An Evolutionary Search Algorithm for Covariate Models in Population Pharmacokinetic Analysis.

Building a covariate model is a crucial task in population pharmacokinetics. This study develops a novel method for automated covariate modeling based on gene expression programming (GEP), which not only enables covariate selection, but also the construction of nonpolynomial relationships between pharmacokinetic parameters and covariates. To apply GEP to the extended nonlinear least squares analysis, the parameter consolidation and initial parameter value estimation algorithms were further developed and implemented.

Modeling of rifampicin-induced CYP3A4 activation dynamics for the prediction of clinical drug-drug interactions from in vitro data.

Induction of cytochrome P450 3A4 (CYP3A4) expression is often implicated in clinically relevant drug-drug interactions (DDI), as metabolism catalyzed by this enzyme is the dominant route of elimination for many drugs. Although several DDI models have been proposed, none have comprehensively considered the effects of enzyme transcription/translation dynamics on induction-based DDI. Rifampicin is a well-known CYP3A4 inducer, and is commonly used as a positive control for evaluating the CYP3A4 induction potential of test compounds.

Computer-based evolutionary search for a nonlinear conversion function for establishing in vitro-in vivo correlation (IVIVC) of oral drug formulations.

Establishment of in vitro-in vivo correlation (IVIVC) accelerates optimization of desirable drug formulations and/or modification of the manufacturing processes in the scale-up and post-approval periods. This article presents a method of finding the optimal conversion function for establishing Level A point-to-point IVIVC, based on a computer-based evolutionary search technique. Gene expression programming (GEP) is a technique for optimizing a mathematical expression tree with the help of a genetic algorithm.