Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track

Kuo, Tsung-Ting; Bath, Tyler; Ma, Shuaicheng; Pattengale, Nicholas; Yang, Meng; Cao, Yang; Hudson, Corey M.; Kim, Jihoon; Post, Kai; Xiong, Li; Ohno-Machado, Lucila

doi:10.1016/j.ijmedinf.2021.104559

Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track

Journal Article · Wed Aug 18 00:00:00 EDT 2021 · International Journal of Medical Informatics

DOI:https://doi.org/10.1016/j.ijmedinf.2021.104559· OSTI ID:1831161

Kuo, Tsung-Ting ^[1]; Bath, Tyler ^[1]; Ma, Shuaicheng ^[2]; Pattengale, Nicholas ^[3]; Yang, Meng ^[4]; Cao, Yang ^[5]; Hudson, Corey M. ^[3]; Kim, Jihoon ^[1]; Post, Kai ^[1]; Xiong, Li ^[2]; Ohno-Machado, Lucila ^[6]

Univ. of California San Diego, La Jolla, CA (United States)
Emory Univ., Atlanta, GA (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
BGI-Shenzhen, Guangdong (China); Univ. of Copenhagen (Denmark)
Kyoto Univ. (Japan)
Univ. of California San Diego, La Jolla, CA (United States); VA San Diego Healthcare System, CA (United States)

Blockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine. We generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing. We achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: NA0003525

OSTI ID:: 1831161

Report Number(s):: SAND--2021-11263J; 699322

Journal Information:: International Journal of Medical Informatics, Journal Name: International Journal of Medical Informatics Vol. 154; ISSN 1386-5056

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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60 APPLIED LIFE SCIENCES
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Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track

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