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Dynamic consent management for clinical trials via private blockchain technology


Clinical trials (CTs) are essential for the advancement of medical research, paving the way for the development and adoption of new treatments, and contributing to the evolution of healthcare. An essential factor for the success of a CT is the appropriate management of its participants and their personal data. According to the current regulations, collecting and using personal data from participants must comply with rigorous standards. Therefore, healthcare institutes need to obtain freely given, specific, informed, and unambiguous consent before being able to collect the data. Some of the major limitations of the current technological solutions are the lack of control over the granularity of consent grants, as well as the difficulty of handling dynamic changes of consent over time. In this paper, we present SCoDES, an approach for trusted and decentralized management of dynamic consent in clinical trials, based on blockchain technology (BCT). The usage of blockchain provides a set of features that allow maintaining consent information with trust guarantees while avoiding the need for a dedicated or centralized third trusted party. We provide a full implementation of SCoDES, made available as a self-contained infrastructure, with the possibility to interact with external services, and using hyperledger as a blockchain framework.

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  1. A blockchain is permissioned if the identities of the users and rights to participate in the consensus (writing to the ledger and/or validating the transactions) are controlled by a membership service.

  2. CDISC:

  3. An EDC is a computerized system designed for the collection of clinical data in electronic format for use mainly in human clinical trials.

  4. Hyperledger is an open-source collaborative effort created to advance cross-industry blockchain technologies. It is a global collaboration, hosted by The Linux Foundation, including leaders in finance, banking, Internet of Things, supply chains, manufacturing and Technology (IBM 2019).

  5. A consensus algorithm defines the mechanisms ruling agreement among several peers about the correctness and security of a given transaction.

  6. Business network refers to a blockchain application developed with hyperledger composer.

  7. Every operation that needs to communicate with the blockchain network needs to be authenticated. To avoid redundancy, this step is omitted in the next descriptions.

  8. For the purposes of the study, a custom definition of the trial has been used.

  9. REDCap-Tools is a non-official organization that provides several interfaces and project using REDCap, helping developers to exploit REDCap’s advanced functions to their full potential (Burns et al. 2019).

  10. Data coming from different platforms concerning the same user.


  • Agbo CC, Mahmoud QH, Eklund JM (2019) Blockchain technology in healthcare: a systematic review. In: Healthcare, vol 7. MDPI, Basel, p 56

  • Angeletti F, Chatzigiannakis I, Vitaletti A (2017) The role of blockchain and iot in recruiting participants for digital clinical trials. In: 2017 25th international conference on software, telecommunications and computer networks (SoftCOM). IEEE, pp 1–5

  • Anjomshoae S, Najjar A, Calvaresi D, Främling K (2019) Explainable agents and robots: results from a systematic literature review. In: Proceedings of the 18th international conference on autonomous agents and multiagent systems, international foundation for autonomous agents and multiagent systems. ACM, New York, pp 1078–1088

  • Association WM (2013) WMA declaration of Helsinki—ethical principles for medical research involving human subjects.

  • Atasoy H, Greenwood BN, McCullough JS (2018) The digitization of patient care: a review of the effects of electronic health records on health care quality and utilization. Annu Rev Public Health 40:487–500

    Article  Google Scholar 

  • Beierle F, Tran VT, Allemand M, Neff P, Schlee W, Probst T, Zimmermann J, Pryss R (2019) What data are smartphone users willing to share with researchers? J Ambient Intell Human Comput.

    Article  Google Scholar 

  • Benchoufi M, Porcher R, Ravaud P (2017) Blockchain protocols in clinical trials: transparency and traceability of consent. F1000Research.

    Article  Google Scholar 

  • Burns S, Beasley W, Zhu H (2019) Redcap-tools.

  • Cachin C, Vukolić M (2017) Blockchains consensus protocols in the wild. arXiv:1707.01873

  • Calvaresi D, Cesarini D, Sernani P, Marinoni M, Dragoni AF, Sturm A (2017) Exploring the ambient assisted living domain: a systematic review. J Ambient Intell Humaniz Comput 8(2):239–257

    Article  Google Scholar 

  • Calvaresi D, Dubovitskaya A, Calbimonte JP, Taveter K, Schumacher M (2018) Multi-agent systems and blockchain: results from a systematic literature review. International conference on practical applications of agents and multi-agent systems. Springer, Cham, pp 110–126

    Google Scholar 

  • Calvaresi D, Calbimonte JP, Dubovitskaya A, Mattioli V, Piguet JG, Schumacher M (2019a) The good, the bad, and the ethical implications of bridging blockchain and multi-agent systems. Information 10(12):363

    Article  Google Scholar 

  • Calvaresi D, Mualla Y, Najjar A, Galland S, Schumacher M (2019b) Explainable multi-agent systems through blockchain technology. In: Proc. of explainable, transparent autonomous agents and multi-agent systems. EXTRAAMAS 2019, vol 11763. Springer, Cham, pp 41–58

