title: Pharmacodynamic population analysis in chronic renal failure using artificial neural networks--a comparative study.
abstract: This work presents a pharmacodynamic population analysis in chronic renal failure patients using Artificial Neural Networks (ANNs). In pursuit of an effective and cost-efficient strategy for drug delivery in patients with renal failure, two different types of ANN are applied to perform drug dose-effect modeling and their performance compared. Applied in a clinical environment, such models will allow for prediction of patient response to the drug at the effect site and, subsequently, for adjusting the dosing regimen.
authors.affiliation: Kidney Disease Program, University of Louisville, Louisville, KY 40202, USA.
authors.forename: Adam E
authors.initials: AE
authors.lastname: Gaweda
authors.forename: Alfred A
authors.initials: AA
authors.lastname: Jacobs
authors.forename: Michael E
authors.initials: ME
authors.lastname: Brier
authors.forename: Jacek M
authors.initials: JM
authors.lastname: Zurada
mesh_terms: D001185:Artificial Intelligence; D006801:Humans; D007676:Kidney Failure, Chronic / Q000188:drug therapy / Q000378:metabolism; D008954:Models, Biological; D016571:Neural Networks, Computer; D010599:Pharmacokinetics