Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5861310 | Toxicology in Vitro | 2015 | 14 Pages |
Abstract
Predicting repeated-dosing in vivo drug toxicity from in vitro testing and omics data gathering requires significant support in bioinformatics, mathematical modeling and statistics. We present here the major aspects of the work devoted within the framework of the European integrated Predict-IV to pharmacokinetic modeling of in vitro experiments, physiologically based pharmacokinetic (PBPK) modeling, mechanistic models of toxicity for the kidney and brain, large scale dose-response analyses methods and biomarker discovery tools. All of those methods have been applied to various extent to the drug datasets developed by the project's partners. Our approach is rather generic and could be adapted to other drugs or drug candidates. It marks a successful integration of the work of the different teams toward a common goal of predictive quantitative in vitro to in vivo extrapolation.
Keywords
GCLMGPXGSSGGCLMRPIPSCPTXMTXGCLCPBPKQIVIVEPhysiologically based modelsRenal proximal tubular epithelial cellsMCMCTCXRPTECDose–response modelingCyPGSHEPAADMENrf2keap1ROSEnvironmental Protection AgencyOctCSABioinformaticsabsorption, distribution, metabolism, and excretionorganic cation transporterMateMarkov chain Monte CarloSystems biologyblood brain barrierBBBInduced pluripotent stem cellCytochrome P450Cyclosporine APharmacodynamicsPharmacokineticsPhysiologically based pharmacokineticnuclear factor (erythroid-derived 2)-like 2Lactate deshydrogenaseLDHglutamate cysteine ligaseBiomarkersAREKelch-like ECH-associated protein 1multidrug resistance proteinglutamate cysteine ligase modifier subunitGlutamate cysteine ligase catalytic subunitGlutathioneglutathione disulfideglutathione synthetaseglutathione peroxidaseReactive oxygen species
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Authors
Jérémy Hamon, Maria Renner, Masoud Jamei, Arno Lukas, Annette Kopp-Schneider, Frédéric Y. Bois,