Designing QSARs for Parameters of High-Throughput Toxicokinetic Models Using Open-Source Descriptors
| Autor: | Brandall Ingle, John F. Wambaugh, Daniel E. Dawson, Katherine Phillips, Rogelio Tornero-Velez, John W. Nichols |
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| Rok vydání: | 2021 |
| Předmět: |
Prioritization
Quantitative structure–activity relationship Computer science business.industry In silico Experimental data Quantitative Structure-Activity Relationship General Chemistry Chemical industry 010501 environmental sciences 01 natural sciences Models Biological Article Toxicokinetics Open source Metabolic clearance rate Environmental Chemistry Computer Simulation Biochemical engineering business Throughput (business) 0105 earth and related environmental sciences |
| Zdroj: | Environ Sci Technol |
| ISSN: | 1520-5851 |
| Popis: | 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 (6484 chemicals) we found that the proportion of chemicals with BER 1 using either in silico or in vitro parameters (768/848, 90.5%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured in vitro TK data are lacking. |
| Databáze: | OpenAIRE |
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