The client, one of the global leaders in precision medicine, uses genomic analytics to generate actionable healthcare insights for enhancing patient care.
The Challenge
The client leverages artificial intelligence-powered algorithms for data management and uses personalized genetic data to predict the impact of genetics in ophthalmology, oncology, and infectious diseases.
They managed large molecular data that catered to a diverse range of users, including computational biologists, clinical researchers, and health economics outcomes researchers, each with unique requirements for varying levels of molecular data resolution.
This generation of molecular data records involved multiple software systems owned by different teams, each having its own internal data representations. This posed a significant challenge to achieving widespread data interoperability and creating analysis-ready content for computational biologists, clinical researchers, etc.
Therefore, there was a lack of clear traceability to the source and reference data, prompting the client to seek a solution for this issue.
Approach and Solution
- Standardized approach: Persistent aimed at establishing and implementing a standardized approach for encoding and decoding common molecular variations.
- Establishing a single source of truth: Created a library to enable the tracing of molecular alterations from detection events to characterization and reporting. This ensured that researchers had access to a reliable and consistent source of information at any level of data resolution.
- Enhancing data representation and interoperability: The library extends the Variant Representation Specification, allowing for comprehensive representation of molecular data models.
- Improved traceability: Improved the traceability of data to its sources and references, promoting unambiguous data interpretation. Furthermore, it enhanced interoperability and facilitated the generation of analysis-ready content for downstream consumers, making it easier for different systems and tools to work together effectively.
Benefits
- Streamlined and accelerated interoperability
- Accelerated data integration
- Efficient data utilization
- Automated and reliable traceability
