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Updated: Aug 31, 2026

Cost-Efficient Transcriptomic-Based Drug Screening
Published on: February 23, 2024
A transcriptomics-based computational drug repurposing pipeline identifies simvastatin and primaquine as therapeutics
Tomiko T Oskotsky1,2, Xinyu Tang1, Erin Arthurs3
1Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
Abstract:
Endometriosis has limited treatment options, prompting the search for data-driven therapeutics. We previously used a transcriptomics-based computational drug repositioning pipeline and identified several drug candidates. Fenoprofen, our top in silico candidate, was validated in a rat model of endometriosis-associated pain. Building on this, we evaluated two additional candidates, simvastatin and primaquine. Using the rat model, we conducted behavioral testing, bulk RNA sequencing, and differential expression analysis to assess their therapeutic potential. We also assessed endometriosis diagnosis among patients prescribed simvastatin in electronic medical records across six University of California (UC) healthcare institutions. Overall, simvastatin and primaquine attenuated pain-associated behaviors and reversed endometriosis-related gene expression changes in our animal model. Moreover, simvastatin prescription was associated with a lower observed relative risk of endometriosis in our retrospective multi-center cohort study. These findings highlight their potential as repurposed therapeutics for endometriosis and support the effectiveness of computational drug repositioning in identifying treatment strategies.
