Evidence map›Paper›PMID 40117041›Full record

ArticleInternational journal of clinical pharmacy2025

Optimizing tacrolimus dosage in post-renal transplantation using DoseOptimal framework: profiling CYP3A5 genetic variants for interpretability.

Chintal Upendra Raval, Ashwin Makwana, Samir Patel, Rashmi Hemani, Sachchida Nand Pandey

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Article in International journal of clinical pharmacy, 2025. 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 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Trial
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Chintal Upendra RavalU & P U Patel Department of Computer Engineering, Chandubhai S. Patel Institute of Technology, Charotar University of Science and Technology, CHARUSAT - Campus, Changa, Anand, Gujarat, 388421, India.ORCID http://orcid.org/0000-0002-8013-7589
Ashwin MakwanaU & P U Patel Department of Computer Engineering, Chandubhai S. Patel Institute of Technology, Charotar University of Science and Technology, CHARUSAT - Campus, Changa, Anand, Gujarat, 388421, India.ORCID http://orcid.org/0000-0002-4232-9598
Samir PatelDepartment of Pharmaceutical Chemistry and Analysis, Ramanbhai Patel College of Pharmacy, Charotar University of Science and Technology, CHARUSAT - Campus, Changa, Anand, Gujarat, 388421, India.ORCID http://orcid.org/0000-0003-4481-8296
Rashmi HemaniDepartment of Pharmacology, Ramanbhai Patel College of Pharmacy, Charotar University of Science and Technology, CHARUSAT - Campus, Changa, Anand, Gujarat, 388421, India.ORCID http://orcid.org/0000-0003-1428-6831
Sachchida Nand PandeyDepartment of Pathology, Muljibhai Patel Urological Hospital, Nadiad, Gujarat, 387001, India. snpandey@mpuh.org.ORCID http://orcid.org/0000-0002-0567-5344

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAchieving optimal tacrolimus dosing is vital for effectively balancing therapeutic efficacy and safety, as CYP3A5 genetic variants and inter-patient variability emphasize the need for precision strategies.

aimThis study aimed to optimize tacrolimus dosage prediction for renal transplant recipients by incorporating genetic polymorphisms, specifically profiling CYP3A5 genetic variants, within the DoseOptimal framework to enhance interpretability and accuracy of dosing decisions.

methodThe dataset comprised clinical, demographic, and CYP3A5 genetic variants information from 1045 stable tacrolimus-treated patients. The DoseOptimal framework was developed by integrating the strengths of the most effective algorithms from fifteen machine learning models. SHapley Additive exPlanations (SHAP) and decision tree insights were incorporated to enhance the framework's interpretability. The framework's performance was assessed using mean absolute error (MAE) and the coefficient of determination (R

resultsThe DoseOptimal framework demonstrated robust performance with an R

conclusionThe framework provides precision medicine-based dosing solutions tailored to individual genetic profiles, minimizing dosing errors and enhancing patient outcomes.

Indexed as

Cytochrome P-450 CYP3AGenetic VariationImmunosuppressive AgentsKidney TransplantationTacrolimusAdultAgedDose-Response Relationship, DrugFemaleHumansMaleMiddle AgedCYP3A5 protein, humanCytochrome P-450 CYP3AImmunosuppressive AgentsTacrolimusCYP3A5Machine learning algorithmsPharmacogenomicsPrecision medicineRenal transplantationTacrolimus

Identifiers

PMID40117041

What OpenQuestion holds

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Registered trials

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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.