Prediction of pharmacokinetic/pharmacodynamic properties of aldosterone synthase inhibitors at drug discovery stage using an artificial intelligence-physiologically based pharmacokinetic model.

ABSTRACT: The objective of this study is to develop an artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) model to predict the pharmacokinetic (PK) and pharmacodynamic (PD) properties of aldosterone synthase inhibitors (ASIs), enabling selection of the right candidate with high potency and good selectivity at the drug discovery stage. On a web-based platform, an AI-PBPK model, integrating machine learning and a classical PBPK model for the PK simulation of ASIs, was developed. Baxdrostat, with the most clinical data available, was selected as the model compound. Following calibration and validation using published data, the model was applied to estimate the PK parameters of Baxdrostat, Dexfadrostat, Lorundrostat, BI689648, and the 11β-hydroxylase inhibitor LCI699. The PD of all

SUBMITTER: Zhang M 

PROVIDER: S-EPMC12066422 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature