Utilization of Machine Learning Approaches for Drug Clearance Prediction and Population Pharmacokinetic Covariate Analysis.

ABSTRACT: Population pharmacokinetic (popPK) analysis is routinely used to evaluate drug clearance and covariate effects on pharmacokinetic parameters to support dosing recommendations. While stepwise methods are traditionally employed for covariate identification, artificial intelligence (AI) and machine learning (ML) approaches offer promising alternatives for enhancing these analyses. This proof-of-concept study illustrates the application of AI/ML and explainable artificial intelligence (XAI) techniques for drug clearance prediction and covariate analysis using two distinct datasets for the drugs methotrexate and remifentanil. For the larger methotrexate dataset, we utilized multiple ML models including convolutional neural networks, logistic regression, and gradient boosting and highlighted exc

SUBMITTER: Rawal A 

PROVIDER: S-EPMC12446568 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature