In silico clinical trials: concepts and early adoptions
Abstract Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simul...
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Published in | Briefings in bioinformatics Vol. 20; no. 5; pp. 1699 - 1708 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
England
Oxford University Press
27.09.2019
Oxford Publishing Limited (England) |
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Online Access | Get full text |
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Abstract | Abstract
Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term ‘in silico clinical trials’ refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach. |
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AbstractList | Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term 'in silico clinical trials' refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach.Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term 'in silico clinical trials' refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach. Abstract Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term ‘in silico clinical trials’ refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach. Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term 'in silico clinical trials' refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach. |
Author | Russo, Giulia Viceconti, Marco Tshinanu, Flora Musuamba Pappalardo, Francesco |
Author_xml | – sequence: 1 givenname: Francesco surname: Pappalardo fullname: Pappalardo, Francesco organization: Department of Drug Sciences, University of Catania, Catania, Italy – sequence: 2 givenname: Giulia surname: Russo fullname: Russo, Giulia organization: Department of Biomedical and Biotechnological Sciences, University of Catania, Catania 95123, Italy – sequence: 3 givenname: Flora Musuamba surname: Tshinanu fullname: Tshinanu, Flora Musuamba organization: Federal Agency for Medicines and Health Products, Brussels, Belgium and INSERM U1248, Université de Limoges, Limoges, France – sequence: 4 givenname: Marco surname: Viceconti fullname: Viceconti, Marco email: m.viceconti@sheffield.ac.uk organization: Department of Mechanical Engineering, University of Sheffield, Sheffield, UK and INSIGNEO Institute for In Silico Medicine, University of Sheffield, Sheffield, UK |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29868882$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.1113/jphysiol.1965.sp007745 10.1186/s12868-017-0394-8 10.1016/j.jmbbm.2008.02.005 10.1371/journal.pone.0111946 10.1136/heartjnl-2015-308044 10.1197/jamia.M1637 10.1146/annurev-bioeng-110915-114742 10.1038/s41598-018-20737-y 10.1006/taap.1994.1068 10.1126/science.1062117 10.2174/1574888X10666151001115942 10.1177/1535370217740853 10.1038/clpt.2012.236 10.1016/j.jtbi.2014.04.013 10.1016/j.humimm.2015.11.012 10.1002/0470857897.ch17 10.1152/ajpheart.01151.2011 10.1161/CIRCGENETICS.117.001804 10.1016/j.ress.2013.11.005 10.1007/978-1-4939-1115-8_19 10.1002/j.1552-4604.1994.tb02025.x 10.1152/jappl.1961.16.5.911 10.1016/j.cmpb.2005.04.005 10.1093/bioinformatics/btv172 10.1109/TCBB.2017.2733529 10.1007/978-1-4615-5959-7_28 10.1186/s12859-016-1361-6 10.1186/1471-2105-14-S6-S11 10.1056/NEJMra1512592 10.2174/138161209789105162 10.1007/s00198-016-3597-4 10.1007/BF01060893 10.1002/tera.1420490205 10.1007/978-1-60327-118-9_11 10.1080/10543406.2017.1300907 10.3389/fphys.2017.00668 10.1093/bioinformatics/btw293 10.1093/brain/awx288 10.1016/j.apsb.2016.04.004 10.1080/17425255.2017.1389897 10.1038/35074122 10.1114/1.112 10.1186/1472-6947-12-129 10.1016/S0264-410X(00)00554-5 10.1039/c0ib00092b 10.1126/science.1069492 10.1002/ddr.20415 10.1126/scitranslmed.aaa3636 10.1016/j.jbiomech.2014.12.019 10.1016/j.jocs.2010.09.002 10.1186/1471-2105-7-482 10.1186/1471-2105-6-132 10.1002/1097-0142(197707)40:1+<519::AID-CNCR2820400718>3.0.CO;2-4 10.1016/j.coi.2016.01.002 10.1371/journal.pcbi.1005724 10.1016/j.phrs.2014.08.006 10.1021/acs.jmedchem.5b01684 10.1016/j.jim.2011.11.009 10.2170/physiolsci.RP009908 10.1007/s11095-015-1699-x 10.1016/j.biotechadv.2009.10.001 10.1371/journal.pcbi.0020129 10.1038/bonekey.2015.31 10.1155/2014/902545 10.1177/0954411917702931 10.1146/annurev.genom.2.1.343 10.1258/ebm.2009.009230 10.1371/journal.pcbi.1002742 10.1016/j.jmbbm.2017.07.034 10.1016/S1359-6446(03)02600-X |
