The influence of tuberculosis treatment on efavirenz clearance in patients co-infected with HIV and tuberculosis.

Purpose: Drug interactions are of concern when treating patients co-infected with human immunodeficiency virus (HIV) and tuberculosis. Concomitant use of efavirenz (EFV) with the enzyme inducer rifampicin might be expected to increase EFV clearance. We investigated the influence of concomitant tuberculosis treatment on the plasma clearance of EFV. Methods: Fifty-eight patients were randomized to receive their EFV-containing antiretroviral therapy either during or after tuberculosis treatment. Steady-state EFV plasma concentrations (n = 209 samples) were measured, 83 in the presence of rifampicin. Data were analyzed using a non-linear mixed effects model, and the model was evaluated using non-parametric bootstrap and visual predictive checks. Results: The patients had a median age of 32 (range 19–55) years and 43.1% were women. There was a bimodal distribution of apparent clearance, with slow EFV metabolizers accounting for 23.6% of the population and having a metabolic capacity 36.4% of that of the faster metabolizers. Apparent EFV clearance after oral administration in fast metabolizers was 12.9 L/h/70 kg whilst off tuberculosis treatment and 9.1 L/h/70 kg when on tuberculosis treatment. In slow metabolizers, the clearance estimates were 3.3 and 4.7 L/h/70 kg in the presence and absence of TB treatment, respectively. Overall there was a 29.5% reduction in EFV clearance during tuberculosis treatment. Conclusion: Unexpectedly, concomitant rifampicin-containing tuberculosis treatment reduced apparent EFV clearance with a corresponding increase in EFV exposure. While the reasons for this interaction require further investigation, cytochrome P450 2B6 polymorphisms in the population studied may provide some explanation

Prediction of drug-drug Interactions Between Various Antidepressants and Efavirenz or Boosted Protease Inhibitors Using a Physiologically Based Pharmacokinetic Modelling Approach

The rate of depression in patients with HIV is higher than in the general population. The use of antidepressants can have a beneficial effect, improving antiretroviral therapy adherence and consequently their efficacy and safety. Efavirenz and protease inhibitor boosted with ritonavir are major components of the antiretroviral therapy and are inducers and/or inhibitors of several cytochrome P450 (CYP) isoforms. Although antidepressants are prescribed to a significant proportion of patients treated with antiretrovirals, there are limited clinical data on drug-drug interactions. The aim of this study was to predict the magnitude of drug-drug interactions among efavirenz, boosted protease inhibitors and the most commonly prescribed antidepressants using an in vitro-in vivo extrapolation (IVIVE) model simulating virtual clinical trials.; In vitro data describing the chemical characteristics, and absorption, distribution, metabolism and elimination (ADME) properties of efavirenz, boosted protease inhibitors and the most commonly prescribed antidepressants were obtained from published literature or generated by standard methods. Pharmacokinetics and drug-drug interaction were simulated using the full physiologically based pharmacokinetic model implemented in the Simcyptm ADME simulator. The robustness of our modeling approach was assessed by comparing the magnitude of simulated drug-drug interactions using probe drugs to that observed in clinical studies.; Simulated pharmacokinetics and drug-drug interactions were in concordance with available clinical data. Although the simulated drug-drug interactions with antidepressants were overall weak to moderate according to the classification of the US FDA, fluoxetine and venlafaxine represent better candidates from a pharmacokinetic standpoint for patients on efavirenz and venlafaxine or citalopram for patients on boosted protease inhibitors.; The modest magnitude of interaction could be explained by the fact that antidepressants are substrates of multiple isoforms and thus metabolism can still occur through CYPs that are weakly impacted by efavirenz or boosted protease inhibitors. These findings indicate that IVIVE is a useful tool for predicting drug-drug interactions and designing prospective clinical trials, giving insight into the variability of exposure, sample size and time-dependent induction or inhibition