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Development and validation of an open data model for pharmacogenetics to enable semantic interoperability in clinical
Videha Sharma1, John H McDermott2,3, Jessica Keen2
1The Division of Evolution, Infection and Genomics, School of Biological Sciences, University of Manchester, Manchester, M13 9PT, UK. videha.sharma@manchester.ac.uk.
The Pharmacogenomics Journal
|June 12, 2026
Summary
Developing open data standards for pharmacogenetic results enables interoperability in healthcare. This framework supports integrating genetic testing into clinical practice for safer, more effective medication prescribing.
Area of Science:
- Genomic Medicine
- Health Informatics
- Clinical Pharmacology
Background:
- Pharmacogenetics, using genetic testing to optimize drug therapy, faces limited clinical adoption.
- Lack of interoperable health IT solutions hinders the integration of pharmacogenetic results into prescribing workflows.
- Scalable implementation requires standardized data models for seamless information exchange.
Purpose of the Study:
- To develop and validate open data standards for pharmacogenetic results.
- To enable interoperability of pharmacogenetic data across diverse healthcare systems.
- To facilitate the integration of pharmacogenetic information into clinical decision-making.
Main Methods:
- Constructed a baseline openEHR data model using literature, genomic data, and international specifications.
- Refined the model through expert workshops with the Global Alliance for Genomics and Health.
- Validated the model via peer review, mapping to HL7 FHIR, and automated transformation tools.
Main Results:
- Developed a standardized pharmacogenetic data model separating test results from therapeutic implications.
- Incorporated recognized terminologies (SNOMED CT, HGNC) and achieved international consensus.
- Demonstrated bidirectional information flow with HL7 FHIR, enabling scalable integration.
Conclusions:
- The study provides a framework for storing and exchanging pharmacogenetic test results.
- The open data standards support semantic harmonization and interoperability.
- This work lays the foundation for widespread clinical implementation of pharmacogenetics.
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