Evidence map›Paper›PMID 36571702›Full record

ArticleClinical pharmacokinetics2023

Physiologically Based Pharmacokinetic Modelling to Identify Physiological and Drug Parameters Driving Pharmacokinetics in Obese Individuals.

Mattia Berton, Sara Bettonte, Felix Stader, Manuel Battegay, Catia Marzolini

Open access · hybridAbstract read
In one paragraph

Article in Clinical pharmacokinetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.1field-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

22 citing papers in PubMed, 28 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Review
  4. Best Practices in Physiologically Based Pharmacokinetic (PBPK) Modeling.CPT: pharmacometrics & systems pharmacology · 2026
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Nanomedicines Against Mitochondrial Dysfunction-Induced Metabolic Diseases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  12. Advances in Cytotoxicity Testing: From In Vitro Assays to In Silico Models.International journal of molecular sciences · 2025
    Review
  13. Article
  14. Obesity-related drug-metabolizing enzyme expression alterations in the human liver.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2025
    Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Effect of Obesity on the Exposure of Long-acting Cabotegravir and Rilpivirine: A Modeling Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
  20. Article
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

5 authors at 2 institutions in 2 countries.

Mattia BertonDivision of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland. mattia.berton@unibas.ch.ORCID http://orcid.org/0000-0001-9450-2228
Sara BettonteDivision of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.
Felix StaderCertara UK Limited, Sheffield, UK.
Manuel BattegayDivision of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.
Catia MarzoliniDivision of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.
University of Basel · CHUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObese individuals are often underrepresented in clinical trials, leading to a lack of dosing guidance.

objectiveThis study aimed to investigate which physiological parameters and drug properties determine drug disposition changes in obese using our physiologically based pharmacokinetic (PBPK) framework, informed with obese population characteristics.

methodsSimulations were performed for ten drugs with clinical data in obese (i.e., midazolam, triazolam, caffeine, chlorzoxazone, acetaminophen, lorazepam, propranolol, amikacin, tobramycin, and glimepiride). PBPK drug models were developed and verified first against clinical data in non-obese (body mass index (BMI) ≤ 30 kg/m

resultsPredicted pharmacokinetic parameters were within 1.25-fold (71.5%), 1.5-fold (21.5%) and twofold (7%) of clinical data. On average, clearance increased by 1.6% per BMI unit up to 64% for a BMI of 60 kg/m

conclusionBoth physiological changes and drug properties impact drug pharmacokinetics in obese subjects. Clearance increases due to enhanced hepatic and renal blood flows. Volume of distribution is higher for all drugs, with differences among drugs depending on their pK

Indexed as

MidazolamObesityBody Mass IndexCaffeineComputer SimulationHumansModels, BiologicalPharmacokineticsPropranololCaffeineMidazolamPropranolol

Identifiers

PMID36571702
PMCPMC9998327
OpenAlexW4312194542

What OpenQuestion holds

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LicenceCC BY-NC
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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.