{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"AI Validating AI: The Future of Compliance in Life Sciences","description":" Artificial intelligence is moving fast\u2014but in regulated life science environments, speed without trust is a non\u2011starter. In this episode of The Life Science Effect, host Steven Vinson reacts to a recent EY article on AI validation in pharmaceutical and biotech settings and explores a fascinating question: Can AI actually be used to validate other AI systems? Steven walks through how regulators are beginning to rethink traditional validation models to accommodate AI\u2019s non\u2011deterministic nature, where the same input can produce different, but still acceptable, outputs. Drawing parallels to earlier industry shifts like electronic records, he explains why clear regulatory frameworks are essential for innovation without compromising patient safety. The conversation dives into EU\u2011specific regulations such as GMP Annex 11, Annex 22, and the EU AI Act, while contrasting Europe\u2019s proactive approach with the more hands\u2011off posture emerging in the U.S. Along the way, Steven offers practical insight for entrepreneurs, engineers, and investors navigating AI in regulated environments, and why \u201crobots testing robots\u201d might be less science fiction than it sounds.   EY ARTICLE:  GxP and AI tools: Compliance, Validation and Trust in Pharma | EY - Switzerland   MUSIC used under the Creative Commons Attribution 4.0 International License: Acid Jazz-Kevin MacLeod Acoustic Motivation by Corna Media   Key Discussion Points Why AI validation is different from traditional computer system validation What \u201cacceptable ranges of output\u201d mean for regulated AI systems Using AI to validate AI: hype vs. reality Overview of EU regulations: GMP Annex 11, Annex 22, and the EU AI Act Lessons from the transition from paper records to electronic systems Why regulatory clarity enables innovation in pharma and biotech Notable Quotes \u201cAI is a tool\u2014and tools still have to be validated.\u201d \u201cWith AI, different outputs are okay, as long as they fall within what\u2019s acceptable.\u201d \u201cI just love the idea of robots testing robots.\u201d \u201cChatGPT does not equal AI.\u201d \u201cAI is a fantastic tool, but it\u2019s not the solution to every problem.\u201d Call to Action If you\u2019re working with AI in regulated environments\u2014or thinking about it\u2014subscribe to The Life Science Effect, leave a review, and share this episode with your team. Want to join the conversation? Email steven.vinson@bpm-associates.com or visit thelifescienceeffect.com.   Transcript [00:00:01] You are about to experience The Life Science Effect, Season 2, brought to you by our presenting sponsor, BPM Associates. [00:00:16] Extraordinary people. Relationships that matter. Important change for a better world. The joy of belonging. Life, science, leadership. [00:00:29] A few years ago, when we all started learning about ChatGPT and were amazed by it, my first thought was: how can this be used for GMP validation in the pharmaceutical and medical device industries? For testing the equipment that makes products, and the systems used to manage manufacturing and R&D. [00:00:57] I asked a colleague who works in the quality and regulatory space for pharma and medical devices, \u201cWhat are you hearing? What are you seeing?\u201d He said, \u201cAI is a tool, and you have to validate the tools you use for testing.\u201d [00:01:15] That led to a bigger question. He had asked someone from the FDA at a conference: how do you validate an AI when most of us\u2014even the people who design AI\u2014aren\u2019t 100% sure what\u2019s going on inside it? [00:01:31] Fast forward a few years. I\u2019ve been reading articles and digging into this topic, and I came across a really interesting piece\u2014more like a blog post\u2014on EY\u2019s website. I\u2019ll link to it in the show notes. [00:01:47] It\u2019s written by Martin Blank, a partner at EY in Switzerland, focused on life science regulatory work. EY is one of the large global consulting firms, similar to Accenture. Because of his background, the article has more of an EU perspective, but much of it applies to the U.S. as well\u2014though the U.S. may be a bit behind. [00:02:09] The article is titled \u201cAI Validation in Pharma: Maintaining Compliance and Trust.