Is AI Replacing Laid Off FDA Workers?

One of the goals of the current administration is to implement the use of AI in FDA’s approval process. Proponents of the policy argue that the technology can increase the speed at which FDA can review materials and approve new drugs. Critics, however, worry both that the technology will be used to replace existing workers at the agency and also that the results will be unreliable. Marcel Botha, CEO of 10XBeta, spoke with Pharmaceutical Executive about the technology and the risks and benefits of its use at FDA.

PE:This year, FDA was hit by mass layoffs. Is there risk that the AI is going to be used to replace these now laid off workers?
Botha: I think the assumption was that the goal was to streamline the workforce and then have AI fill in the gaps, or at least lighten the workload. What we're seeing is that the opposite is happening. It's effectively making them less credible as a group, because the AI's work needs to be scrutinized at this point. Can we solve this over time? Yes. Will it happen immediately? No.

The immediate impact it's going to have on the FDA is to slow them down or to force them to take shortcuts. Having worked with FDA many times, it’s not a group of people who like to take shortcuts. They would rather just not approve something than approve something that they know has not been vetted properly. Because of that, they are all capable humans in the decision process to decide whether they are going to take the risk of approving something that possibly shouldn't be approved. Will there be political pressure to create a higher approval success rate just so that they can justify the mass layoffs? I don't know. I think that the there's a lot of human risk being introduced because an overworked employee of the FDA will also yield a worse outcome, both in quality and quantity of review over time, leading to burnout and other issues.

PE: When it comes to AI and its use in FDA’s approval process, what are these programs actually capable of doing now that will make the process more efficient?
Botha: There are a couple of simple things that can be used where AI is very, very efficient. It can look at complex submissions and to do a lot of the grunt work in analyzing ingredients, processes followed, checking for completeness, and other things that a human would historically have to do. It can also very quickly check for any anomalies that need to be flagged by the human because it doesn't follow protocol or understood protocol based on past experience or data sets. Yes. The benefit of what AI is going to and what the AI application will bring to the FDA is still very much on the edge of machine learning.