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Adanur Dedeturk B, Soran A, Bakir-Gungor B. Blockchain for genomics and healthcare: a literature review, current status, classification and open issues. PeerJ 2021; 9:e12130. [PMID: 34703661 PMCID: PMC8487622 DOI: 10.7717/peerj.12130] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 08/17/2021] [Indexed: 11/20/2022] Open
Abstract
The tremendous boost in the next generation sequencing technologies and in the "omics" technologies resulted in the generation of hundreds of gigabytes of data per day. Nowadays, via integrating -omics data with other data types, such as imaging and electronic health record (EHR) data, panomics studies attempt to identify novel and potentially actionable biomarkers for personalized medicine applications. In this respect, for the accurate analysis of -omics data and EHR, there is a need to establish secure and robust pipelines that take the ethical aspects into consideration, regulate privacy and ownership issues, and data sharing. These days, blockchain technology has picked up significant attention in diverse fields, including genomics, since it offers a new solution for these problems from a different perspective. Blockchain is an immutable transaction ledger, which offers secure and distributed system without a central authority. Within the system, each transaction can be expressed with cryptographically signed blocks, and the verification of transactions is performed by the users of the network. In this review, firstly, we aim to highlight the challenges of EHR and genomic data sharing. Secondly, we attempt to answer "Why" or "Why not" the blockchain technology is suitable for genomics and healthcare applications in detail. Thirdly, we elucidate the general blockchain structure based on the Ethereum, which is a more suitable technology for the genomic data sharing platforms. Fourthly, we review current blockchain-based EHR and genomic data sharing platforms, evaluate the advantages and disadvantages of these applications, and classify these applications using different metrics. Finally, we conclude by discussing the open issues and introducing our suggestion on the topic. In summary, to facilitate the diagnosis, monitoring and therapy of diseases with the effective analysis of -omics data with other available data types, through this review, we put forward the possible implications of the blockchain technology to life sciences and healthcare.
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Affiliation(s)
| | - Ahmet Soran
- Department of Computer Engineering, Abdullah Gul University, Kayseri, Turkey
| | - Burcu Bakir-Gungor
- Department of Computer Engineering, Abdullah Gul University, Kayseri, Turkey
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Wang S, Bonomi L, Dai W, Chen F, Cheung C, Bloss CS, Cheng S, Jiang X. Big Data Privacy in Biomedical Research. IEEE TRANSACTIONS ON BIG DATA 2020; 6:296-308. [PMID: 32478127 PMCID: PMC7258042 DOI: 10.1109/tbdata.2016.2608848] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Biomedical research often involves studying patient data that contain personal information. Inappropriate use of these data might lead to leakage of sensitive information, which can put patient privacy at risk. The problem of preserving patient privacy has received increasing attentions in the era of big data. Many privacy methods have been developed to protect against various attack models. This paper reviews relevant topics in the context of biomedical research. We discuss privacy preserving technologies related to (1) record linkage, (2) synthetic data generation, and (3) genomic data privacy. We also discuss the ethical implications of big data privacy in biomedicine and present challenges in future research directions for improving data privacy in biomedical research.