  • Casino F, Dasaklis TK, Patsakis C (2019) A systematic literature review of blockchain-based applications: current status, classification and open issues. Telemat Inform 36:55–81

    Article  Google Scholar 

  • Compert C, Luinetti M, Portier B (2018) Blockchain and GDPR: How blockchain could address five areas associated with GDPR compliance. Technical report. IBM Security

  • Crosby M, Pattanayak P, Verma S, Kalyanaraman V et al (2016) Blockchain technology: beyond bitcoin. Appl Innov 2(6–10):71

    Google Scholar 

  • Davis TC, Berkel HJ, Holcombe RF, Pramanik S, Divers SG (1998) Informed consent for clinical trials: a comparative study of standard versus simplified forms. JNCI J Natl Cancer Inst 90(9):668–674

    Article  Google Scholar 

  • Drosatos G, Kaldoudi E (2019) Blockchain applications in the biomedical domain: a scoping review. Comput Struct Biotechnol J.

    Article  Google Scholar 

  • EU (2019) Eugdpr.

  • Friedman LM, Furberg C, DeMets DL, Reboussin DM, Granger CB et al (2010) Fundamentals of clinical trials, vol 4. Springer, Cham

    Book  Google Scholar 

  • Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG (2009) Research electronic data capture (redcap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 42(2):377–381

    Article  Google Scholar 

  • IBM (2019) Hyperledger framework. Accessed: 30 Apr 2019

  • Inc F (2019) React—a javascript library for building user interfaces.

  • Jahankhani H, Kendzierskyj S (2019) Digital transformation of healthcare. In: Jahankhani H, Kendzierskyj S, Jamal A, Epiphaniou G, Al-Khateeb H (eds) Blockchain and clinical trial: securing patient data, Springer International Publishing, Cham, pp 31–52.

  • Jaschinski C, Allouch SB (2019) Listening to the ones who care: exploring the perceptions of informal caregivers towards ambient assisted living applications. J Ambient Intell Humaniz Comput 10(2):761–778

    Article  Google Scholar 

  • Kaye J, Whitley EA, Lund D, Morrison M, Teare H, Melham K (2015) Dynamic consent: a patient interface for twenty-first century research networks. Eur J Hum Genet 23(2):141

    Article  Google Scholar 

  • Krenn R (2014) Design and development of a web-based clinical trial management system. PhD thesis, Graz University of Technology.

  • Lee E, Yoon Y (2019) Trusted information project platform based on blockchain for sharing strategy. J Ambient Intell Hum Comput.

    Article  Google Scholar 

  • LLC O (2019) Openclinica reference guide.

  • Lorell BH, Mikita JS, Anderson A, Hallinan ZP, Forrest A (2015) Informed consent in clinical research: consensus recommendations for reform identified by an expert interview panel. Clin Trials 12(6):692–695

    Article  Google Scholar 

  • Maslove DM, Klein J, Brohman K, Martin P (2018) Using blockchain technology to manage clinical trials data: a proof-of-concept study. JMIR Med Inform 6:e11949.

    Article  Google Scholar 

  • Mulder T, Tudorica M (2019) Privacy policies, cross-border health data and the gdpr. Inf Commun Technol Law 28:261–274

    Article  Google Scholar 

  • Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system.

  • Neisse R, Baldini G, Steri G, Miyake Y, Kiyomoto S, Biswas AR (2015) An agent-based framework for informed consent in the internet of things. In: 2015 IEEE 2nd world forum on internet of things (WF-IoT). IEEE, NJ, pp 789–794

  • Nugent T, Upton D, Cimpoesu M (2016) Improving data transparency in clinical trials using blockchain smart contracts. F1000Research.

    Article  Google Scholar 

  • Pocock SJ (2013) Clinical trials: a practical approach. Wiley, Chichester

    Book  Google Scholar 

  • Rantos K, Drosatos G, Demertzis K, Ilioudis C, Papanikolaou A, Kritsas A (2018) Advocate: a consent management platform for personal data processing in the iot using blockchain technology. In: International conference on security for information technology and communications, Springer, pp 300–313

  • Richardson L, Ruby S (2008) RESTful web services. O’Reilly Media, Inc., Sebastopol

  • University V (2019) Redcap—research electronic data capture.

  • Vimal S, Srivatsa S (2019) A new cluster p2p file sharing system based on ipfs and blockchain technology. J Ambient Intell Hum Comput.

    Article  Google Scholar 

  • Yaga D, Mell P, Roby N, Scarfone K (2019) Blockchain technology overview. arXiv:1906.11078

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The authors want to acknowledge the SCoDES project supporting this study.

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Correspondence to Davide Calvaresi.

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Albanese, G., Calbimonte, JP., Schumacher, M. et al. Dynamic consent management for clinical trials via private blockchain technology. J Ambient Intell Human Comput 11, 4909–4926 (2020).

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