Good morning, everybody. Luke Sergott. I cover life science tools and diagnostics for Barclays. With me, I have Mike Fedock, CFO of IQVIA. Thanks again for making it down. I know it's been a long week for you guys. I know. Really appreciate. It's been a long week for everybody. The worst place is to be in Miami, so thank you for asking. That is incredibly true. I think we were just kind of talking offline, like, one of the biggest issues facing you guys and overall CROs is just obviously this boogey of AI is coming, right? The AI boogeyman. It's really hard to disprove the negative. Yeah. Already talked and you guys talked about having, you know, 70 agentic, you know, modules running out. Like, can you open up the sheet a little bit and just show us, like, here's what you guys have been working on, here's where it's going. Mm-hmm. Like, interest in where you think, like, the initial demand is going to translate into. Sure. Business growth. Yeah. Absolutely. No, great question and obviously incredibly timely. First, this AI phenomenon. It's great for us, right? Because, A, AI is a net positive to IQVIA on both in terms of revenue and margin expansion over time. What it's done is, it's actually put a spotlight on our crown jewels at IQVIA, which is really our proprietary data and our domain expertise. You know, that's the first thing I think that was being misunderstood was the data, right? You get this like kind of this high-level narrative with the AI boogeyman to say, "Well, you have data, and you sell data to pharma, and therefore you're gonna be displaced." That is just fundamentally false. If you think about our data, and obviously everybody has kinda gotten around the notion of if you're building models, your models are only as good as the data that it's built upon. We, by far and away, have the most robust data set in the industry, hands down. It's not even close. We have 150,000 live data feeds of prescription data and claims data and genomics data. I mean, you name it's coming in. That raw data that comes in every day is, in a sense, useless. What our secret sauce is is that we take that data and you de-identify it and you clean it and you code it, you bridge it, you link it together to actually make it useful. That, that's our data moat. That data is not available out there in the marketplace. Clients have realized that. It's actually changed. It's fundamentally changed the way clients are engaging with us. The whole theory of the merger, and in October we'll have our 10th anniversary as IQVIA, was to take that, at the time, 60+ years of IMS data and use it to completely transform Clinical development, right? That's the whole theory of why IQVIA came to be in the first place. Over the years, we would build all of these like amazing leveraging that data, and we would build all these agents, let's say like on the Clinical side. One of the first things we built was an AI-enabled study optimizer, sort of tool. We would sit down with a pharma company and they said, "You asked us to bid on this protocol. We bid it to spec 'cause it's competitive, but here's our AI team has sort of ran it through our models, and we've taken your protocol and we've optimized it. If you go to this site, if you change this assessment, this is what it's gonna do to speed up enrollment and reduce sort of dropouts." You know, years ago, pharma would go, "Oh my god, that's amazing. But thank you. We've always done it this way." Now that's changed because now pharma wants to use the data to inform decisions, so it's like elevated. Now they're actually pulling us in. In 2025, I think we've deployed over 150 agents. Our roadmap is by 2027, have over 500 agents. We're going sort of at pace. We even learned this week in some of our internal management meetings that already, 19 out of the top 20 pharma already are using agents that we've built within their operations. Yeah, it's a net positive for us, and we're excited about the outlook. Is that across both the research side? Yeah. Right. Both Clinical and Commercial. Yeah. Yeah, absolutely. On the Clinical side, I mean, I was just thinking when I just mentioned 10 years ago, you did a deal like PTSD feels like yesterday. Elizabeth Anderson and I putting together a deck when you guys did the deal. I remember you guys came out with a heat map, and we were just like, "Oh my God, this is amazing." Right? Like, you can figure out which doctors are ordering based on this data and like. Yeah. Just accelerating. This just feels like a you know, giving that backbone of your business like steroids, right? This is like this is natural evolution of how things are going. When you're engaging with customers now that their mentality slipped to be like, "Oh, we know what we're doing," to like, "How can you help?" Like, how much are you leading with the AI piece? Like, how much of that is your biggest differentiator right now? Yeah. I mean, we're leaning hard into it. Our teams are super excited because, like, that engagement is being received, like, on the other side. You know, one of the big fears that kind of came out is particularly on the Commercial side, there's like, oh, people would have this hypothesis, well, your consulting business is gonna go away. Yeah. Like, no, it's not gonna go away. You know, our teams here locked into virtual rooms, and we try to beat the hell out of all of our offerings and try to say, "Okay, where are we vulnerable, and where do we have sort of, sort of net gains to have there?" When we looked at, like, our analytics consulting, you know, there's some offerings like primary market research. Mm-hmm. Key opinion leader searches where you know you could probably scrape together good enough data that's out there, but we even kind of ran the simulation. Say, let's use you know Claude to come up with sort of the top 10 key opinion leaders in a particular therapy and compare it to what our data shows us. Out of the top 10, Claude got like three out of the top 10 right. Even in like the most basic sort of use cases. Yeah. It's still not as good. What we're finding with our clients is, you know, there's so many use cases out there, particularly in the commercialization sort of area, that it's just not economical for them to go and try to build