Evidence mapPaperPMID 40700148Full record

ReviewJournal of xenobiotics2025

Cataloging Actionable Pharmacogenomic Variants for Indian Clinical Practice: A Scoping Review.

Sacheta Sudhendra Kulkarni, Venkatesh R, Anuradha Das, Gayatri Rangarajan Iyer

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Review in Journal of xenobiotics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Sacheta Sudhendra KulkarniTata Institute for Genetics and Society, Gandhi Krishi Vignana Kendra Campus, Bellary Road, Bengaluru 560065, Karnataka, India.
Venkatesh RTata Institute for Genetics and Society, Gandhi Krishi Vignana Kendra Campus, Bellary Road, Bengaluru 560065, Karnataka, India.
Anuradha DasTata Institute for Genetics and Society, Gandhi Krishi Vignana Kendra Campus, Bellary Road, Bengaluru 560065, Karnataka, India.
Gayatri Rangarajan IyerTata Institute for Genetics and Society, Gandhi Krishi Vignana Kendra Campus, Bellary Road, Bengaluru 560065, Karnataka, India.ORCID 0000-0003-4811-6750

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPharmacogenomics (PGx), a pivotal branch of personalized medicine, studies how genetic variations influence drug responses. Despite its transformative potential, the adoption of PGx in Indian clinical practice faces challenges, such as the lack of population-specific data, evidence-based guidelines, and complexities in interpreting genomic reports. Comprehensive datasets tailored to Indian patients are essential to facilitate the integration of PGx into clinical settings. METHODOLOGY: The study collates pharmacogenomic data from multiple sources, including essential drugs listed by the World Health Organization (WHO), drugs used in neonatal intensive care units (NICUs), minimum sets of alleles recommended by the Association for Molecular Pathology (AMP), and catalogs the allele frequencies from the IndiGenomes database to address gaps in actionable PGx for the Indian population. Curated datasets were used to identify pharmacogenomic variants relevant to clinical practice.

resultsOverall, 24 prime genes are essential for the outcomes of 57 drugs. In adults, 18 genes influence the metabolism of 44 drugs whereas, in pediatric populations, genotypes of 18 genes significantly impact the metabolism of 18 drugs. Two over-the-counter drugs with actionable PGx variants were identified: ibuprofen and omeprazole. These findings emphasize the clinical relevance of PGx for commonly used drugs, underscoring the need for population-specific data.

conclusionsAs the data of several Indian human genome projects become available, an overarching need exists to establish and regulate the dynamic actionable PGx in Indian clinical practice. This will facilitate the integration of pharmacogenomic data into healthcare, enabling effective and personalized drug therapies.

Indexed as

adverse drug reactionsgene–drug interactionIndiGenomesindigenous datapharmacogenomicspharmacogenomics testingPharmGKB

Identifiers

PMID40700148
PMCPMC12286129

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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 Socratic graph.