An application of Bayesian population pharmacokinetic/pharmacodynamic models to dose recommendation.
Population pharmacokinetic data consists of dose histories, individual covariates and measured drug concentrations with associated sampling times. Population pharmacodynamic data consist of dose histories, covariates and some response measure. Population analyses, whether they be pharmacokinetic or pharmacodynamic attempt to explain the variability observed in the recorded measurements and are increasingly being seen as an important aid in drug development. In this paper a general Bayesian population pharmacokinetic/pharmacodynamic model is described and an analysis of data for the drug recombinant hirudin is presented. The model we use allows for both outliers and censoring in the concentration data and outlying individual pharmacokinetic parameters. We attempt to address directly important questions such as recommended dose size using predictive distributions for response.
Wakefield
J
J
Mathematics Department, Imperial College, London, UK.
Racine-Poon
A
A
D001499:Bayes Theorem; D001777:Blood Coagulation / Q000187:drug effects; D017322:Clinical Trials, Phase II as Topic / Q000706:statistics & numerical data; D017326:Clinical Trials, Phase III as Topic / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D004347:Drug Interactions; D004359:Drug Therapy, Combination; D006493:Heparin / Q000494:pharmacology; D006629:Hirudins / Q000493:pharmacokinetics / Q000494:pharmacology; D006801:Humans; D007275:Injections, Intravenous; D008390:Markov Chains; D015233:Models, Statistical
D006629:Hirudins; D006493:Heparin