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

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An Erratum to this article was published on 30 April 2013

Abstract

Background and Objective

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.

Methods

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 Simcyp™ 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.

Results

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.

Conclusion

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.

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Acknowledgments

Andrew Owen has received honoraria for lectures or advisory board meetings and/or research support research funding by Abbott Laboratories, AstraZeneca, GlaxoSmithKline, Merck, Pfizer and Roche Pharmaceuticals. David Back and Saye Khoo have received honoraria for lectures or advisory board meetings and/or research support and research funding by Merck, Gilead, BMS, Tibotec and ViiV. Marco Siccardi has received financial support from Simcyp Ltd. Lisa Almond is an employee of Simcyp Ltd. Catia Marzolini, Kay Seden and Anna Kirov declared no conflicts of interest that are directly relevant to the content of this study.

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Authors and Affiliations

  1. Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, 70 Pembroke Place, Liverpool, L69 3GF, UK

    Marco Siccardi, Kay Seden, Anna Kirov, Saye Khoo, Andrew Owen & David Back

  2. Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland

    Catia Marzolini

  3. Simcyp Limited, Sheffield, UK

    Lisa Almond

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  1. Marco Siccardi
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Correspondence to Marco Siccardi.

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Siccardi, M., Marzolini, C., Seden, K. et al. Prediction of drug-drug Interactions Between Various Antidepressants and Efavirenz or Boosted Protease Inhibitors Using a Physiologically Based Pharmacokinetic Modelling Approach. Clin Pharmacokinet 52, 583–592 (2013). https://doi.org/10.1007/s40262-013-0056-7

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