ArticleCurrent opinion in organ transplantation2020
Recent advances in precision medicine for individualized immunosuppression.
Article in Current opinion in organ transplantation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Augmenting the Transplant Team With Artificial Intelligence: Toward Meaningful AI Use in Solid Organ Transplant.Frontiers in immunology · 2021Pooled it
- Immunomodulatory Strategies for Managing Viral Infections in Solid Organ Transplantation: Progress and Challenges.Current microbiology · 2026Review
- Responsible Use of Artificial Intelligence to Improve Kidney Care: A Statement from the American Society of Nephrology.Journal of the American Society of Nephrology : JASN · 2026Review
- Cells, tissues, and vigilance: navigating the complex landscape of biovigilance in India.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Advocating for the recognition of underlying immunosuppression in critical illness.EClinicalMedicine · 2025Review
- Identification of urinary metabolites correlated with tacrolimus levels through high-precision liquid chromatography-mass spectrometry and machine learning algorithms in kidney transplant patients.Medicine and pharmacy reports · 2025Article
- Smart transplants: emerging role of nanotechnology and big data in kidney and islet transplantation, a frontier in precision medicine.Frontiers in immunology · 2025Review
- Machine Learning Applications in Solid Organ Transplantation and Related Complications.Frontiers in immunology · 2021Review
- Donor-specific cell-free DNA as a biomarker in liver transplantation: A review.World journal of transplantation · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
purpose of reviewThe current tools to proactively guide and individualize immunosuppression in solid organ transplantation are limited. Despite continued improvements in posttransplant outcomes, the adverse effects of over-immunosuppression or under-immunosuppression are common. The present review is intended to highlight recent advances in individualized immunosuppression. RECENT
findingsThere has been a great focus on genomic information to predict drug dose requirements, specifically on single nucleotide polymorphisms of CYP3A5 and ABCB1. Furthermore, biomarker studies have developed ways to better predict clinical outcomes, such as graft rejection. SUMMARY: The integration of advanced computing tools, such as artificial neural networks and machine learning, with genome sequencing has led to intriguing findings on individual or group-specific dosing requirements. Rapid computing allows for processing of data and discovering otherwise undetected clinical patterns. Genetic polymorphisms of CYP3A5 and ABCB1 have yielded results to suggest varying dose requirements correlated with race and sex. Newly proposed biomarkers offer precise and noninvasive ways to monitor patient's status. Cell-free DNA quantitation is increasingly explored as an indicator of allograft injury and rejection, which can help avoid unneeded biopsies and more frequently monitor graft function.
Indexed as
Identifiers
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.