To give just one example, when Australia’s Commonwealth Scientific and Industrial Research Organisation (CSIRO) announced on April 2nd that it would be conducting the first comprehensive pre-clinical trials of Covid-19 vaccines to use an animal model, researchers working on the project told reporters, “Normally it takes about one-to-two years to get to this point and we’ve in fact shortened that to a period of a couple of months.”
If we’re moving at unprecedented speed, how can it be that we’re still potentially years from the finish line?
A big part of the answer lies in the development process for new medicines. Before it can be approved, any new treatment must go through a series of clinical trials. The gold standard in this regard, double blind randomized placebo-controlled trials, are rigorous tests that prove both the safety and the efficacy of potential treatments. They have been the bedrock of medicines development since the post-war era, and they have served us incredibly well.
Unfortunately, clinical trials are painfully slow. In fact, it now takes on average more than 10 years from a treatment’s concept to its approval. Of course, everyone agrees that we’ll find effective treatments, and a vaccine, for Covid-19 in less than 10 years. We must. The point is, in our race to beat this virus, every day counts. Finding a cure or a vaccine in six months rather than 18 months could save millions of lives and prevent a catastrophic meltdown of the global economy. If we can speed up the clinical trial process, we just might be able to turn that 18 months into six.
Why do clinical trials take so long to complete? As with any complex system, there are numerous contributing factors at play, but to a large extent, it ultimately comes down to an inability to collect and manage data. If researchers could gather, share, analyze, and report more data on the potential treatment and its effects (or lack thereof), they could determine exactly which treatments work, and they could do so at a much faster pace.
In the digital age, where our power to capture and analyze data has never been so great, how can it be that inadequate data management holds back the development of important medical treatments?
The answer is that the legacy systems for managing data don’t provide the needed levels of security, transparency, and immutability to unlock the power of the data being collected. Sensitive information on patients needs to be protected. Intellectual property, the fuel that drives the profit-motive needed to spur innovation, must be protected. Regulators and peer reviewers need assurances that the data is accurate. However, in the status-quo client-server model for data management, where data is maintained on a centralized server, all of the above are extremely difficult. There’s a constant trade-off between protecting the integrity of the data and unleashing its power.
Fortunately, there’s already a proven solution. A year ago, 10 of the world’s largest pharmaceutical companies made an historic agreement to pool their data on antibiotics, providing the needed data volume to unleash the power of AI in the fight against antibiotic-resistant bacteria. That agreement was only possible because the technology behind it leveraged blockchain, a technology that changes the way data is stored and managed. This allowed each pharma in the consortium to maintain their IP and meet regulatory requirements.
