Quantitative in vitro to in vivo extrapolation of tissues toxicity. Issue 1 (25th December 2015)

• Record Type: Journal Article
• Authors: Hamon, Jérémy; Renner, Maria; Jamei, Masoud; Lukas, Arno; Kopp-Schneider, Annette; Bois, Frédéric Y.
• Is Part Of: Toxicology in vitro. Volume 30:Issue 1 Part A (2015)
• Page Start: 203
• Page End: 216
• Publication Date: 2015-12-25
• Subjects: ADME absorption, distribution, metabolism, and excretion -- ARE antioxidant responses elements -- BBB blood brain barrier -- CsA cyclosporine A -- CYP cytochrome P450 -- EPA Environmental Protection Agency -- GCL glutamate cysteine ligase -- GCLC glutamate cysteine ligase catalytic subunit -- GCLM glutamate cysteine ligase modifier subunit -- GPx glutathione peroxidase -- GS glutathione synthetase -- GSH glutathione -- GSSG glutathione disulfide -- IPSC induced pluripotent stem cell -- Keap1 Kelch-like ECH-associated protein 1 -- LDH lactate deshydrogenase -- MATE multi-antimicrobial extrusion protein -- MCMC Markov chain Monte Carlo -- MTX metabolomic data -- MRP multidrug resistance protein -- Nrf2 nuclear factor (erythroid-derived 2)-like 2 -- OCT organic cation transporter -- PBPK physiologically based pharmacokinetic -- PD pharmacodynamics -- PK pharmacokinetics -- PTX proteomic data -- QIVIVE quantitative in vitro to in vivo extrapolation -- ROS reactive oxygen species -- RPTEC renal proximal tubular epithelial cells -- TCX transcriptomic data; Bioinformatics -- Biomarkers -- Dose–response modeling -- Physiologically based models -- Systems biology; Toxicity testing -- In vitro -- Periodicals; Toxicology -- Periodicals; 615.9
• DOI: 10.1016/j.tiv.2015.01.011
• Languages: English
• ISSNs: 0887-2333

Abstract

Highlights: We develop several mechanistic dose–response models. We insist on the development of systems biology models for predictive toxicology. We couple a systems biology model with a PBPK model. Understanding in vitro pharmacokinetics is therefore a key step in QIVIVE. We develop tools to predict the variability of drug effects across human individuals. 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.