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Updated: May 24, 2026

An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Published on: March 30, 2014
A population pharmacokinetic-pharmacogenetic analysis of atazanavir
Deidre A Kile1, Samantha MaWhinney, Christina L Aquilante
1Colorado Health Outcomes Program, University of Colorado Denver School of Medicine, Aurora, USA.
Abstract:
Atazanavir is a first-line HIV protease inhibitor commonly co-dosed with ritonavir. Ritonavir inhibits atazanavir metabolism, decreasing variability and increasing plasma concentrations. However, ritonavir use results in higher costs and increased drug-related adverse events. Elucidating atazanavir pharmacokinetics might allow for individualized ritonavir boosting. We previously demonstrated that genetically determined CYP3A5 nonexpression was associated with slower atazanavir clearance CL/F and higher trough concentrations. This effect was prominent in non-African-American men but absent in African-Americans. The present study considers additional genetic predictors of atazanavir CL/F with a focus on race differences. Nine polymorphisms in CYP3A4, ABCG2, NR1I2 (PXR), and SLCO1B1 were evaluated; 330 plasma samples from 30 HIV-negative volunteers, balanced by sex, race, and CYP3A5 expressor status, were available. Analyses were performed using nonlinear mixed-effects modeling (NONMEM). The following factors were univariately associated with atazanavir CL/F (% effect) : African-American race (decreased 35%), female sex (decreased 25%), older age (decreased 1.7%/year), CYP3A5 nonexpressors (decreased 26%), ABCB1 CGC haplotype carriers (1236C/2677G/3435C) (decreased 33%), and CYP3A4*1B carriers (decreased 31%). However, an independent genetic explanation for the differential race effect could not be identified. An interaction was observed with PXR 63396 C>T and CYP3A5 expressor status (p=0.0002). CYP3A5 nonexpressors with a PXR 63396 CC genotype had 37% slower CL/F versus those with CT or TT genotypes. For CYP3A5 expressors, those with a PXR 63396 CC genotype had 63% faster CL/F versus those with CT or TT genotypes. Although this study has as its main limitation a small overall sample size, these results nonetheless provide new leads and impetus to evaluate ways to individualize the need for ritonavir boosting using demographic and genetic predictors of atazanavir pharmacokinetics.
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One key aspect of the noncompartmental approach is determining a drug's total clearance. This can be done by dividing the drug dose by the area under the concentration-time curve from zero to infinity. The area under the concentration-time curve represents the drug's overall...
