Development of a sufficient design for estimation of fluconazole pharmacokinetics in people with HIV infection Juliana F. Roos, Carl M. J. Kirkpatrick, Susan E. Tett, Andrew J. McLachlan 1 & Stephen B. Duffull 2 School of Pharmacy, University of Queensland, Brisbane and 1 Faculty of Pharmacy, University of Sydney, Sydney, Australia, and 2 School of Pharmacy, University of Otago, Dunedin, Otago, New Zealand Correspondence Carl Kirkpatrick, School of Pharmacy, University of Queensland, Brisbane, QLD 4072, Australia. Tel: + 61 7 3365 3227 Fax: + 61 7 3365 1688 E-mail: c.kirkpatrick@pharmacy.uq.edu.au ---------------------------------------------------------------------- Keywords fluconazole, population pharmacokinetics, optimal design, HIV ---------------------------------------------------------------------- Received 20 October 2007 Accepted 10 June 2008 Published OnlineEarly 12 August 2008 WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Optimal design is being employed more frequently to help reduce the number of samples taken per patient, the number of patients and number of doses to be given within a study. • In doing this the economic and patient resources required to conduct a population pharmacokinetic or pharmacokinetic–pharmacodynamic study are reduced. WHAT THIS STUDY ADDS • This is the first time that healthy volunteer data (e.g. from Phase I) have been used to develop an optimal design that is to be conducted in a population with different characteristics due to disease (e.g. Phase II). AIMS To assess an optimal design that is sufficient to gain precise estimates of the pharmacokinetic (PK) parameters for fluconazole in people with HIV infection. METHODS Two studies were identified, the first in healthy volunteers and the second in HIV patients.The investigators (J.F.R. and S.B.D.) were blinded to the second study results. The healthy volunteer study was modelled and a design was found to estimate the PK parameters. The design was evaluated by comparison of the standard errors of the parameters and the predictive performance of the optimal design. The predictive performance was assessed by comparing model predictions against observed concentrations for two models. The first model, termed ‘sufficient design’,was developed from data extracted from the HIV study that corresponded to the optimal design. The second model, termed‘HIV outcome model’, by modelling all the data from the HIV study. RESULTS An optimal design HIV study was developed which had considerably fewer blood samples and dosing arms compared with the actual HIV study. The optimized design performed as well as the actual HIV study in terms of parameter precision. The performance of the design, described as the precision (mg l -1 ) 2 (95% confidence interval) of the predicted concentrations to the actual concentrations for the ‘sufficient design’ and ‘HIV outcome model’ models were: 0.63 (0.40, 0.87) and 0.56 (0.32, 0.79), respectively. CONCLUSION This study demonstrates how data from healthy volunteers can be utilized via optimal design methodology to design a successful study in the target population. British Journal of Clinical Pharmacology DOI:10.1111/j.1365-2125.2008.03247.x Br J Clin Pharmacol / 66:4 / 455–466 / 455 © 2008 The Authors Journal compilation © 2008 Blackwell Publishing Ltd