The application of blockchain technology in the biotech and pharma industry can increase collaboration, trust, traceability, and auditability in clinical trials by improving the processes’ consistency. Using a “network of networks” (blockchains vs. blockchain) could allow distinct sectors like life-science to use a single, interdependent system. Due to early promise, many companies started to assess the potential uses of blockchain technologies to help with counterfeit drugs, licensing, and technical knowledge sharing. However, the implementation of blockchain technologies in the life science sector is still in its infancy.
There is much promise in using blockchain to protect patient data & for sample management in clinical trials. Pharmaceutical companies run clinical studies to commercialize pharmaceutical products. The patients participate in clinical trials to gain early access to new therapies that are still being investigated for safety and efficacy. The patient cares about protecting their health-related information, selecting the proper clinical study, uninterrupted participation, safety, and outcome of the experimental treatment. It is in the company’s best interest to provide the best experience to the patient being treated in the clinical trial, which can be further improved with new technologies such as blockchain.
In clinical trials, blockchain can help handle the trial’s subject identity better, including electronic health records, without losing privacy or security. Blockchain technologies could translate into a set of solutions that may improve patient participation and relevant processes, leading to better health outcomes. All clinical trial participants: patients, clinical investigators, coordinators, and primary physicians would be touching different parts of the same ledger.
Storing and tracking critical patient data in clinical trials on a blockchain could reshape drug R&D. An example is a cloud & blockchain-based patient “health passport.” It includes consistent, secured information, from searching for relevant trials, matching criteria, consenting, and screening to participation.
Protecting health information (PHI) or personally identifiable information (PII) from exposure is essential. Blockchain already provides a potential solution to provide the required security but requires additional steps to ensure complete protection. The distinction between identified and de-identified is essential in clinical trials, and any blockchain applications should uphold the highest privacy standards.
A similar unbroken information chain could be used in other related processes such as biological sample collection, tracking, and analysis, replacing other document formats that are hard to read or automate. Blockchain could promote a more efficient operation and greater confidence in the laboratory samples’ transportation, analysis, and results.
As of now, no single blockchain solution is a clear winner. To broadly adopt blockchain technologies, pharma companies should avoid operational silos and develop clear business implementation plans for new technologies. Collaborations within healthcare and life-science sector competitors and regulatory bodies (FDA) would be needed to foster mass adoption. The broad life science ecosystem will benefit from adopting blockchain technologies and connections of MedTech, pharma, patients, and providers. Those connections will allow collaborations within clinical trials, track patient consent and reported outcomes, and pre-and post- clinical trial data (real-world evidence). Collaborations between R&D competitors are an essential source of new intellectual property and technologies.
Adopting any new technology used in clinical trials will require trust from both patients and other ecosystem stakeholders. The early adopters need to create a culture of trust and reliability and secure the buy-in from the regulatory bodies, competitors, and patients to achieve the initiative’s tipping point. Pilot collaboration within the life-science industry could also be a way to share the risks and costs of experimentation, thus boosting the adoption.