Evidence map›Paper›PMID 39304577›Full record

SynthesisClinical pharmacokinetics2024

Model-Informed Precision Dosing of Tacrolimus: A Systematic Review of Population Pharmacokinetic Models and a Benchmark Study of Software Tools.

Yannick Hoffert, Nada Dia, Tim Vanuytsel, Robin Vos, Dirk Kuypers, Johan Van Cleemput, Jef Verbeek, Erwin Dreesen

Erratum issuedAbstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Clinical pharmacokinetics, 2024. 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 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. State of Art of Dose Individualization to Support tacrolimus drug monitoring: What's Next?Transplant international : official journal of the European Society for Organ Transplantation · 2025
    Review
  16. Review
  17. Article
  18. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Yannick HoffertDepartment of Pharmaceutical and Pharmacological Sciences, KU Leuven, ON2 Herestraat 49, Box 521, 3000, Leuven, Belgium.ORCID 0000-0002-1631-9484
Nada DiaDepartment of Pharmaceutical and Pharmacological Sciences, KU Leuven, ON2 Herestraat 49, Box 521, 3000, Leuven, Belgium.ORCID 0000-0003-1818-1949
Tim VanuytselDepartment of Chronic Diseases, Metabolism and Ageing (CHROMETA), KU Leuven, Leuven, Belgium.ORCID 0000-0001-8728-0903
Robin VosDepartment of Chronic Diseases, Metabolism and Ageing (CHROMETA), KU Leuven, Leuven, Belgium.ORCID 0000-0002-3468-9251
Dirk KuypersDepartment of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.ORCID 0000-0001-5546-9680
Johan Van CleemputDepartment of Cardiovascular Sciences, KU Leuven, Leuven, Belgium.ORCID 0000-0001-9246-6382
Jef VerbeekDepartment of Chronic Diseases, Metabolism and Ageing (CHROMETA), KU Leuven, Leuven, Belgium.ORCID 0000-0002-1549-8003
Erwin DreesenDepartment of Pharmaceutical and Pharmacological Sciences, KU Leuven, ON2 Herestraat 49, Box 521, 3000, Leuven, Belgium. erwin.dreesen@kuleuven.be.ORCID 0000-0002-0785-2930

Funding

Research Foundation Flanders (FWO) 1803521NResearch Foundation Flanders (FWO) 1830517NResearch Foundation Flanders (FWO) 1SHAA24N
6 · The paper itself

Abstract

BACKGROUND AND

objectiveTacrolimus is an immunosuppressant commonly administered after solid organ transplantation. It is characterized by a narrow therapeutic window and high variability in exposure, demanding personalized dosing. In recent years, population pharmacokinetic models have been suggested to guide model-informed precision dosing of tacrolimus. We aimed to provide a comprehensive overview of population pharmacokinetic models and model-informed precision dosing software modules of tacrolimus in all solid organ transplant settings, including a simulation-based investigation of the impact of covariates on exposure and target attainment.

methodsWe performed a systematic literature search to identify population pharmacokinetic models of tacrolimus in solid organ transplant recipients. We integrated selected population pharmacokinetic models into an interactive software tool that allows dosing simulations, Bayesian forecasting, and investigation of the impact of covariates on exposure and target attainment. We conducted a web survey amongst model-informed precision dosing software tool providers and benchmarked publicly available tools in terms of models, target populations, and clinical integration.

resultsWe identified 80 population pharmacokinetic models, including 44 one-compartment and 36 two-compartment models. The most frequently retained covariates on clearance and distribution parameters were cytochrome P450 3A5 polymorphisms and body weight, respectively. Our simulation tool, hosted at https://lpmx.shinyapps.io/tacrolimus/ , allows thorough investigation of the impact of covariates on exposure and target attainment. We identified 15 model-informed precision dosing software tool providers, of which ten offer a tacrolimus solution and nine completed the survey.

conclusionsOur work provides a comprehensive overview of the landscape of available tacrolimus population pharmacokinetic models and model-informed precision dosing software modules. Our simulation tool allows an interactive thorough exploration of covariates on exposure and target attainment.

Indexed as

Immunosuppressive AgentsModels, BiologicalSoftwareTacrolimusBayes TheoremBenchmarkingComputer SimulationCytochrome P-450 CYP3AHumansOrgan TransplantationPrecision MedicineCYP3A5 protein, humanCytochrome P-450 CYP3AImmunosuppressive AgentsTacrolimus

Identifiers

What Socratic 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 Socratic graph.