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Affiliation(s)
- Shuang Wang
- Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093
| | - Luca Bonomi
- Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093
| | - Wenrui Dai
- Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093
| | - Feng Chen
- Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093
| | - Cynthia Cheung
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093
| | - Cinnamon S Bloss
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093
| | - Samuel Cheng
- School of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, 74135
| | - Xiaoqian Jiang
- Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093
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Paddock S, Abedtash H, Zummo J, Thomas S. Proof-of-concept study: Homomorphically encrypted data can support real-time learning in personalized cancer medicine. BMC Med Inform Decis Mak 2019; 19:255. [PMID: 31801535 PMCID: PMC6894133 DOI: 10.1186/s12911-019-0983-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Accepted: 11/14/2019] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The successful introduction of homomorphic encryption (HE) in clinical research holds promise for improving acceptance of data-sharing protocols, increasing sample sizes, and accelerating learning from real-world data (RWD). A well-scoped use case for HE would pave the way for more widespread adoption in healthcare applications. Determining the efficacy of targeted cancer treatments used off-label for a variety of genetically defined conditions is an excellent candidate for introduction of HE-based learning systems because of a significant unmet need to share and combine confidential data, the use of relatively simple algorithms, and an opportunity to reach large numbers of willing study participants. METHODS We used published literature to estimate the numbers of patients who might be eligible to receive treatments approved for other indications based on molecular profiles. We then estimated the sample size and number of variables that would be required for a successful system to detect exceptional responses with sufficient power. We generated an appropriately sized, simulated dataset (n = 5000) and used an established HE algorithm to detect exceptional responses and calculate total drug exposure, while the data remained encrypted. RESULTS Our results demonstrated the feasibility of using an HE-based system to identify exceptional responders and perform calculations on patient data during a hypothetical 3-year study. Although homomorphically encrypted computations are time consuming, the required basic computations (i.e., addition) do not pose a critical bottleneck to the analysis. CONCLUSION In this proof-of-concept study, based on simulated data, we demonstrate that identifying exceptional responders to targeted cancer treatments represents a valuable and feasible use case. Past solutions to either completely anonymize data or restrict access through stringent data use agreements have limited the utility of abundant and valuable data. Because of its privacy protections, we believe that an HE-based learning system for real-world cancer treatment would entice thousands more patients to voluntarily contribute data through participation in research studies beyond the currently available secondary data populated from hospital electronic health records and administrative claims. Forming collaborations between technical experts, physicians, patient advocates, payers, and researchers, and testing the system on existing RWD are critical next steps to making HE-based learning a reality in healthcare.
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Affiliation(s)
- Silvia Paddock
- Rose Li and Associates, Inc., 1101 Wootton Pkwy, Suite 400A, Rockville, MD, 20852, USA.
| | - Hamed Abedtash
- Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, 46285, USA
| | - Jacqueline Zummo
- Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, 46285, USA
| | - Samuel Thomas
- Rose Li and Associates, Inc., 1101 Wootton Pkwy, Suite 400A, Rockville, MD, 20852, USA
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Wang S, Jiang X, Singh S, Marmor R, Bonomi L, Fox D, Dow M, Ohno-Machado L. Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States. Ann N Y Acad Sci 2017; 1387:73-83. [PMID: 27681358 PMCID: PMC5266631 DOI: 10.1111/nyas.13259] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 08/18/2016] [Accepted: 08/22/2016] [Indexed: 12/28/2022]
Abstract
Accessing and integrating human genomic data with phenotypes are important for biomedical research. Making genomic data accessible for research purposes, however, must be handled carefully to avoid leakage of sensitive individual information to unauthorized parties and improper use of data. In this article, we focus on data sharing within the scope of data accessibility for research. Current common practices to gain biomedical data access are strictly rule based, without a clear and quantitative measurement of the risk of privacy breaches. In addition, several types of studies require privacy-preserving linkage of genotype and phenotype information across different locations (e.g., genotypes stored in a sequencing facility and phenotypes stored in an electronic health record) to accelerate discoveries. The computer science community has developed a spectrum of techniques for data privacy and confidentiality protection, many of which have yet to be tested on real-world problems. In this article, we discuss clinical, technical, and ethical aspects of genome data privacy and confidentiality in the United States, as well as potential solutions for privacy-preserving genotype-phenotype linkage in biomedical research.
