Quantitative in Vitro to in Vivo Extrapolation of Tissues Toxicity
Overview
Affiliations
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.
Advancing Toxicity Predictions: A Review on to Extrapolation in Next-Generation Risk Assessment.
Han P, Li X, Yang J, Zhang Y, Chen J Environ Health (Wash). 2024; 2(7):499-513.
PMID: 39473885 PMC: 11504544. DOI: 10.1021/envhealth.4c00043.
Unmasking the Metabolite Signature of Bladder Cancer: A Systematic Review.
Pereira F, Domingues M, Vitorino R, Guerra I, Santos L, Ferreira J Int J Mol Sci. 2024; 25(6).
PMID: 38542319 PMC: 10970247. DOI: 10.3390/ijms25063347.
IVIVE: Facilitating the Use of Toxicity Data in Risk Assessment and Decision Making.
Chang X, Tan Y, Allen D, Bell S, Brown P, Browning L Toxics. 2022; 10(5).
PMID: 35622645 PMC: 9143724. DOI: 10.3390/toxics10050232.
Chen Y, Tang D, Wu H, Wu Y, Yuan T, Zhang H Arch Toxicol. 2021; 95(7):2431-2442.
PMID: 33852043 DOI: 10.1007/s00204-021-03050-y.
A model-based assay design to reproduce in vivo patterns of acute drug-induced toxicity.
Kuepfer L, Clayton O, Thiel C, Cordes H, Nudischer R, Blank L Arch Toxicol. 2017; 92(1):553-555.
PMID: 28852801 PMC: 5773653. DOI: 10.1007/s00204-017-2041-7.