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Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts
BACKGROUND: As pharmacogenomics data becomes increasingly integral to clinical treatment decisions, appropriate data storage and sharing protocols need to be adopted. One promising option for secure, high-integrity storage and sharing is Ethereum smart contracts. Ethereum is a blockchain platform, a...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268467/ https://www.ncbi.nlm.nih.gov/pubmed/32487214 http://dx.doi.org/10.1186/s12920-020-00732-x |
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author | Gürsoy, Gamze Brannon, Charlotte M. Gerstein, Mark |
author_facet | Gürsoy, Gamze Brannon, Charlotte M. Gerstein, Mark |
author_sort | Gürsoy, Gamze |
collection | PubMed |
description | BACKGROUND: As pharmacogenomics data becomes increasingly integral to clinical treatment decisions, appropriate data storage and sharing protocols need to be adopted. One promising option for secure, high-integrity storage and sharing is Ethereum smart contracts. Ethereum is a blockchain platform, and smart contracts are immutable pieces of code running on virtual machines in this platform that can be invoked by a user or another contract (in the blockchain network). The 2019 iDASH (Integrating Data for Analysis, Anonymization, and Sharing) competition for Secure Genome Analysis challenged participants to develop time- and space-efficient Ethereum smart contracts for gene-drug relationship data. METHODS: Here we design a specific smart contract to store and query gene-drug interactions in Ethereum using an index-based, multi-mapping approach. Our contract stores each pharmacogenomics observation, a gene-variant-drug triplet with outcome, in a mapping searchable by a unique identifier, allowing for time and space efficient storage and query. This solution ranked in the top three at the 2019 IDASH competition. We further improve our ”challenge solution” and develop an alternate ”fastQuery” smart contract, which combines together identical gene-variant-drug combinations into a single storage entry, leading to significantly better scalability and query efficiency. RESULTS: On a private, proof-of-authority network, both our challenge and fastQuery solutions exhibit approximately linear memory and time usage for inserting into and querying small databases (<1,000 entries). For larger databases (1000 to 10,000 entries), fastQuery maintains this scaling. Furthermore, both solutions can query by a single field (”0-AND”) or a combination of fields (”1- or 2-AND”). Specifically, the challenge solution can complete a 2-AND query from a small database (100 entries) in 35ms using 0.1 MB of memory. For the same query, fastQuery has a 2-fold improvement in time and a 10-fold improvement in memory. CONCLUSION: We show that pharmacogenomics data can be stored and queried efficiently using Ethereum blockchain. Our solutions could potentially be used to store a range of clinical data and extended to other fields requiring high-integrity data storage and efficient access. |
format | Online Article Text |
id | pubmed-7268467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72684672020-06-07 Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts Gürsoy, Gamze Brannon, Charlotte M. Gerstein, Mark BMC Med Genomics Technical Advance BACKGROUND: As pharmacogenomics data becomes increasingly integral to clinical treatment decisions, appropriate data storage and sharing protocols need to be adopted. One promising option for secure, high-integrity storage and sharing is Ethereum smart contracts. Ethereum is a blockchain platform, and smart contracts are immutable pieces of code running on virtual machines in this platform that can be invoked by a user or another contract (in the blockchain network). The 2019 iDASH (Integrating Data for Analysis, Anonymization, and Sharing) competition for Secure Genome Analysis challenged participants to develop time- and space-efficient Ethereum smart contracts for gene-drug relationship data. METHODS: Here we design a specific smart contract to store and query gene-drug interactions in Ethereum using an index-based, multi-mapping approach. Our contract stores each pharmacogenomics observation, a gene-variant-drug triplet with outcome, in a mapping searchable by a unique identifier, allowing for time and space efficient storage and query. This solution ranked in the top three at the 2019 IDASH competition. We further improve our ”challenge solution” and develop an alternate ”fastQuery” smart contract, which combines together identical gene-variant-drug combinations into a single storage entry, leading to significantly better scalability and query efficiency. RESULTS: On a private, proof-of-authority network, both our challenge and fastQuery solutions exhibit approximately linear memory and time usage for inserting into and querying small databases (<1,000 entries). For larger databases (1000 to 10,000 entries), fastQuery maintains this scaling. Furthermore, both solutions can query by a single field (”0-AND”) or a combination of fields (”1- or 2-AND”). Specifically, the challenge solution can complete a 2-AND query from a small database (100 entries) in 35ms using 0.1 MB of memory. For the same query, fastQuery has a 2-fold improvement in time and a 10-fold improvement in memory. CONCLUSION: We show that pharmacogenomics data can be stored and queried efficiently using Ethereum blockchain. Our solutions could potentially be used to store a range of clinical data and extended to other fields requiring high-integrity data storage and efficient access. BioMed Central 2020-06-01 /pmc/articles/PMC7268467/ /pubmed/32487214 http://dx.doi.org/10.1186/s12920-020-00732-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Technical Advance Gürsoy, Gamze Brannon, Charlotte M. Gerstein, Mark Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts |
title | Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts |
title_full | Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts |
title_fullStr | Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts |
title_full_unstemmed | Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts |
title_short | Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts |
title_sort | using ethereum blockchain to store and query pharmacogenomics data via smart contracts |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268467/ https://www.ncbi.nlm.nih.gov/pubmed/32487214 http://dx.doi.org/10.1186/s12920-020-00732-x |
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