Affiliation:
1. Xiangya School of Pharmaceutical Sciences, Central South University, No. 172, Tongzipo Road, Changsha, Hunan,
410013, China
Abstract
Abstract:
Quantitative Structure-Property Relationship (QSPR) employs mathematical and statistical methods to reveal quantitative correlations between the pharmacokinetics of compounds and
their molecular structures, as well as their physical and chemical properties. QSPR models have
been widely applied in the prediction of drug absorption, distribution, metabolism, excretion, and
toxicity (ADMET). However, the accuracy of QSPR models for predicting drug ADMET properties still needs improvement. Therefore, this paper comprehensively reviews the tools employed in
various stages of QSPR predictions for drug ADMET. It summarizes commonly used approaches
to building QSPR models, systematically analyzing the advantages and limitations of each modeling method to ensure their judicious application. We provide an overview of recent advancements
in the application of QSPR models for predicting drug ADMET properties. Furthermore, this review explores the inherent challenges in QSPR modeling while also proposing a range of considerations aimed at enhancing model prediction accuracy. The objective is to enhance the predictive
capabilities of QSPR models in the field of drug development and provide valuable reference and
guidance for researchers in this domain.
Publisher
Bentham Science Publishers Ltd.
Subject
Drug Discovery,General Medicine