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Affiliation(s)
- Shuang Wang
- Department of Biomedical Informatics, University of California San Diego, La Jolla, California
| | - Xiaoqian Jiang
- Department of Biomedical Informatics, University of California San Diego, La Jolla, California
| | - Siddharth Singh
- Department of Biomedical Informatics, University of California San Diego, La Jolla, California
| | - Rebecca Marmor
- Department of Biomedical Informatics, University of California San Diego, La Jolla, California
| | - Luca Bonomi
- Department of Biomedical Informatics, University of California San Diego, La Jolla, California
| | - Dov Fox
- School of Law, University of San Diego, San Diego, California
| | - Michelle Dow
- Department of Biomedical Informatics, University of California San Diego, La Jolla, California
| | - Lucila Ohno-Machado
- Department of Biomedical Informatics, University of California San Diego, La Jolla, California
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Delaney SK, Hultner ML, Jacob HJ, Ledbetter DH, McCarthy JJ, Ball M, Beckman KB, Belmont JW, Bloss CS, Christman MF, Cosgrove A, Damiani SA, Danis T, Delledonne M, Dougherty MJ, Dudley JT, Faucett WA, Friedman JR, Haase DH, Hays TS, Heilsberg S, Huber J, Kaminsky L, Ledbetter N, Lee WH, Levin E, Libiger O, Linderman M, Love RL, Magnus DC, Martland A, McClure SL, Megill SE, Messier H, Nussbaum RL, Palaniappan L, Patay BA, Popovich BW, Quackenbush J, Savant MJ, Su MM, Terry SF, Tucker S, Wong WT, Green RC. Toward clinical genomics in everyday medicine: perspectives and recommendations. Expert Rev Mol Diagn 2016; 16:521-32. [PMID: 26810587 PMCID: PMC4841021 DOI: 10.1586/14737159.2016.1146593] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Precision or personalized medicine through clinical genome and exome sequencing has been described by some as a revolution that could transform healthcare delivery, yet it is currently used in only a small fraction of patients, principally for the diagnosis of suspected Mendelian conditions and for targeting cancer treatments. Given the burden of illness in our society, it is of interest to ask how clinical genome and exome sequencing can be constructively integrated more broadly into the routine practice of medicine for the betterment of public health. In November 2014, 46 experts from academia, industry, policy and patient advocacy gathered in a conference sponsored by Illumina, Inc. to discuss this question, share viewpoints and propose recommendations. This perspective summarizes that work and identifies some of the obstacles and opportunities that must be considered in translating advances in genomics more widely into the practice of medicine.
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Affiliation(s)
- Susan K Delaney
- a Coriell Institute for Medical Research , Camden , NJ , USA
| | - Michael L Hultner
- b Lockheed Martin , Information Systems & Global Solutions , Rockville , MD , USA
| | - Howard J Jacob
- c HudsonAlpha Institute for Biotechnology , Huntsville , AL , USA
| | | | - Jeanette J McCarthy
- e Duke University , Center for Applied Genomics and Precision Medicine , Durham , NC , USA
| | | | - Kenneth B Beckman
- g University of Minnesota , Genomics Center ,, Minneapolis , MN , USA
| | - John W Belmont
- h Baylor College of Medicine , Children's Nutrition Research Center , Houston , TX , USA
| | - Cinnamon S Bloss
- i University of California, San Diego , School of Medicine , La Jolla , CA , USA
| | | | | | - Stephen A Damiani
- k Mission Massimo Foundation , Elsternwick , VIC , Australia .,l Mission Massimo Foundation Inc ., Westlake Village , CA , USA
| | | | | | - Michael J Dougherty
- o The American Society of Human Genetics , Bethesda , MD , USA.,p Department of Pediatrics , University of Colorado School of Medicine , Aurora , CO , USA
| | - Joel T Dudley
- q Icahn School of Medicine at Mount Sinai , New York , NY , USA
| | | | - Jennifer R Friedman
- r University of California, San Diego , Departments of Neurosciences and Pediatrics and Rady Children's Hospital , San Diego , CA , USA
| | | | - Tom S Hays
- t University of Minnesota , Department of Genetics, Cell Biology and Development , Minneapolis , MN , USA
| | | | - Jeff Huber
- u Google Inc ., Mountain View , CA , USA
| | | | | | | | - Elissa Levin
- q Icahn School of Medicine at Mount Sinai , New York , NY , USA
| | | | | | | | - David C Magnus
- y Stanford Center for Biomedical Ethics , Stanford School of Medicine , Stanford , CA , USA
| | | | | | | | - Helen Messier
- ab Healix Health, Ltd , West Vancouver , BC , Canada
| | | | | | | | | | | | | | - Michael M Su
- ai Anthem Blue Cross , Woodland Hills , CA , USA
| | | | - Steven Tucker
- ak Novena Specialist Center , Singapore , Republic of Singapore
| | | | - Robert C Green
- am Division of Genetics, Department of Medicine, Brigham and Women's Hospital , the Broad Institute, Harvard Medical School and Partners Healthcare Personalized Medicine , Boston , MA , USA
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