\u201d It caught my attention for a few reasons. I was actively looking for examples of how AI is being used, and I wanted something relatively recent. This was published in October 2025, and I\u2019m recording this in early 2026, so it felt timely. [00:02:32] What really grabbed me was that he talks about using AI to validate AI. [00:02:46] It\u2019s kind of like robot-on-robot violence. [00:02:50] I, for one, welcome our robot overlords. [00:02:58] I read the article and thought I\u2019d share my reactions with you. The big takeaway right away is that AI can absolutely be validated. That answers the question from a few years ago. The real question is: how? [00:03:25] In traditional computer system validation, you provide a specific input and expect a specific output that matches exactly. With AI, you might give the same input multiple times and get different outputs. [00:03:48] Regulators are saying that\u2019s acceptable\u2014as long as you expect a range of outputs and all of them fall within what\u2019s acceptable for the intended use. [00:04:03] For example, if you ask a chatbot whether there are interactions between ibuprofen and a GLP\u20111 drug, you\u2019d expect some variation in how the answer is presented. But every answer should reflect the real interactions. It shouldn\u2019t hallucinate or invent risks that don\u2019t exist. [00:04:39] The same principle applies whether AI is supporting research, identifying drug candidates, or helping design a testing strategy for a drug or a piece of equipment. [00:04:56] I found that fascinating. And while that wasn\u2019t the only focus of the article, it\u2019s the part that really excited me. [00:05:06] First, this absolutely can be done if you understand the regulations. Second, I just love the idea of robots testing robots. [00:05:29] So what are the regulations involved? In the EU, there\u2019s GMP Annex 11 for computerized systems\u2014traditional systems, what we might think of as pre\u20112020 technology. There\u2019s also GMP Annex 22, which is specific guidance for AI used in GMP environments. [00:05:55] Then there\u2019s the EU AI Act, which governs AI more broadly\u2014not just pharma and medical devices. [00:06:13] The U.S. has been discussing similar approaches, but with recent political changes, it appears the U.S. is choosing to let industry largely govern itself. The EU, on the other hand, has taken a proactive approach and has been rolling out AI regulations in phases since around 2023. [00:06:30] They started with lower\u2011risk applications and are working toward higher\u2011risk ones. That may sound backward, but it allows regulators to learn and adapt as complexity increases. [00:06:47] You also still have to comply with GDPR. Even if you\u2019re using AI, privacy and personal data protections don\u2019t go away. [00:07:10] And of course, GxP standards still apply globally\u2014FDA, EU, Asia\u2011Pacific, Brazil. There\u2019s a fair amount of harmonization across regions, and those expectations exist regardless of what tool you\u2019re using. [00:07:20] Is this a big deal? I think it\u2019s a very big deal. [00:07:35] I remember in the late 1990s, when electronic records started replacing paper, the industry was asking for a regulatory framework. The rules were written as if everything would stay on paper forever. It took time, but that framework eventually came. [00:08:15] I\u2019m glad the EU is getting out in front of AI. Regulators are focused on patient safety and drug effectiveness. They want more effective therapies, more of them, and they want them to be safe. AI presents a real opportunity to innovate, but it has to be done within a clear regulatory structure. [00:08:44] If the U.S. decides it wants to participate more actively in this future, it can likely build on much of what the EU has already developed. [00:09:04] I know I\u2019ve been talking a lot about AI lately. I promise there\u2019s more going on than just AI. [00:09:18] As someone recently said on a panel discussion, ChatGPT does not equal AI. AI has been around for a long time. What\u2019s new is the speed and scale at which it\u2019s advancing. [00:09:33] As Raul Zavaleta once told me, AI is just a tool. A fantastic tool\u2014but not the solution to every problem. [00:09:46] So yes, I\u2019m on an AI kick, and it probably won\u2019t stop anytime soon. But I will mix in other topics too. [00:10:05] If you\u2019re an AI expert or someone doing real work in this space\u2014especially in regulated environments\u2014I\u2019d love to talk. This EY article focused more on how to approach AI, not how people are actually using it. I\u2019d love to hear what problems are being solved and how teams are navigating the regulatory landscape. [00:10:24] If you want to continue the conversation, email me at steven.vinson@bpm-associates.com or visit thelifescienceeffect.com. [00:10:35] You can find us on all the major platforms. Don\u2019t forget to subscribe, leave a review, and do all the internet things. [00:10:41] Thanks for listening. Stay strong out there. ","author_name":"The Life Science Effect","author_url":"http:\/\/www.thelifescienceeffect.com","html":"