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Copyright | The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com 2018 The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com. The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com |
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References | Morris (2020080807562744800_bby043-B40) 2016; 102 Hunter (2020080807562744800_bby043-B12) 2002; 247 Swinney (2020080807562744800_bby043-B53) 2013; 93 Taylor (2020080807562744800_bby043-B42) 2015; 48 Pappalardo (2020080807562744800_bby043-B58) 2010; 28 Pennisi (2020080807562744800_bby043-B33) 2016; 17 Lemon (2020080807562744800_bby043-B41) 2016; 11 Singh (2020080807562744800_bby043-B64) 2016; 77 Viceconti (2020080807562744800_bby043-B18) 2016; 18 Peleg (2020080807562744800_bby043-B29) 2004; 12 Brown (2020080807562744800_bby043-B59) 2015; 7 Peters (2020080807562744800_bby043-B65) 2005; 6 ASME (2020080807562744800_bby043-B74) 2017 Kumar (2020080807562744800_bby043-B44) 2017; 18 Qasim (2020080807562744800_bby043-B37) 2016; 27 Castiglione (2020080807562744800_bby043-B73) 2014; 2014 Gullo (2020080807562744800_bby043-B26) 2015; 31 Bassingthwaighte (2020080807562744800_bby043-B10) 1997; 430 Nichol (2020080807562744800_bby043-B3) 1977; 40 Srinivasan (2020080807562744800_bby043-B9) 1994; 34 Sackmann (2020080807562744800_bby043-B31) 2006; 7 Grant (2020080807562744800_bby043-B22) 2006; 2 Yonucu (2020080807562744800_bby043-B28) 2017; 13 Cordero (2020080807562744800_bby043-B30) 2013; 14 Janes (2020080807562744800_bby043-B2) 1965; 181 Yenkie (2020080807562744800_bby043-B57) 2014; 355 Viceconti (2020080807562744800_bby043-B70) 2009; 2 Viceconti (2020080807562744800_bby043-B19) 2016 Desai (2020080807562744800_bby043-B62) 2014; 1184 Tang (2020080807562744800_bby043-B23) 2011; 3 Viceconti (2020080807562744800_bby043-B49) 2017; 231 Rappuoli (2020080807562744800_bby043-B67) 2001; 19 Stoll (2020080807562744800_bby043-B14) 2001; 294 Pappalardo (2020080807562744800_bby043-B68) 2015; 92 Finn (2020080807562744800_bby043-B56) 2016; 39 Kitano (2020080807562744800_bby043-B15) 2002; 295 Lafuente (2020080807562744800_bby043-B63) 2009; 15 Faris (2020080807562744800_bby043-B52) 2017; 376 Teutonico (2020080807562744800_bby043-B60) 2015; 32 Byczkowski (2020080807562744800_bby043-B8) 1994; 125 Zhuang (2020080807562744800_bby043-B39) 2016; 6 Alemani (2020080807562744800_bby043-B71) 2012; 376 De Vivo (2020080807562744800_bby043-B38) 2016; 59 Ravvaz (2020080807562744800_bby043-B46) 2017; 10 Lindbom (2020080807562744800_bby043-B5) 2005; 79 Rejniak (2020080807562744800_bby043-B27) 2010; 235 Popel (2020080807562744800_bby043-B11) 1998; 26 Calonaci (2020080807562744800_bby043-B20) 2012; 12 Stracuzzi (2020080807562744800_bby043-B75) 2017 Pappalardo (2020080807562744800_bby043-B25) 2016; 32 Kim (2020080807562744800_bby043-B24) 2012; 8 Davidov (2020080807562744800_bby043-B16) 2003; 8 Xu (2020080807562744800_bby043-B35) 2018; 141 Shankaran (2020080807562744800_bby043-B61) 2001; 410 Church (2020080807562744800_bby043-B45) 2018; 243 Alqahtani (2020080807562744800_bby043-B43) 2017; 13 Haddad (2020080807562744800_bby043-B50) 2017; 27 Reche (2020080807562744800_bby043-B66) 2007; 409 Haddad (2020080807562744800_bby043-B51) 2014; 123 Caiazzo (2020080807562744800_bby043-B72) 2011; 2 Cogan (2020080807562744800_bby043-B4) 