Researchers at UC San Francisco say they have successfully developed and validated the feasibility of using blockchain technology to securely share clinical trial data.
The way the proof-of-concept web portal operates is that each time new data is entered on a trial participant, the sender, receiver, timestamp and file attachment containing the data—as well as the hash of the previous block of data pertaining to that patient—is recorded onto a new block with its own distinct signature.
“We showed that a blockchain-based file and data structure could be used to reliably safeguard data in a clinical trials network, and provide an immutable and fully traceable audit trail,” conclude the authors of a study published on Friday in the journal Nature Communications.
By using clinical trials data from a previously completed major study, the researchers contend that they demonstrated how “data entry, storage and adverse event reporting can be performed in a more robust and secure manner, which could withstand attacks from both other people in the network and infrastructure damage at the storage level.”
“It makes it really obvious when someone’s changing something,” says co-author Daniel Wong, a Ph.D. candidate in biological and medical informatics at UCSF, who built the blockchain system to operate via a web portal. “You can see who put their hands on it, who made it, who changed it and who received it.”
According to the researchers, the auditing of data for regulators of clinical trials—such as the Food and Drug Administration—is challenging given that there is no easy and secure way of accessing or viewing the complex network of data transactions as they happen.
What differentiates UCSF’s clinical trial prototype from most decentralized blockchain applications is that it relies on having a regulator with centralized authority—such as the FDA—to operate the web portal, register all parties, and keep a ledger of the blockchain’s hashes.
“Everyone is talking about how blockchain is going to revolutionize many of the data challenges in medicine, and here is one use that finally might make sense,” says co-author Atul Butte, MD, who is the Priscilla Chan and Mark Zuckerberg Distinguished Professor and director of the Bakar Computational Health Sciences Institute at UCSF. “We think it could someday be useful for pharma companies running clinical trials.”