Literature DB >> 18806695

Population pharmacokinetics of atazanavir in human immunodeficiency virus-infected patients.

Caroline Solas1, Marie-Claude Gagnieu, Isabelle Ravaux, Marie-Pierre Drogoul, Alain Lafeuillade, Saadia Mokhtari, Bruno Lacarelle, Nicolas Simon.   

Abstract

The aim of this study was to determine the population pharmacokinetic (PK) parameters of atazanavir in adult human immunodeficiency virus-infected patients to build up a Bayesian strategy for dosage regimen individualization. This was an observational study of patients treated with the once-daily regimen atazanavir associated with 100 mg of ritonavir. Blood samples were drawn at steady state at various times ranging from 1 to 26 hours postdose. Atazanavir plasma concentrations were determined by a validated reverse-phase high-performance liquid chromatography method. PK analysis of the atazanavir population was performed using a nonlinear mixed-effects model (NONMEM version 6). One hundred eighty-seven patients were included in the study. The atazanavir doses prescribed were 300 mg (n = 169), 400 mg (n = 12), 200 mg (n = 1), and 150 mg (n = 5). The atazanavir population PK was described using a 1-compartment model with first-order absorption. Mean PK parameter estimations (95% confidence interval, coefficients of variation %) were as follows: oral clearance (CL) = 7.6 L/h (6.9-8.3; 34%), volume of distribution (V) = 80.8 L (67.4-94; 37%), and absorption constant rate (Ka) = 1.05 hours (0.01-2.09; 156%). The mean estimated half-life (T-half) was 7.5 hours (95% confidence interval: 7.2 -7.8 hours). The estimated T-half of atazanavir was in agreement with that previously reported of 8.6 and 8.8 hours. We observed a wide interpatient variability for the PK parameters, especially for Ka. This population approach allowed us to determine atazanavir PK parameters in human immunodeficiency virus-infected patients in a real-life context and to perform Bayesian analysis to predict Ctrough from samples collected at any moment during the dosing interval. This could therefore improve therapeutic drug monitoring interpretations and provide an interesting tool for correlation with virologic data.

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Year:  2008        PMID: 18806695     DOI: 10.1097/FTD.0b013e3181897bff

Source DB:  PubMed          Journal:  Ther Drug Monit        ISSN: 0163-4356            Impact factor:   3.681


  15 in total

1.  Population pharmacokinetic modeling of the association between 63396C->T pregnane X receptor polymorphism and unboosted atazanavir clearance.

Authors:  Alessandro Schipani; Marco Siccardi; Antonio D'Avolio; Lorena Baietto; Marco Simiele; Stefano Bonora; Sonia Rodríguez Novoa; Lorena Cuenca; Vincent Soriano; Nitipatana Chierakul; Natpratou Saguenwong; Charoen Chuchuttaworn; Janelle M Hoskins; Anne M Dvorak; Howard L McLeod; Gerry Davies; Saye Khoo; David J Back; Giovanni Di Perri; Andrew Owen
Journal:  Antimicrob Agents Chemother       Date:  2010-10-04       Impact factor: 5.191

2.  Atazanavir/ritonavir-based combination antiretroviral therapy for treatment of HIV-1 infection in adults.

Authors:  Chad J Achenbach; Kristin M Darin; Robert L Murphy; Christine Katlama
Journal:  Future Virol       Date:  2011-02       Impact factor: 1.831

3.  Population pharmacokinetics of atazanavir/ritonavir in HIV-1-infected children and adolescents.

Authors:  Frantz Foissac; Stéphane Blanche; Catherine Dollfus; Déborah Hirt; Ghislaine Firtion; Corinne Laurent; Jean-Marc Treluyer; Saïk Urien
Journal:  Br J Clin Pharmacol       Date:  2011-12       Impact factor: 4.335

4.  Pharmacokinetic-pharmacodynamic modeling of unboosted Atazanavir in a cohort of stable HIV-infected patients.

Authors:  Sylvain Goutelle; Thomas Baudry; Marie-Claude Gagnieu; André Boibieux; Jean-Michel Livrozet; Dominique Peyramond; Christian Chidiac; Michel Tod; Tristan Ferry
Journal:  Antimicrob Agents Chemother       Date:  2012-11-12       Impact factor: 5.191

5.  Effect of ritonavir and atazanavir on human subcutaneous preadipocyte proliferation and differentiation.

Authors:  Giuseppe Caso; Izolda Mileva; Margaret A McNurlan; Dennis C Mynarcik; Frank Darras; Marie C Gelato
Journal:  Antiviral Res       Date:  2010-02-11       Impact factor: 5.970

6.  Effect of adherence as measured by MEMS, ritonavir boosting, and CYP3A5 genotype on atazanavir pharmacokinetics in treatment-naive HIV-infected patients.

Authors:  R M Savic; A Barrail-Tran; X Duval; G Nembot; X Panhard; D Descamps; C Verstuyft; B Vrijens; A-M Taburet; C Goujard; F Mentré
Journal:  Clin Pharmacol Ther       Date:  2012-10-03       Impact factor: 6.875

7.  Population pharmacokinetic modelling of the changes in atazanavir plasma clearance caused by ritonavir plasma concentrations in HIV-1 infected patients.

Authors:  José Moltó; Javier A Estévez; Cristina Miranda; Samandhy Cedeño; Bonaventura Clotet; Marta Valle
Journal:  Br J Clin Pharmacol       Date:  2016-09-13       Impact factor: 4.335

Review 8.  Atazanavir: a review of its use in the management of HIV-1 infection.

Authors:  Katherine F Croom; Sohita Dhillon; Susan J Keam
Journal:  Drugs       Date:  2009-05-29       Impact factor: 9.546

9.  Factors influencing lopinavir and atazanavir plasma concentration.

Authors:  Wolfgang Stöhr; David Back; David Dunn; Caroline Sabin; Alan Winston; Richard Gilson; Deenan Pillay; Teresa Hill; Jonathan Ainsworth; Brian Gazzard; Clifford Leen; Loveleen Bansi; Martin Fisher; Chloe Orkin; Jane Anderson; Margaret Johnson; Philippa Easterbrook; Sara Gibbons; Saye Khoo
Journal:  J Antimicrob Chemother       Date:  2010-01       Impact factor: 5.790

Review 10.  Clinical pharmacokinetics of antiretroviral drugs in older persons.

Authors:  John C Schoen; Kristine M Erlandson; Peter L Anderson
Journal:  Expert Opin Drug Metab Toxicol       Date:  2013-03-20       Impact factor: 4.481

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