1984; 247 Carusi (2020080807562744800_bby043-B69) 2012; 303 Ideker (2020080807562744800_bby043-B13) 2001; 2 Sheiner (2020080807562744800_bby043-B6) 1981; 9 Luecke (2020080807562744800_bby043-B7) 1994; 49 Viceconti (2020080807562744800_bby043-B17) 2008; 58 Andreoni (2020080807562744800_bby043-B54) 2014; 9 Lu (2020080807562744800_bby043-B48) 2017; 75 Russo (2020080807562744800_bby043-B21) 2018 Nyman (2020080807562744800_bby043-B36) 2015; 4 Zevedei-Oancea (2020080807562744800_bby043-B32) 2003; 3 Carlier (2020080807562744800_bby043-B34) 2018; 8 Passini (2020080807562744800_bby043-B47) 2017; 8 An (2020080807562744800_bby043-B55) 2011; 72 Silverman (2020080807562744800_bby043-B1) 1961; 16 |
References_xml | – volume: 181 start-page: 59 issue: 1 year: 1965 ident: 2020080807562744800_bby043-B2 article-title: The analysis of glucose measurements by computer simulation publication-title: J Physiol doi: 10.1113/jphysiol.1965.sp007745 – volume: 18 start-page: 76. issue: 1 year: 2017 ident: 2020080807562744800_bby043-B44 article-title: In silico repurposing of antipsychotic drugs for Alzheimer's disease publication-title: BMC Neurosci doi: 10.1186/s12868-017-0394-8 – volume: 2 start-page: 120 issue: 1 year: 2009 ident: 2020080807562744800_bby043-B70 article-title: Pre-clinical validation of joint prostheses: a systematic approach publication-title: J Mech Behav Biomed Mater doi: 10.1016/j.jmbbm.2008.02.005 – volume: 9 start-page: e111946 issue: 12 year: 2014 ident: 2020080807562744800_bby043-B54 article-title: In silico models for dynamic connected cell cultures mimicking hepatocyte-endothelial cell-adipocyte interaction circle publication-title: PLoS One doi: 10.1371/journal.pone.0111946 – volume: 102 start-page: 18 issue: 1 year: 2016 ident: 2020080807562744800_bby043-B40 article-title: Computational fluid dynamics modelling in cardiovascular medicine publication-title: Heart doi: 10.1136/heartjnl-2015-308044 – volume: 12 start-page: 181 issue: 2 year: 2004 ident: 2020080807562744800_bby043-B29 article-title: Using Petri Net tools to study properties and dynamics of biological systems publication-title: J Am Med Inform Assoc doi: 10.1197/jamia.M1637 – volume: 18 start-page: 103 issue: 1 year: 2016 ident: 2020080807562744800_bby043-B18 article-title: The virtual physiological human: ten years after publication-title: Annu Rev Biomed Eng doi: 10.1146/annurev-bioeng-110915-114742 – volume: 8 start-page: 2465 issue: 1 year: 2018 ident: 2020080807562744800_bby043-B34 article-title: In silico clinical trials for pediatric orphan diseases publication-title: Sci Rep doi: 10.1038/s41598-018-20737-y – volume: 125 start-page: 228 issue: 2 year: 1994 ident: 2020080807562744800_bby043-B8 article-title: Computer simulation of the lactational transfer of tetrachloroethylene in rats using a physiologically based model publication-title: Toxicol Appl Pharmacol doi: 10.1006/taap.1994.1068 – volume: 294 start-page: 1723 issue: 5547 year: 2001 ident: 2020080807562744800_bby043-B14 article-title: A genomic-systems biology map for cardiovascular function publication-title: Science doi: 10.1126/science.1062117 – volume: 11 start-page: 666 issue: 8 year: 2016 ident: 2020080807562744800_bby043-B41 article-title: The use of mathematical modelling for improving the tissue engineering of organs and stem cell therapy publication-title: Curr Stem Cell Res Ther doi: 10.2174/1574888X10666151001115942 – volume: 243 start-page: 300 year: 2018 ident: 2020080807562744800_bby043-B45 article-title: In silico modeling to optimize interpretation of liver safety biomarkers in clinical trials publication-title: Exp Biol Med doi: 10.1177/1535370217740853 – volume: 93 start-page: 299 issue: 4 year: 2013 ident: 2020080807562744800_bby043-B53 article-title: Phenotypic vs. target-based drug discovery for first-in-class