Evidence map›Paper›PMID 23479398›Full record

ArticleClinical pharmacokinetics2013

Prediction of drug-drug interactions between various antidepressants and efavirenz or boosted protease inhibitors using a physiologically based pharmacokinetic modelling approach.

Marco Siccardi, Catia Marzolini, Kay Seden, Lisa Almond, Anna Kirov, Saye Khoo, Andrew Owen, David Back

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Clinical pharmacokinetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
3.6field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.

  1. Antidepressants for depression in adults with HIV infection.The Cochrane database of systematic reviews · 2018
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  5. Transforming Treatment: The Impact of Bariatric Surgery on Oral Drug Absorption.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
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4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Marco SiccardiDepartment of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, 70 Pembroke Place, Liverpool, L69 3GF, UK. siccardi@liverpool.ac.uk
Catia Marzolini
Kay Seden
Lisa Almond
Anna Kirov
Saye Khoo
Andrew Owen
David Back
University of Liverpool · GBLiverpool School of Tropical Medicine · GBSimcyp (United Kingdom) · GBUniversity Hospital of Basel · CH

Funding

Medical Research Council G0800247
6 · The paper itself

Abstract

BACKGROUND AND

objectiveThe 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.

methodsIn 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.

resultsSimulated 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.

conclusionThe 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.

Indexed as

Models, BiologicalAlkynesAntidepressive AgentsAnti-Retroviral AgentsAtazanavir SulfateBenzoxazinesCyclopropanesDarunavirDrug InteractionsHumansOligopeptidesPyridinesRitonavirSulfonamidesAlkynesAntidepressive AgentsAnti-Retroviral AgentsAtazanavir SulfateBenzoxazinesCyclopropanesDarunavirefavirenzOligopeptidesPyridinesRitonavirSulfonamides

Identifiers

PMID23479398
OpenAlexW2045288713

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.