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Blockchain Prototype Designed for Clinical Trial Data

Network illustration

(Gerd Altmann, Pixabay)

22 Feb. 2019. A bioinformatics lab developed a prototype system for securely transmitting and storing clinical trial data with blockchain that protects against corrupting trial records. A team from University of California in San Francisco describes the system in today’s issue of the journal Nature Communications.

Researchers from the UC-San Francisco lab of data scientist Atul Butte are look for better ways of securing sensitive data produced in clinical trials. Among the needs of medical researchers conducting clinical trials are ensuring the integrity and immutability of data collected on or by participants in trials, which are subject to risks of error and fraud. The authors cite reports of fabricated results and reliance on manual processes that heighten the chance of unintentional errors. And because of few standard protocols in the conduct of clinical trials, there are few guarantees of transparency or traceability of data.

Butte and colleagues propose adapting blockchain technology to manage these risks. Blockchain is a system for capturing data about transactions in a network, but with the data distributed among the various parties to the transactions. Data about a transaction are broken up into blocks, with each block connected in a chain. Each block is also time-stamped and encrypted with an algorithm giving it a unique identifier or fingerprint, also linked mathematically to the previous block in the chain. This linking of uniquely identified and encrypted blocks in the chain ensures the integrity of the data, as well as protects the data from hacking.

The system recommended by the UC-San Francisco team, however, deviates from the pure decentralized blockchain model. The researchers instead propose a web-based portal with a neutral central authority to register all parties and maintain the identifier ledgers. An interactive voice-response system would assign unique verification codes, with each transaction, such as enrolling new participants or reporting clinical data, generating new blocks and adding to the chain. Each transaction would record the parties, timestamp, file attachments, and previous block hash, then joined together and hashed with a common encryption algorithm, such as SHA-256. Upon completion of the trial, the complete chain would be made available to regulatory authorities, such as Food and Drug Administration, as part of the drug approval review process.

The UC-San Francisco system adds expedited adverse effects reporting to the blockchain system as well. In the system, reports of adverse effects are sent directly to the trial’s data safety management board, since participant health and safety are at stake. Under most current protocols, adverse effects are reported through a chain of command, taking several steps and often extended periods of time.

The researchers tested the system with real-life clinical trial data maintained at UC-San Francisco in its ImmPort repository, an NIH-funded portal on immunology. The data are from a completed mid-stage trial testing the drug omalizumab, marketed as Xolair by Genentech, to treat hay fever and other ragweed allergies. The team performed realistic transactions in the trial, but also simulated errors, such as exchanging participants originally assigned to treatment or placebo groups. The blockchain, says the researchers, highlights the error and when it occurs. Likewise, the team simulated a study supervisor erasing adverse effect reports, but the blockchain records and adds those attempts to the transaction chain, again with the parties and timestamp noted.

The researchers believe that their system may not eliminate all clinical trial error sources, but it can make it possible for trials to be conducted under more complex and demanding conditions. “A system built upon our prototype,” says Butte in a university statement, “could be developed to enable oversight of international clinical trials, for example. And it could be expanded to provide more access to raw data for research scientists, the way we do with ImmPort, or deliver trial results to the public.”

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