medicines publication-title: Clin Pharmacol Ther doi: 10.1038/clpt.2012.236 – volume: 355 start-page: 219 year: 2014 ident: 2020080807562744800_bby043-B57 article-title: Optimal control for predicting customized drug dosage for superovulation stage of in vitro fertilization publication-title: J Theor Biol doi: 10.1016/j.jtbi.2014.04.013 – volume: 77 start-page: 295 issue: 3 year: 2016 ident: 2020080807562744800_bby043-B64 article-title: Major histocompatibility complex linked databases and prediction tools for designing vaccines publication-title: Hum Immunol doi: 10.1016/j.humimm.2015.11.012 – volume-title: In Silico Clinical Trials: How Computer Simulation Will Transform the Biomedical Industry year: 2016 ident: 2020080807562744800_bby043-B19 – year: 2017 ident: 2020080807562744800_bby043-B74 – volume: 247 start-page: 207 year: 2002 ident: 2020080807562744800_bby043-B12 article-title: The IUPS physiome project. International union of physiological sciences publication-title: Novartis Found Symp doi: 10.1002/0470857897.ch17 – volume: 303 start-page: H144 issue: 2 year: 2012 ident: 2020080807562744800_bby043-B69 article-title: Bridging experiments, models and simulations: an integrative approach to validation in computational cardiac electrophysiology publication-title: Am J Physiol Heart Circ Physiol doi: 10.1152/ajpheart.01151.2011 – volume: 10 start-page: e001804 issue: 6 year: 2017 ident: 2020080807562744800_bby043-B46 article-title: Personalized anticoagulation: optimizing Warfarin management using genetics and simulated clinical trials publication-title: Circ Cardiovasc Genet doi: 10.1161/CIRCGENETICS.117.001804 – volume: 123 start-page: 145 year: 2014 ident: 2020080807562744800_bby043-B51 article-title: Fracture prediction of cardiac lead medical devices using Bayesian networks publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2013.11.005 – volume: 1184 start-page: 333 year: 2014 ident: 2020080807562744800_bby043-B62 article-title: T-cell epitope prediction methods: an overview publication-title: Methods Mol Biol doi: 10.1007/978-1-4939-1115-8_19 – volume: 34 start-page: 692 issue: 6 year: 1994 ident: 2020080807562744800_bby043-B9 article-title: Application of physiologically based pharmacokinetic models for assessing drug disposition in space publication-title: J Clin Pharmacol doi: 10.1002/j.1552-4604.1994.tb02025.x – volume: 16 start-page: 911 year: 1961 ident: 2020080807562744800_bby043-B1 article-title: Application of analogue computer to measurement of intestinal absorption rates with tracers publication-title: J Appl Physiol doi: 10.1152/jappl.1961.16.5.911 – volume: 79 start-page: 241 issue: 3 year: 2005 ident: 2020080807562744800_bby043-B5 article-title: PsN-Toolkit–a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM publication-title: Comput Methods Programs Biomed doi: 10.1016/j.cmpb.2005.04.005 – volume: 31 start-page: 2514 issue: 15 year: 2015 ident: 2020080807562744800_bby043-B26 article-title: Computational modeling of the expansion of human cord blood CD133+ hematopoietic stem/progenitor cells with different cytokine combinations publication-title: Bioinformatics doi: 10.1093/bioinformatics/btv172 – year: 2018 ident: 2020080807562744800_bby043-B21 article-title: Continuous Petri Nets and microRNA analysis in melanoma publication-title: IEEE/ACM Transactions of Computational Biology and Bioinformatics doi: 10.1109/TCBB.2017.2733529 – volume: 430 start-page: 325 year: 1997 ident: 2020080807562744800_bby043-B10 article-title: Design and strategy for the Cardionome Project publication-title: Adv Exp Med Biol doi: 10.1007/978-1-4615-5959-7_28 – volume: 17 start-page: 498 issue: S19 year: 2016 ident: 2020080807562744800_bby043-B33 article-title: A methodological approach for using high-level Petri Nets to model the immune system response