title: A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection.
abstract: The current algorithm for selecting a population pharmacokinetic/pharmacodynamic model is based on the well-established forward addition/backward elimination method. A central strength of this approach is the opportunity for a modeller to continuously examine the data and postulate new hypotheses to explain observed biases. This algorithm has served the modelling community well, but the model selection process has essentially remained unchanged for the last 30 years. During this time, more robust approaches to model selection have been made feasible by new technology and dramatic increases in computation speed. We review these methods, with emphasis on genetic algorithm approaches and discuss the role these methods may play in population pharmacokinetic/pharmacodynamic model selection.
authors.affiliation: Next Level Solutions, LLC, Raleigh, NC, USA; Modeling and Simulation, Kinetigen Inc., Research Triangle Park, NC, USA.
authors.forename: Mark
authors.initials: M
authors.lastname: Sale
authors.forename: Eric A
authors.initials: EA
authors.lastname: Sherer
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D010597:Pharmacogenetics
keywords: genetic algorithm; nonmem; pharmacokinetics