What will the research lab of the future look like? Data will be king, and the insights it provides will accelerate the development of new medicines. But there are also risks, according to Charles Fracchia, CEO of data automation firm BioBright, who will participate in a February 7 panel at the Society for Laboratory Automation and Screening (SLAS) 2022 event.
Fracchia is also a co-founder of Bioeconomy Information Sharing and Analysis Center (Bio-Isac), an organization that addresses threats to the bioeconomy. Fracchia will be one of the panelists at the session on how artificial intelligence is being used in research laboratories today and how it will shape labs in the future.
Q: How do you see the lab of the future?
A: It will be a lab that's fully connected, where, effectively, the data and the insights are king. It's effectively a translation of what is happening in the wider biological sciences field, I think, but into the lab.
The biosciences used to be much more process-driven. It was so complex that you had to control every point of the process itself and only then could you trust the results: "Did I do this correctly? Do I know that this result is accurate or not?" Now, it's a bit different. We're doing a bunch of more competent, real experiments and seeing what the data tells us. It's a much different approach to the scientific field.
The lab of the future, specifically, is the embodiment of that spirit, that sort of shift from process-driven to data-driven but in the lab, and so that means more automation, it means products that interact with each other seamlessly, even if they're from different vendors, and where data is king, and where the insights that are derived from that data, by consuming the data, analyzing that data, is really key. It's about how fast can you get to an insight by using robotics and automated systems, including on the software side.
Ideologically, the field has now switched to this more data-driven process. Everybody talks about digitization and the lab of the future, because these are embodiments of this underlying shift in the way of thinking for the biosciences and for biotech.
It's essential to note that now we're coming into sort of the implementation phase. A lot of people are having trouble with training. Very advanced neural networks or other machine systems are pretty complex, and pretty difficult to introspect, so how can you know that the machine gave you the right result? So validation is one thing.
But then there's also data security and integrity because if data is king -- if data is the new oil -- you need a pretty secure pipeline, right?
Q: What else are you going to discuss in your panel at SLAS?
A: One of the things we're going to talk about is the security and integrity of data and how those things are interacting and inextricably linked to those insights. Also, other limitations like human training, capabilities, workforce development, etc. And also, some of the threats inherent to other sorts of neural networks.
What kind of techniques should people consider? Because sometimes, even though it's the fanciest new tool, neural networks might actually turn out to make the whole process more brittle long term, and so we have to accept the trade-off, to think about it carefully.
Q: Tell us about Bio-Isac, the organization you founded that addresses cyberthreats?
A: Bio-Isac was created because we need to treat the bioeconomy as a critical infrastructure. We created the Bio-Isac to try to get the industry to pay more attention. It's been working -- industry is paying more attention to realizing how important this is -- but we need more awareness.
We made a disclosure of a new APT [advanced persistent threat] that we discovered in the biomanufacturing sector that demonstrated that there was a very advanced, persistent threat, a cyberthreat from an actor that was likely to be at the very top end of the food chain (although we're not doing any attribution).
And so, the reality is that we are making all of the same mistakes that we've made in other fields such as DNS, the domain name service system. That service until very recently didn't really have secure modes.
We're making all the same mistakes for biology, except the difference here is we're not talking about, like, going to a phishing website or somebody stealing your Facebook login, however annoying that may be. We're talking about potentially adulterating medicines and wreaking havoc on agriculture. I mean, these are very, very different consequences. So that's why Bio-Isac was created. We're just at the beginning of that mission.
Q: Looking toward the future, what are you excited about?
A: We are clearly amidst an inflection point for biology, for biochemistry, and for biotech. We're starting to feel this rocket take off and that means good job opportunities; that means tremendous products that come out that will improve human health overall. There are other challenges that we have to deal with, but those are fantastic. That's why I'm excited and why I focus on the things that could jeopardize this.
It's our job to elevate the discussion and to bring in technologies to help. But at the same time, be very honest and open internally in our field. Say: "Here are the vulnerabilities, here's what could threaten this renaissance." Let's go mitigate those so that we can focus on changing even more people's lives by making medicine more accessible and more wide-reaching in terms of diseases.