publication-title: BMC Bioinformatics doi: 10.1186/s12859-016-1361-6 – volume: 14 start-page: S11. issue: Suppl 6 year: 2013 ident: 2020080807562744800_bby043-B30 article-title: Multi-level model for the investigation of oncoantigen-driven vaccination effect publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-14-S6-S11 – volume: 376 start-page: 1350 issue: 14 year: 2017 ident: 2020080807562744800_bby043-B52 article-title: An FDA viewpoint on unique considerations for medical-device clinical trials publication-title: N Engl J Med doi: 10.1056/NEJMra1512592 – volume: 15 start-page: 3209 issue: 28 year: 2009 ident: 2020080807562744800_bby043-B63 article-title: Prediction of MHC-peptide binding: a systematic and comprehensive overview publication-title: Curr Pharm Des doi: 10.2174/138161209789105162 – volume: 27 start-page: 2815 issue: 9 year: 2016 ident: 2020080807562744800_bby043-B37 article-title: Patient-specific finite element estimated femur strength as a predictor of the risk of hip fracture: the effect of methodological determinants publication-title: Osteoporos Int doi: 10.1007/s00198-016-3597-4 – volume: 9 start-page: 503 issue: 4 year: 1981 ident: 2020080807562744800_bby043-B6 article-title: Some suggestions for measuring predictive performance publication-title: J Pharmacokinet Biopharm doi: 10.1007/BF01060893 – volume: 49 start-page: 90 issue: 2 year: 1994 ident: 2020080807562744800_bby043-B7 article-title: A physiologically based pharmacokinetic computer model for human pregnancy publication-title: Teratology doi: 10.1002/tera.1420490205 – volume: 409 start-page: 163 year: 2007 ident: 2020080807562744800_bby043-B66 article-title: Definition of MHC supertypes through clustering of MHC peptide-binding repertoires publication-title: Methods Mol Biol doi: 10.1007/978-1-60327-118-9_11 – volume: 27 start-page: 1089 issue: 6 year: 2017 ident: 2020080807562744800_bby043-B50 article-title: Incorporation of stochastic engineering models as prior information in Bayesian medical device trials publication-title: J Biopharm Stat doi: 10.1080/10543406.2017.1300907 – volume: 247 start-page: F387 issue: 3 Pt 2 year: 1984 ident: 2020080807562744800_bby043-B4 article-title: Regulation of proximal bicarbonate reabsorption publication-title: Am J Physiol – volume: 8 start-page: 668. year: 2017 ident: 2020080807562744800_bby043-B47 article-title: Human in silico drug trials demonstrate higher accuracy than animal models in predicting clinical pro-arrhythmic cardiotoxicity publication-title: Front Physiol doi: 10.3389/fphys.2017.00668 – volume: 32 start-page: 2672 issue: 17 year: 2016 ident: 2020080807562744800_bby043-B25 article-title: A computational model to predict the immune system activation by citrus-derived vaccine adjuvants publication-title: Bioinformatics doi: 10.1093/bioinformatics/btw293 – volume: 141 start-page: 48 issue: 1 year: 2018 ident: 2020080807562744800_bby043-B35 article-title: High-dimensional therapeutic inference in the focally damaged human brain publication-title: Brain doi: 10.1093/brain/awx288 – year: 2017 ident: 2020080807562744800_bby043-B75 – volume: 6 start-page: 430 issue: 5 year: 2016 ident: 2020080807562744800_bby043-B39 article-title: PBPK modeling and simulation in drug research and development publication-title: Acta Pharm Sin B doi: 10.1016/j.apsb.2016.04.004 – volume: 13 start-page: 1147 issue: 11 year: 2017 ident: 2020080807562744800_bby043-B43 article-title: In silico ADME-Tox modeling: progress and prospects publication-title: Expert Opin Drug Metab Toxicol doi: 10.1080/17425255.2017.1389897 – volume: 410 start-page: 1107 issue: 6832 year: 2001 ident: 2020080807562744800_bby043-B61 article-title: IFNgamma and lymphocytes prevent primary tumour development and shape tumour immunogenicity publication-title: Nature doi: 10.1038/35074122 – volume: 