"United States of America"}}},{id:"72920",title:"Prof.",name:"Yves",middleName:"Philippe",surname:"Rybarczyk",fullName:"Yves Rybarczyk",profilePictureURL:"https://mts.intechopen.com/storage/users/72920/images/system/72920.jpeg",institutionString:"Dalarna University, Faculty of Data and Information Sciences",institution:{name:"Dalarna University",institutionURL:null,country:{name:"Sweden"}}}]},{id:"27",title:"Multi-Agent Systems",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",annualVolume:11423,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"275140",title:"Dr.",name:"Dinh Hoa",middleName:null,surname:"Nguyen",fullName:"Dinh Hoa Nguyen",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRbnKQAS/Profile_Picture_1622204093453",institutionString:null,institution:{name:"Kyushu University",institutionURL:null,country:{name:"Japan"}}},{id:"20259",title:"Dr.",name:"Hongbin",middleName:null,surname:"Ma",fullName:"Hongbin Ma",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRhDJQA0/Profile_Picture_2022-05-02T08:25:21.jpg",institutionString:null,institution:{name:"Beijing Institute of Technology",institutionURL:null,country:{name:"China"}}},{id:"28640",title:"Prof.",name:"Yasushi",middleName:null,surname:"Kambayashi",fullName:"Yasushi Kambayashi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYOQxQAO/Profile_Picture_1625660525470",institutionString:null,institution:{name:"Nippon Institute of Technology",institutionURL:null,country:{name:"Japan"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/143363",hash:"",query:{},params:{id:"143363"},fullPath:"/profiles/143363",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()