FDA's ELSA AI: What It Means (so far) for Clinical Research w/ John Reites

John Reites reviews what we know (so far) about FDA's AI tool named ELSA. He provides his insights on what ELSA is, why it matters to Clinical Research, how the industry currently views it and what he personally thinks about ELSA.

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Transcript

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If you have kids or love Disney movies, you've invested your time and money with a famous Arendelle leader that has the same name as today's topic. You guessed it. We're talking about the FDA releasing their new AI tool named ELSA. So what is this AI tool? What is it trying to accomplish? And why does it matter to you? Let's talk about it. If you watch the news or you've been on LinkedIn for less than five minutes recently, you've seen this new FDA press release. And what was announced is that the FDA just launched an agency-wide generative AI tool called ELSA. Now, ELSA stands for Evaluation of Life Science Applications, and it's an AI tool built on an existing large language model, or LLM, although we're not sure which LLMs are involved just yet. They also want to ensure we knew that it was released a month ahead of schedule and under budget, which is kind of interesting. ELSA is designed with an intent to accelerate scientific reviews, improve operational efficiency, and reduce submission review timelines for both drugs and medical devices. Overall, it's important to note that ELSA is only in beta use right now, and I'm not sure a production release date is confirmed just yet. So what does the FDA want ELSA to do for them? Well, if you watch the video, if you review the press release, if you read industry articles and you hear the volume of off-the-record insights, it's really only a simple list so far. It includes things like sorting through unstructured data, summarizing documents and generating draft reviews, identifying trends across applications, and supporting internal training and documentation workflows. There's obviously more they must have planned because these are only entry-level solutions. So if that's the case, why does it matter for clinical research? It matters because this is a market signal. When the U.S. regulator makes a video and issues a press release saying they are using AI, they are providing some form of endorsing AI at the same time. And if the solution works, patients, prescribers, and sponsors, in theory and in long term, could see faster access to new therapies. It's also going to embolden companies with AI solutions, real and perceived, to amplify their messages in the short term. This is going to be a closely watched test run for AI. Can it deliver a trusted solution that provides proven return on investment? Or will it create a negative perception is really the key question to answer. So what does our industry think about ELSA so far? Well, it's still early. But it's creating a passionate discussion with many industry experts because it's AI. We're still early on the AI hype curve as we learn the difference between practical AI and fabricated AI. And on one side of the debate, NBC News already reports that ELSA struggles with basic tasks, which already starts to raise early concerns about reliability, transparency, and product quality. And other experts are warning us of a black box problem where reviewers get an AI-generated answer, but without reasoning, context, or references. On the other side of the debate, this could be a solid use case for AI and global regulators if it does deliver. AI companies and clinical research are all creating a new slide in their capabilities deck today with this informal endorsement. And sponsors should see this as a positive signal. especially the sponsors that have been investing in AI solutions for regulatory submissions for the last year. So what do I think about ELSA? It's early, and I think the use cases described in the press release are entry-level. I'm waiting to learn more about what moves from beta to production release, as that's really what I think we should pay attention to. And the LLMs and the app features they built do matter. We need to learn more about which tools are being used, although I think we can guess what some of them are. I also really want to know when they're going to publish a guidance on how they will use the tool, how it's referenced, and if any decisions are made by ELSA versus a human reviewer, and a whole list of other questions that I think still need to be answered, even at this early stage. AI is generally overhyped in the market already, so many people I speak with believe it's either alive or does a lot of things it does not do. But I see sponsors utilize AI tools in very practical use cases every day, and I believe this could be a step in the right direction with some delivery excellence and if clear heads prevail. It's early, it's not in production use yet, but we are paying attention. Thanks for joining, and let me know what you think via direct message or comment. Especially if you're sending me your new The FDA Supports AI slide.