Blockchain Protocols In Clinical Trials: Transparency And Traceability Of Consent

Mehdi Benchoufi
Raphael Porcher
Philippe Ravaud
Clinical trial consent for protocols and their revisions should be transparent for patients and traceable for stakeholders. Our goal is to implement a process allowing the collection of patients’ informed consent, which is bound to protocol revisions, storing and tracking the consent in a secure, unfalsifiable and publicly verifiable way, and enabling the sharing of this information in real time. For that, we will built a consent workflow using a rising technology called Blockchain. This is a distributed technology that brings a built-in layer of transparency and traceability. Additionally, it removes the need for third parties, and gives participative control to the peer-to-peer users. From a more general and prospective point of view, we believe Blockchain technology brings a paradigmatical shift to the entire clinical research field. We designed a Proof-of-Concept protocol consisting of time-stamping each step of the patient’s consent collection using Blockchain; thus archiving and historicising the consent through cryptographic validation in a securely unfalsifiable and transparent way. For each revision of the protocol, consent was sought again. We obtained a single document, in a standard open format, that accounted for the whole consent collection process: timestamped consent status with regards to each version of the protocol. This document cannot be corrupted, and can be checked on any dedicated public website. It should be considered as a robust proof of data. In the future, we think that the complex data flow of a clinical trial can be tracked using Blockchain. Moreover, a blockchain core functionality, named Smart Contract, can help prevent clinical trial events not to happen in the right chronological order: including patients before they consented or analysing case report forms data before freezing the database. This will help reaching reliability, security, and transparency, and could be a consistent step towards reproducibility.

Metadata

Year 2017
Peer Reviewed done
Venue F1000Research
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