ArticleJAMIA open2026
Design and implementation of PharMe: a mobile application to return pharmacogenomic test results to patients.
Article in JAMIA open, 2026. 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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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.
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13 authors.
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Abstract
Objective: Pharmacogenomics can optimize therapeutic outcomes while minimizing adverse events. However, the lack of trained healthcare professionals has impeded its widespread adoption. Current patient-facing applications are either institution-specific or vary significantly in their coverage of genetic variants, interpretation guidelines, and data privacy protection. To address these shortcomings, we developed PharMe. Materials and Methods: All components were developed through co-design; experts created patient-friendly content in English from Clinical Pharmacogenomics Implementation Consortium and Food and Drug Administration guidelines. Results: PharMe returns pharmacogenomic results for 17 genes and 159 medications, including phenoconversion of CYP2D6 due to inhibitors. PharMe is facilitated by Anni, a web interface enabling consistent, multilingual annotation of guidelines with patient-friendly formulations. Initial evaluations demonstrate that PharMe is usable and stable. PharMe is available for iOS and Android in English. Discussion: PharMe and Anni use transparent, standardized guideline content, are agnostic to data sources, and can flexibly be deployed globally in different settings and institutions, while upholding data privacy. Prospectively, both could support further guidelines and data formats. Validation of clinical utility, patient comprehension, and empowerment is underway in a clinical validation study with diverse patients. Conclusion: We developed a novel, extensible, usable, and stable system to transparently return pharmacogenomic results to patients. These findings support further investigation in larger, more diverse populations and in real-world clinical settings, with the goal of informing scalable, guideline-concordant pharmacogenomics implementation.
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