Designing QSARs for Parameters of High Throughput Toxicokinetic Models Using Open-Source Descriptors (vol 55, pg 6505, 2021)

The intrinsic metabolic clearance rate (Cl-int) and fraction of chemical unbound in plasma (f(up)) serve as important parameters for high throughput toxicokinetic 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 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 (BER), in which a BER < 1 indicates exposures are predicted to exceed a biological activity threshold. When applied to a subset of the Tox21 screening library (6631 chemicals) we found that the proportion of chemicals with BER < 1 was similar using either in silico (1337/6631; 20.16%) or in vitro (151/850; 17.76%) parameters. Further, when considering only the chemicals in the Tox21 set with in vitro data, there was a high concordance of chemicals classified with either BER < 1 or >1 using either in silico or in vitro parameters (776/850, 91.30%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured in vitro TK data are lacking.