JAC Advance Access originally published online on September 29, 2008
Journal of Antimicrobial Chemotherapy 2008 62(6):1344-1355; doi:10.1093/jac/dkn399
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Original research |
Population pharmacokinetics of ritonavir-boosted saquinavir regimens in HIV-infected individuals
1 NIHR National Biomedical Research Centre, Royal Liverpool and Broadgreen University Hospital Trust, Liverpool, UK 2 Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK 3 St Stephen's Centre, Chelsea and Westminster Foundation Trust, London, UK 4 Joint Clinical Research Centre, Kampala, Uganda 5 Department of Pharmacology, Trinity College Dublin, Dublin, Ireland 6 HIV-NAT, Thai Red Cross AIDS Research Centre, Bangkok, Thailand 7 Department of Clinical Pharmacy, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands 8 School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, UK
Received 24 June 2008; returned 21 August 2008; revised 29 August 2008; accepted 29 August 2008
* Correspondence address. Department of Pharmacology, University of Liverpool, Pharmacology Research Laboratories, Block H, First Floor, 70 Pembroke Place, Liverpool L69 3GF, UK. Tel: +44-151-794-5553; Fax: +44-151-794-5656; E-mail: laurad{at}liv.ac.uk
Objectives: The aim of this study was to develop and validate a population pharmacokinetic model in order to describe ritonavir-boosted saquinavir concentrations dosed twice and once daily in human immunodeficiency virus (HIV)-infected patients from the UK, Uganda and Thailand and to identify factors that may influence saquinavir pharmacokinetics.
Methods: Pharmacokinetic data from 10 clinical studies were combined. Non-linear mixed effects modelling (NONMEM version V) was applied to determine the saquinavir pharmacokinetic parameters, interindividual/interoccasion variability (IIV/IOV) and residual error. Various covariates potentially related to saquinavir pharmacokinetics were explored, and the final model was validated by means of 95% prediction interval and testing the predictive performance of the model with data not included in the model-building process.
Results: Ninety-seven patients were included from the UK (n = 52), Uganda (n = 18) and Thailand (n = 27), contributing 347 saquinavir profiles (1–14 profiles per patient). A one-compartment model with zero-order absorption and lag-time best described the data with IIV/IOV on apparent oral clearance (CL/F) and volume of distribution (V/F) and with IIV on duration and absorption lag-time. The ritonavir area under the curve over the dosing interval was significantly associated with saquinavir CL/F and V/F. A typical patient from the UK had 
1.5- and 3-fold higher saquinavir CL/F compared with patients from Uganda (89.0 versus 49.8 L/h) and Thailand (89.0 versus 26.7 L/h), respectively.
Conclusions: A model to characterize ritonavir-boosted saquinavir pharmacokinetics in HIV-infected adults has been developed and validated. The model could be used for dosage adaptation following therapeutic drug monitoring and to assess patients' suitability for once-daily boosted saquinavir therapy.
Keywords: NONMEM , UK , Uganda , Thailand , variability
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