Designing QSARs for Parameters of High-Throughput Toxicokinetic Models Using Open-Source Descriptors
Daniel E. Dawson, Brandall Ingle, Katherine A. Phillips, John W. Nichols, John F. Wambaugh, Rogelio Tornero‐Velez · Environmental Science & Technology · 2021
The intrinsic metabolic clearance rate (Cl int ) and the fraction of the chemical unbound in plasma ( f up ) serve as important parameters for high-throughput toxicokinetic (TK) models, but experimental data are limited for many chemicals. Open-source quantitative structure–activity relationship (QSAR) models for both parameters were developed to offer reliable in silico predictions for a diverse set of chemicals regulated under the U.S. law, including pharmaceuticals, pesticides, and industrial chemicals. As a case study to demonstrate their utility, model predictions served as inputs to the TK component of a risk-based prioritization approach based on bioactivity/exposure ratios (BERs), in which a BER 1 using either in silico or in vitro parameters (767/848, 90.4%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured in vitro TK data are lacking.