ArticlePharmaceutical research2024
Physiologically Based Pharmacokinetic Modeling to Unravel the Drug-gene Interactions of Venlafaxine: Based on Activity Score-dependent Metabolism by CYP2D6 and CYP2C19 Polymorphisms.
Article in Pharmaceutical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Psychopharmacological Mechanisms of Antidepressant Withdrawal: Insights From Venlafaxine.Human psychopharmacology · 2026Review
- Physiologically Based Pharmacokinetic (PBPK) Modeling of Antidepressants: A Scoping Review of Existing Models, Applications, and Software Tools.Clinical pharmacokinetics · 2026Article
- Advancing inclusive healthcare through PBPK modelling: predicting the impact of CYP genotypes and enzyme ontogenies on infant exposures of venlafaxine and its active metabolite O-desmethylvenlafaxine in lactation.Journal of pharmacokinetics and pharmacodynamics · 2025Article
- A physiologically-based quantitative systems pharmacology model for mechanistic understanding of the response to alogliptin and its application in patients with renal impairment.Journal of pharmacokinetics and pharmacodynamics · 2025Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundVenlafaxine (VEN) is a commonly utilized medication for alleviating depression and anxiety disorders. The presence of genetic polymorphisms gives rise to considerable variations in plasma concentrations across different phenotypes. This divergence in phenotypic responses leads to notable differences in both the efficacy and tolerance of the drug. PURPOSE: A physiologically based pharmacokinetic (PBPK) model for VEN and its metabolite O-desmethylvenlafaxine (ODV) to predict the impact of CYP2D6 and CYP2C19 gene polymorphisms on VEN pharmacokinetics (PK).
methodsThe parent-metabolite PBPK models for VEN and ODV were developed using PK-Sim
resultsIn the base models, 91.1%, 94.8%, and 94.6% of the predicted plasma concentrations for VEN, ODV, and VEN + ODV, respectively, fell within a twofold error range of the corresponding observed concentrations. For DGI scenarios, these values were 81.4% and 85% for VEN and ODV, respectively. Comparing CYP2D6 AS = 2 (normal metabolizers, NM) populations to AS = 0 (poor metabolizers, PM), 0.25, 0.5, 0.75, 1.0 (intermediate metabolizers, IM), 1.25, 1.5 (NM), and 3.0 (ultrarapid metabolizers, UM) populations in CYP2C19 AS = 2.0 group, the predicted DGI AUC
conclusionsIn clinical practice, the impact of genotyping on the in vivo disposition process of VEN should be considered to ensure the safety and efficacy of treatment.
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Registered trials
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 Socratic graph.