TY - JOUR

T1 - Benchmarking blockchain-based gene-drug interaction data sharing methods

T2 - A case study from the iDASH 2019 secure genome analysis competition blockchain track

AU - Kuo, Tsung-Ting

AU - Bath, Tyler

AU - Ma, Shuaicheng

AU - Pattengale, Nicholas

AU - Yang, Meng

AU - Cao, Yang

AU - Hudson, Corey M.

AU - Kim, Jihoon

AU - Post, Kai

AU - Xiong, Li

AU - Ohno-Machado, Lucila

N1 - Publisher Copyright: © 2021

PY - 2021

Y1 - 2021

N2 - Background: 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. Basic Procedures: 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. Main Findings: 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. Principal Conclusions: We show the benchmarking results of novel blockchain-based methods for institutions to share patient outcomes related to gene-drug interactions. Our findings support blockchain utilization in healthcare, genomic and biomedical applications. The source code is publicly available at https://github.com/tsungtingkuo/genedrug.

AB - Background: 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. Basic Procedures: 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. Main Findings: 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. Principal Conclusions: We show the benchmarking results of novel blockchain-based methods for institutions to share patient outcomes related to gene-drug interactions. Our findings support blockchain utilization in healthcare, genomic and biomedical applications. The source code is publicly available at https://github.com/tsungtingkuo/genedrug.

KW - Blockchain Distributed Ledger Technology

KW - Data Sharing

KW - Gene-Drug Interaction

KW - Pharmacogenetics

KW - Smart Contract

U2 - 10.1016/j.ijmedinf.2021.104559

DO - 10.1016/j.ijmedinf.2021.104559

M3 - Journal article

C2 - 34474309

AN - SCOPUS:85114026664

VL - 154

JO - International Journal of Medical Informatics

JF - International Journal of Medical Informatics

SN - 1386-5056

M1 - 104559

ER -