How to revolutionise clinical trials: engaging with participants as partners
Posted 23rd September 2019 by Joshua Sewell
Ahead of the 3rd Global Pharma R&D Informatics and AI Congress, Global Engage spoke to Scott Kahn, CIO of LunaPBC. LunaPBC is the company that manages LunaDNA: a community-owned data-sharing resource. Their conversation was recorded as a podcast, which can be found here.
In the first half of the conversation, Scott discusses the benefits of distributive ledger technologies such as Blockchain for Pharma R&D.
Tell us a bit about LunaDNA?
LunaDNA is all about creating a community-owned resource to gather, organise, and provide access to health data. This includes traditional health data, but also the health data of the future such as wearable data and DNA information.
We have found a large aggregation of this kind of information is largely lacking at the moment because data is siloed. We’ve had to really think about how to do this in a way where the community can have ownership of the data. The community can have absolute control of the data, and in doing so, it promotes a wider range of sharing than would otherwise be the case.
Something that is important within this community-owned resource is that we really pay attention to how users have control. This touches on the topic of privacy because privacy is nothing more than having something that’s secure and deciding when you allow other people to access it.
This was obviously in the news a lot last year with the coming of the General Data Protection Regulation (GDPR) in Europe. But in the US, we’re starting to see privacy legislation creeping its way through the legislature. In California, they passed similar regulations that will take effect next year.
Distributed ledger technologies have recently come into focus for the storage of data. What advantages does blockchain have for storing biomedical data?
Blockchain or distributed ledgers have some advantages and some challenges. One of the advantages they provide is a completely transparent immutable record of the data.
With data that is controlled by others, you want to know who’s accessing it and how they’re accessing it. You want it to be transparent so that you can review whether or not their idea on how the data should be used is consistent with your wishes. A distributed ledger provides an immutable record; an audit trail that can’t be mucked around with because it’s distributed and there is more than one copy.
Another advantage of the distributed ledger (and its extension through smart contracts) is a mechanism where an individual can remain anonymous and still be contacted without an intermediary.
If an individual is willing to be re-contacted, you can send them a request and they remain completely anonymous: they know who contacted them and can opt-in to responding or not. An example of this would anonymous recontact such as: “we’re starting a clinical trial and are really interested in people like you. Here’s what’s expected and what we’re trying to achieve. Do you want to participate?”
No identity has been shared: It’s sent to the individual anonymously through the smart contract and they can opt-in. The individual can then raise their hand and say, “Yes, this excites me. This is consistent with what I want to contribute to the advance of medicine.” Or they can be silent and therefore opt-out, effectively saying, “I’m not interested in that particular study, at this particular time, with these particular conditions.”
We like to think of this as a modern way of doing consent, where an individual has complete knowledge of what they’re consenting for and has the ability to opt-in whilst remaining anonymous
So, transparency and smart contracts are the two significant things that a distributed ledger technology provides.
On the topic of clinical trials: returning data from trials is something that’s definitely top of people’s minds these days. How does this technology also play into that?
In general, some of the forward-looking pharma companies are grappling with how to engage participants in their clinical trials during the trial itself. But they’re also doing this in a more longitudinal sense. Part of that involves how they would return relevant data to those individuals that have participated in their trials. This is now a future trend.
Think about what I said where an individual can be anonymously contacted and can opt-in. Now think of someone who has participated in a clinical trial: they had the data returned which the individual shared through LunaDNA, now that pharma company would like to contact them three years later and ask about their outcomes and any potential side effects. That individual is anonymous, and they can decide to respond or not. It’s a way of promoting engagement.
Also, by returning the results to the individual, they say they are doing right by the individual too. It seems a shame that a study participant would get their genome measured if then only the pharma company gets to use it. For the individual not to be able to use it for reproductive counselling, understanding the onset of disease, or just whatever they wish to use it for seems to be a waste of a resource.
This is a trend that we’re seeing and there are a couple of pharma companies that are already starting to explore this for all the right reasons: to engage with study participants as a partner.
The 3rd Global Pharma R&D Informatics and AI Congress will focus on successfully leveraging the power of AI and machine learning to revolutionise the drug discovery and development process. Register online today.
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