26 start-page: 911 issue: 6 year: 1998 ident: 2020080807562744800_bby043-B11 article-title: The microcirculation physiome project publication-title: Ann Biomed Eng doi: 10.1114/1.112 – volume: 12 start-page: 129. issue: 1 year: 2012 ident: 2020080807562744800_bby043-B20 article-title: Optimal vaccination schedule search using genetic algorithm over MPI technology publication-title: BMC Med Inform Decis Mak doi: 10.1186/1472-6947-12-129 – volume: 19 start-page: 2688 issue: 17–19 year: 2001 ident: 2020080807562744800_bby043-B67 article-title: Reverse vaccinology, a genome-based approach to vaccine development publication-title: Vaccine doi: 10.1016/S0264-410X(00)00554-5 – volume: 3 start-page: 408 issue: 4 year: 2011 ident: 2020080807562744800_bby043-B23 article-title: Phenotypic transition maps of 3D breast acini obtained by imaging-guided agent-based modeling publication-title: Integr Biol doi: 10.1039/c0ib00092b – volume: 295 start-page: 1662 issue: 5560 year: 2002 ident: 2020080807562744800_bby043-B15 article-title: Systems biology: a brief overview publication-title: Science doi: 10.1126/science.1069492 – volume: 72 start-page: 187 issue: 2 year: 2011 ident: 2020080807562744800_bby043-B55 article-title: In silico augmentation of the drug development pipeline: examples from the study of Acute Inflammation publication-title: Drug Dev Res doi: 10.1002/ddr.20415 – volume: 7 start-page: 285ra61 issue: 285 year: 2015 ident: 2020080807562744800_bby043-B59 article-title: Trauma in silico: individual-specific mathematical models and virtual clinical populations publication-title: Sci Transl Med doi: 10.1126/scitranslmed.aaa3636 – volume: 48 start-page: 767 issue: 5 year: 2015 ident: 2020080807562744800_bby043-B42 article-title: Four decades of finite element analysis of orthopaedic devices: where are we now and what are the opportunities? publication-title: J Biomech doi: 10.1016/j.jbiomech.2014.12.019 – volume: 2 start-page: 9 issue: 1 year: 2011 ident: 2020080807562744800_bby043-B72 article-title: A complex automata approach for in-stent restenosis: two-dimensional multiscale modelling and simulations publication-title: J Comput Sci doi: 10.1016/j.jocs.2010.09.002 – volume: 7 start-page: 482. year: 2006 ident: 2020080807562744800_bby043-B31 article-title: Application of Petri net based analysis techniques to signal transduction pathways publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-7-482 – volume: 6 start-page: 132 year: 2005 ident: 2020080807562744800_bby043-B65 article-title: Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-6-132 – volume: 40 start-page: 519 issue: 1 Suppl year: 1977 ident: 2020080807562744800_bby043-B3 article-title: Pharmacokinetics: selectivity of action related to physicochemical properties and kinetic patterns of anticancer drugs publication-title: Cancer doi: 10.1002/1097-0142(197707)40:1+<519::AID-CNCR2820400718>3.0.CO;2-4 – volume: 39 start-page: 52 year: 2016 ident: 2020080807562744800_bby043-B56 article-title: Cancer immunoprevention publication-title: Curr Opin Immunol doi: 10.1016/j.coi.2016.01.002 – volume: 3 start-page: 323 year: 2003 ident: 2020080807562744800_bby043-B32 article-title: Topological analysis of metabolic networks based on Petri net theory publication-title: In Silico Biol – volume: 13 start-page: e1005724 issue: 9 year: 2017 ident: 2020080807562744800_bby043-B28 article-title: Quantifying the effects of antiangiogenic and chemotherapy drug combinations on drug delivery and treatment efficacy publication-title: PLoS Comput Biol doi: 10.1371/journal.pcbi.1005724 – volume: 92 start-page: 40 year: 2015 ident: 2020080807562744800_bby043-B68 article-title: Computational modelling approaches to vaccinology publication-title: Pharmacol Res doi: 10.1016/j.phrs.2014.08.006 – volume: 59 start-page: 4035 issue: 9 year: 2016 