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JAC Advance Access originally published online on March 28, 2009
Journal of Antimicrobial Chemotherapy 2009 63(6):1233-1243; doi:10.1093/jac/dkp102
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© The Author 2009. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org
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Original research

Population pharmacokinetics of ritonavir-boosted atazanavir in HIV-infected patients and healthy volunteers

Laura Dickinson1,2,*, Marta Boffito3, David Back2, Laura Waters3, Laura Else2, Geraint Davies2, Saye Khoo2, Anton Pozniak3 and Leon Aarons4

1 NIHR 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 School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, UK

Received 13 January 2009; returned 30 January 2009; revised 17 February 2009; accepted 24 February 2009

* Corresponding author. 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 to: (i) describe ritonavir-boosted atazanavir concentrations (300/100 mg once daily) and identify important covariates; and (ii) evaluate the predictive performance of the model for lower, unlicensed atazanavir doses (150 and 200 mg once daily) boosted with ritonavir (100 mg once daily).

Methods: Non-linear mixed effects modelling was applied to determine atazanavir pharmacokinetic parameters, inter-individual variability (IIV) and residual error. Covariates potentially related to atazanavir pharmacokinetics were explored. The final model was assessed by means of a visual predictive check for 300/100, 200/100 and 150/100 mg once daily.

Results: Forty-six individuals were included (30 HIV-infected). A one-compartment model with first-order absorption and lag-time best described the data. Final estimates of apparent oral clearance (CL/F), volume of distribution (V/F) and absorption rate constant [relative standard error (%) and IIV (%)] were 7.7 L/h (5, 29), 103 L (13, 48) and 3.4 h–1 (34, 154); a lag-time of 0.96 h (1) was determined. Ritonavir area under the curve (AUC0–24) was the only significant covariate. Overall, 94%–97% of observed concentrations were within the 95% prediction intervals for all three regimens.

Conclusions: A population pharmacokinetic model for ritonavir-boosted atazanavir has been developed and validated. Ritonavir AUC0–24 was significantly associated with atazanavir CL/F. The model was used to investigate other, particularly lower, ritonavir-boosted atazanavir dosing strategies.

Keywords: modelling , simulation , variability , pharmacokinetics


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