Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure...

Area of Science:

• Genomics
• Pharmacogenetics
• Health Informatics

Background:

• Blockchain distributed ledger technology is emerging in genomics and healthcare, but practical applications beyond proof-of-concept are limited.
• Skepticism persists regarding the real-world feasibility of blockchain in biomedical research.
• Sharing gene-drug interaction records is crucial for advancing personalized medicine.

Purpose of the Study:

• To benchmark blockchain strategies for distributed sharing of gene-drug interaction records.
• To evaluate the practicality of blockchain technology in genomic and healthcare applications.
• To demonstrate the potential of blockchain to expedite personalized medicine.

Main Methods:

• Generated gene-drug interaction datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource.
• Developed and compared three blockchain-based methods: Query Index, Index Everything, and Dual-Scenario Indexing.
• Benchmarked data import and retrieval performance across distributed sites.

Main Results:

• Achieved a runtime of approximately 60 seconds for importing 4,000 gene-drug interaction records from four sites.
• Demonstrated a data retrieval query time of about 0.5 seconds.
• Confirmed the feasibility of using blockchain as a platform for inter-institutional data sharing.

Conclusions:

• Blockchain-based methods are effective for sharing patient outcomes related to gene-drug interactions.
• Findings support the utilization of blockchain in healthcare, genomics, and biomedical research.
• The developed source code is publicly available for further research and implementation.