Evidence map›Paper›PMID 42414845›Full record

ArticleClinical pharmacokinetics2026

Physiologically Based Pharmacokinetic (PBPK) Modeling of Antidepressants: A Scoping Review of Existing Models, Applications, and Software Tools.

Rebecca Leyla Huber, Oliver Scherf-Clavel

Abstract readScoping Review
In one paragraph

Article in Clinical pharmacokinetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Rebecca Leyla HuberDepartment of Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5, 81377, Munich, Germany.ORCID http://orcid.org/0009-0008-0302-3925
Oliver Scherf-ClavelDepartment of Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstraße 5, 81377, Munich, Germany. O.Scherf-Clavel@lmu.de.ORCID http://orcid.org/0000-0002-1967-9231

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Physiologically based pharmacokinetic models are a valuable tool for simulating antidepressant pharmacokinetics in patient groups that are often underrepresented in clinical trials. Clinical data on antidepressant use in vulnerable populations such as geriatric patients or pregnant women remain limited, making safe and personalized treatment challenging. The objective of this review was to systematically evaluate existing physiologically based pharmacokinetic models for antidepressants, their applications, and the modeling software platforms used, in order to identify relevant research gaps and highlight future needs for model development. A scoping review was conducted in accordance with Preferred Reporting Items for Scoping Reviews (PRISMA-ScR) guidelines. Seven electronic databases were systematically searched. Data on the modeled drug, model applications, and software platforms were extracted and evaluated. A total of 60 studies met the inclusion criteria. The availability of physiologically based pharmacokinetic models across antidepressants was heterogeneous. Paroxetine, fluvoxamine, and venlafaxine were most frequently modeled (n = 10 each), whereas few or no models exist for substances such as mirtazapine (n = 1) or milnacipran (n = 0). The main application areas were drug-drug interactions (n = 18), pregnancy (n = 14), and drug-(drug-)gene interactions (n = 13). Pediatric populations and specific ethnic groups were rarely addressed. SimCyp® Simulator was the most used modeling platform, followed by PK-Sim®/Mobi®, GastroPlus®, and R®/RStudio®. Although physiologically based pharmacokinetic models for antidepressants are increasingly available, they focus on a limited number of drugs and applications. Substantial evidence gaps remain, particularly for vulnerable patient populations.

Indexed as

Antidepressive AgentsModels, BiologicalDrug InteractionsFemaleHumansPregnancySoftwareAntidepressive Agents

Identifiers

PMID42414845
PMCPMC13461864

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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.