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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Updated: Mar 31, 2026

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets
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Drug repurposing using transcriptomics: principles and unmet needs in cardiovascular disease.

Samuel Leung1,2,3, Clint Miller4, Amrit Singh1,3

  • 1Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada.

American Journal of Physiology. Heart and Circulatory Physiology
|March 30, 2026
PubMed
Summary

Drug repurposing for cardiovascular disease shows promise using transcriptomics. However, current signature mapping methods need better cardiovascular data and reproducibility for effective therapeutic development.

Keywords:
cardiovascular diseaseconnectivity mappingdrug repurposingtranscriptome-based signature mapping

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Area of Science:

  • Genomics and Bioinformatics
  • Cardiovascular Medicine
  • Pharmacology

Background:

  • Cardiovascular disease is a leading global cause of death, with slow therapeutic development.
  • Drug repurposing offers a cost-effective strategy to accelerate cardiovascular drug development.
  • Transcriptomics and 'Omics' era provide new avenues for drug discovery and repurposing.

Purpose of the Study:

  • To review signature mapping principles and workflows for transcriptome-based drug repurposing.
  • To highlight features of analysis pipelines and databases for signature mapping.
  • To identify limitations and unmet needs in current transcriptomic approaches for cardiovascular drug repurposing.

Main Methods:

  • Review of signature mapping methodologies.
  • Analysis of existing transcriptomic databases and pipelines.
  • Comparison of statistical gene prioritization versus pathway-based approaches.

Main Results:

  • Signature mapping utilizes statistical models for transcriptome-based drug repurposing.
  • Current pipelines prioritize statistically significant genes, differing from traditional pharmacology.
  • Pipeline outcomes are sensitive to data quality and reproducibility issues.

Conclusions:

  • Existing RNA-seq databases primarily focus on cancer, lacking cardiovascular disease data.
  • High-quality cardiovascular molecular data is crucial for effective transcriptomic-based drug repurposing.
  • Interdisciplinary collaboration and cardiovascular biobanks are needed to advance this field.