ArticleInternational journal of molecular sciences2020
A Machine Learning-Based Identification of Genes Affecting the Pharmacokinetics of Tacrolimus Using the DMET
Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
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Who cites it
12 citing papers in PubMed, 15 citations in OpenAlex.
- Advances in HLA and Non-HLA Immune Profiling: Integrating Next-Generation Sequencing and Artificial Intelligence in Transplantation.Annals of laboratory medicine · 2026Review
- Artificial Intelligence and Predictive Modelling for Precision Dosing of Immunosuppressants in Kidney Transplantation.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Advancing precision tacrolimus therapy: a systems genetics dissection in BXD platform.Frontiers in immunology · 2026Article
- Optimizing tacrolimus dosage in post-renal transplantation using DoseOptimal framework: profiling CYP3A5 genetic variants for interpretability.International journal of clinical pharmacy · 2025Article
- Clinical significance and gene prediction of a novel classification system based on tacrolimus concentration-to-dose ratio in the early post-liver transplant period.Frontiers in pharmacology · 2025Article
- The Role of Vitamin D Metabolism Genes and Their Genomic Background in Shaping Cyclosporine A Dosage Parameters after Kidney Transplantation.Journal of clinical medicine · 2024Article
- Developing supervised machine learning algorithms to evaluate the therapeutic effect and laboratory-related adverse events of cyclosporine and tacrolimus in renal transplants.International journal of clinical pharmacy · 2023Article
- Computational design of clinical trials using a combination of simulation and the genetic algorithm.CPT: pharmacometrics & systems pharmacology · 2023Article
- The Influence of Cytochrome P450 Polymorphisms on Pharmacokinetic Profiles and Treatment Outcomes Among Malaria Patients in Sub-Saharan Africa: A Systematic Review.Pharmacogenomics and personalized medicine · 2023Review
- Adoption of Machine Learning in Pharmacometrics: An Overview of Recent Implementations and Their Considerations.Pharmaceutics · 2022Article
- Artificial-Intelligence-Assisted Discovery of Genetic Factors for Precision Medicine of Antiplatelet Therapy in Diabetic Peripheral Artery Disease.Biomedicines · 2022Article
- Tacrolimus pharmacokinetics in pediatric nephrotic syndrome: A combination of population pharmacokinetic modelling and machine learning approaches to improve individual prediction.Frontiers in pharmacology · 2022Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tacrolimus is an immunosuppressive drug with a narrow therapeutic index and larger interindividual variability. We identified genetic variants to predict tacrolimus exposure in healthy Korean males using machine learning algorithms such as decision tree, random forest, and least absolute shrinkage and selection operator (LASSO) regression.
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What OpenQuestion holds
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 OpenQuestion graph.