Evidence map›Paper›PMID 42583968›Full record

ReviewIndian journal of pharmacology2026

Effectiveness of pharmacogenomics-guided dosing in improving treatment outcomes.

L V Karthikeyan, A Subamathi, P Pragathi, S Vaishnavi, V Sanjana, R Sangamithra

Abstract readReview
In one paragraph

Review in Indian journal of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

L V KarthikeyanDepartment of Pharmaceutical Analysis, JSS College of Pharmacy, Ooty, Tamil Nadu, India.
A Subamathi
P Pragathi
S Vaishnavi
V Sanjana
R Sangamithra

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

abstractThe pharmacogenomics (PGx) discipline has played the pivotal role in the precision medicine by enabling the tailoring drug therapies to the genomic characteristics on an individual patient. This study reviewed PGx-guided dosing in the treatment of major diseases, such as cardiovascular, psychiatric, transplant, and oncologic. Data from randomized controlled trials, meta-analyses, and system reviews provided important insights. Several case reports indicated that genotype-guided drug prescription, indeed, helped to better select therapies for patients. For cardiovascular care specifically, warfarin and clopidogrel dosing, which were guided by PGx, was shown to work. Psychiatric cases supported better rates of remission and a lower number of side effects. The field of oncology demonstrates a marked reduction in the incidence of toxic reactions in chemotherapy regimens, whereas the field of transplant medicine had improved the management of immunosuppressants and the survival of grafts. Economic analyses further supported PGx testing, showing reduced hospitalizations and fewer treatment failures, thereby lowering healthcare costs. Although the clinical benefits of PGX-guided therapy were evident, several challenges limited its widespread adoption. These include inadequate clinical clinician training in consistent testing standards and gaps in infrastructure. Overcoming these barriers depended on advancements in decision support systems, machine learning applications, and the integration of multiomic data. Growing evidence from recent research has highlighted this shift, demonstrating how the PGx approach continues to evolve. Ultimately, PGF-guided dosing emerged not simply as a new technique but a promising pathway to improving patient outcomes, reducing healthcare costs, and shaping the future direction of personalized medicine.

Indexed as

PharmacogeneticsPrecision MedicineHumansTreatment OutcomeCost-effectivenessgenotype-guided dosingpersonalized medicinepharmacogenomicstreatment outcomes

Identifiers

PMID42583968
PMCPMC13412498

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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.