ident: 2020080807562744800_bby043-B38 article-title: Role of molecular dynamics and related methods in drug discovery publication-title: J Med Chem doi: 10.1021/acs.jmedchem.5b01684 – volume: 376 start-page: 55 issue: 1-2 year: 2012 ident: 2020080807562744800_bby043-B71 article-title: Combining cellular automata and Lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition publication-title: J Immunol Methods doi: 10.1016/j.jim.2011.11.009 – volume: 58 start-page: 441 issue: 7 year: 2008 ident: 2020080807562744800_bby043-B17 article-title: The virtual physiological human—a European initiative for in silico human modelling publication-title: J Physiol Sci doi: 10.2170/physiolsci.RP009908 – volume: 32 start-page: 3228 issue: 10 year: 2015 ident: 2020080807562744800_bby043-B60 article-title: Generating virtual patients by multivariate and discrete re-sampling techniques publication-title: Pharm Res doi: 10.1007/s11095-015-1699-x – volume: 28 start-page: 82 issue: 1 year: 2010 ident: 2020080807562744800_bby043-B58 article-title: Vaccine protocols optimization: in silico experiences publication-title: Biotechnol Adv doi: 10.1016/j.biotechadv.2009.10.001 – volume: 2 start-page: e129 issue: 10 year: 2006 ident: 2020080807562744800_bby043-B22 article-title: Simulating properties of in vitro epithelial cell morphogenesis publication-title: PLoS Comput Biol doi: 10.1371/journal.pcbi.0020129 – volume: 4 start-page: 664. year: 2015 ident: 2020080807562744800_bby043-B36 article-title: Predicting mouse vertebra strength with micro-computed tomography-derived finite element analysis publication-title: Bonekey Rep doi: 10.1038/bonekey.2015.31 – volume: 2014 start-page: 1 year: 2014 ident: 2020080807562744800_bby043-B73 article-title: Modeling biology spanning different scales: an open challenge publication-title: Biomed Res Int doi: 10.1155/2014/902545 – volume: 231 start-page: 455 issue: 5 year: 2017 ident: 2020080807562744800_bby043-B49 article-title: In silico assessment of biomedical products: the conundrum of rare but not so rare events in two case studies publication-title: Proc Inst Mech Eng H doi: 10.1177/0954411917702931 – volume: 2 start-page: 343 year: 2001 ident: 2020080807562744800_bby043-B13 article-title: A new approach to decoding life: systems biology publication-title: Annu Rev Genomics Hum Genet doi: 10.1146/annurev.genom.2.1.343 – volume: 235 start-page: 411 issue: 4 year: 2010 ident: 2020080807562744800_bby043-B27 article-title: Current trends in mathematical modeling of tumor-microenvironment interactions: a survey of tools and applications publication-title: Exp Biol Med doi: 10.1258/ebm.2009.009230 – volume: 8 start-page: e1002742. issue: 10 year: 2012 ident: 2020080807562744800_bby043-B24 article-title: Modeling protective anti-tumor immunity via preventative cancer vaccines using a hybrid agent-based and delay differential equation approach publication-title: PLoS Comput Biol doi: 10.1371/journal.pcbi.1002742 – volume: 75 start-page: 244 year: 2017 ident: 2020080807562744800_bby043-B48 article-title: Longitudinal effects of Parathyroid Hormone treatment on morphological, densitometric and mechanical properties of mouse tibia publication-title: J Mech Behav Biomed Mater doi: 10.1016/j.jmbbm.2017.07.034 – volume: 8 start-page: 175 issue: 4 year: 2003 ident: 2020080807562744800_bby043-B16 article-title: Advancing drug discovery through systems biology publication-title: Drug Discov Today doi: 10.1016/S1359-6446(03)02600-X |
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Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is... Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow... |
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Title | In silico clinical trials: concepts and early adoptions |
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