Using chemical structure information to develop predictive models for in vitro toxicokinetic parameters to inform high-throughput risk-assessment
- 26 September 2020
- journal article
- Published by Elsevier BV in Computational Toxicology
- Vol. 16, 100136
- https://doi.org/10.1016/j.comtox.2020.100136
Abstract
No abstract availableKeywords
Funding Information
- ORISE (US EPA)
- DOE
This publication has 65 references indexed in Scilit:
- Use of category approaches, read-across and (Q)SAR: General considerationsRegulatory Toxicology and Pharmacology, 2013
- Incorporating New Technologies Into Toxicity Testing and Risk Assessment: Moving From 21st Century Vision to a Data-Driven FrameworkToxicological Sciences, 2013
- The Use of Pseudo-Equilibrium Constant Affords Improved QSAR Models of Human Plasma Protein BindingPharmaceutical Research, 2013
- Prediction of the human oral bioavailability by using in vitro and in silico drug related parameters in a physiologically based absorption modelInternational Journal of Pharmaceutics, 2012
- Paradigm Shift in Toxicity Testing and ModelingThe AAPS Journal, 2012
- Screening of chemicals for human bioaccumulative potential with a physiologically based toxicokinetic modelArchives of Toxicology, 2011
- Transforming Environmental Health ProtectionScience, 2008
- EVALUATION OF FRESH AND CRYOPRESERVED HEPATOCYTES AS IN VITRO DRUG METABOLISM TOOLS FOR THE PREDICTION OF METABOLIC CLEARANCEDrug Metabolism and Disposition, 2004
- The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo- and BioinformaticsJournal of Chemical Information and Computer Sciences, 2003
- Support-vector networksMachine Learning, 1995