Comprehensive benchmarking of computational tools for predicting toxicokinetic and physicochemical properties of chemicals.

ABSTRACT: Ensuring the safety of chemicals for environmental and human health involves assessing physicochemical (PC) and toxicokinetic (TK) properties, which are crucial for absorption, distribution, metabolism, excretion, and toxicity (ADMET). Computational methods play a vital role in predicting these properties, given the current trends in reducing experimental approaches, especially those that involve animal experimentation. In the present manuscript, twelve software tools implementing Quantitative Structure-Activity Relationship (QSAR) models were selected for the prediction of 17 relevant PC and TK properties. A total of 41 validation datasets were collected from the literature, curated and used for assessing the models' external predictivity, emphasizing the performance of the models inside

SUBMITTER: Gadaleta D 

PROVIDER: S-EPMC11674477 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature