Comparison of Population Pharmacokinetics Based on Steady-State Assumption Versus Electronically Monitored Adherence to Lopinavir, Atazanavir, Efavirenz, and Etravirine: A Retrospective Study

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Abstract

Background:

Population pharmacokinetic (PopPK) analyses often rely on steady state and full adherence to prescribed dosage regimen assumptions from data gathered during therapeutic drug monitoring (TDM). Nonadherence is common in chronic diseases such as HIV. This study evaluates the impact of adherence measurement by electronic monitoring on PopPK parameter estimation and individual concentration profile predictions, and also the influence of adherence issues on the clinical interpretation of a concentration measurement.

Methods:

Published PopPK models for lopinavir, atazanavir, efavirenz, and etravirine were applied to estimate PK parameters and individual concentrations in 140 HIV patients taking part in a medication adherence program using 2 dosing data sets. The first set included the last dose reported by the patient with steady-state and full adherence assumptions; the second set used detailed electronic dosing history. PopPK parameter estimates and individual predictions were compared between the 2 dosing entries.

Results:

Clearance estimates and likewise predicted concentrations did not markedly differ between the 2 dosing histories. However, certain patterns of nonadherence such as sparse missed doses or consecutive missed doses lead to suboptimal drug exposure. The interpretation based on self-reported information would have concluded on a wrongly appropriate individual exposure.

Conclusions:

PopPK analysis assuming steady state with full adherence produced similar results to those based on detailed electronic dosing history reconciled with patients' allegations. Self-reported last dose intake appeared reliable for concentration predictions and therapeutic drug monitoring interpretation for most patients followed at the medication adherence program. Yet, clinicians should be aware that concentration predictions based on self-reported last dose intake might be overestimated in case of undetected patterns of nonadherence, increasing the risk of forthcoming therapeutic failure.

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