A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection

dc.contributor.authorSale, Mark
dc.contributor.authorSherer, Eric A.
dc.contributor.departmentDepartment of Medicine, IU School of Medicineen_US
dc.date.accessioned2016-06-06T15:30:19Z
dc.date.available2016-06-06T15:30:19Z
dc.date.issued2015-01
dc.description.abstractThe 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.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.citationSale, M., & Sherer, E. A. (2015). A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection. British Journal of Clinical Pharmacology, 79(1), 28–39. http://doi.org/10.1111/bcp.12179en_US
dc.identifier.urihttps://hdl.handle.net/1805/9776
dc.publisherWileyen_US
dc.relation.isversionof10.1111/bcp.12179en_US
dc.relation.journalBritish Journal of Clinical Pharmacologyen_US
dc.rightsPublisher Policyen_US
dc.sourcePMCen_US
dc.subjectgenetic algorithmen_US
dc.subjectNONMEMen_US
dc.subjectpharmacokineticsen_US
dc.titleA genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selectionen_US
dc.typeArticleen_US
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