all of these, like, agents themselves. You might as well come to us that's trained on our data. We even learned that, you know, one pharma company in particular, I think, started out with doing 700 internal AI initiatives, and they've already killed half of them. Hmm. Right? Everybody's playing. That's from drug discovery to Clinical and to Commercial. You know, the level of engagement, we're really leaning into this, the AI effort and what we bring to the table. Yeah. I mean, I feel like it's one of those it's all promise right now. The rapid adoption and potential disruption really needs to come from showing that it is shrinking trial, like, the overall trial spend. It is accelerating the time to market, and that's what you guys have always done. Can you talk about kind of from internally, what you guys have run, some of the use cases that you've actually shown to be like, "Oh, if we did it this way, you know, our trial execution would have been, like, 10% or, you know, 20%." Have you guys done anything like that on internal studies or looked at that? Yeah. I would say just to help people think, how to think about kinda AI and how that'll start manifesting in our numbers sort of over time here. Yeah. I think time is the key thing to put out there. On the Commercial side, right, it's a shorter cycle part of our business. I think that you will see organic revenue growth acceleration and margin accretion as those agents kind of get at scale and are adopted at scale. We're already selling them, and it's already in our numbers, but that's a $7.3 billion part of our business, right? It takes time for you to see it, but it is already happening. On the Clinical side, a lot of our efforts over there are around sort of agentifying our internal processes, so it's more of a margin- Okay. Expansion, kind of play there. The thing that people need to realize is that in quite literally the thousand individual processes that kinda underpin the execution of a Clinical trial, when you make an agent and you deploy it, let's say, on something like that's very laborious, like site activation. Mm-hmm. Right? Where you have to get the sites contracted, and they form consents and things like that, huge potential. When you have that agent, because of the regulatory nature of the studies, you can't drop that into live studies. Yeah. Right? It's gonna come out as new studies start to get launched. You'll apply those agents on a go-forward basis. There's a ton of promise in the Clinical side around accelerating particularly site startup, how you handle the regulatory documents for, like, trial master file. Mm-hmm. It makes your CRAs sort of more efficient, and you can get sort of more throughput through them. Obviously, there's some benefits in, like, data management. You can speed up the setup of the database. Yeah. Things like that. Yeah. That's, like, one of the key questions then, and pushing back on just broad Claude adoption. Yeah. Disruption is like you have to plug into the pharma. Like, there's a lot of hesitance, but like your tax return's up on Claude right now. Like, if pharma, that's like the. That's it. Correct. That's their whole terminal value, like, on that side. Exactly. It's like this. They're already working with you. Yep. Right? You're already doing the services, and if you're building out these applications for them, like, why would they build that internally? Correct. Right. You know, obviously, with the it's built on our data, which is more robust than them building it on their internal datasets. I think one thing that's been resonating over the past sort of three weeks or so with investors on the Clinical side that, you know, to kind of dispel the boogeyman in that part of our house is just reminding people to give an analogy. Right. I remember, like, when the headlines were coming out to basically say AI is gonna, you know, fundamentally disrupt the CRO sort of business model, right? It kinda. You talk about PTSD. Mm-hmm. I go back in the early 2000s, right, when I remember the headlines where CRO business models were gonna collapse because people were going from paper CRFs to electronic data capture, and pharma was gonna have all the data, and CROs make a lot of money. You know, what happened? If you look back, CROs and budgets grew and even sort of accelerated. Absolutely there were certain line items or services in the budget that went away. I mean, CROs used to charge, you know, $2 a page or whatever it was for double data entry of paper, and that goes away. Because you had electronic data capture where you can get access to data in real time and it's being cleaned and coded, well, like, new offerings came up like centralized monitoring and remote monitoring. Those are like net new services. Trial complexity accelerated because it's like, oh, if I can collect data easier, I want more data to inform my trials. Yes. you know, we think that AI is going to do something similar on the CRO side. It's gonna open up, you know, new potential offerings. Yeah. I promised I wouldn't go over half our time talking about AI. No, it's okay. It's fascinating because it's so unknown, and it's just one of those things where I feel like the entrenched players have an edge, and they're just not being given that credit. Mm-hmm. Let's talk more about just demand environment itself. Sure. On the Clinical side. It's been recovering. Book-to-bill's been improving. You guys have been showing nice growth in the booking side. Can you talk about just that existing demand environment right now? The problem is we all go back to, like, the heyday of pre-biotech spending, right? Like, PhRMA was just like- Right. Everything was up and to the right. Now it's been this kind of, is this one of those another false starts that we're getting? I know that you guys get a good early look on the late-stage Clinical side, and you're building out more on your biotech piece. Just give us the lay of the land of what you see right now and, you know, not how that comped before, but, like, how. What's been changing? Sure. Well, with book-to-bill, I think it's pretty well known about our feelings on that particular metric. I mean, it is the most- You can make it up either way. Used sort of metric in the industry, and people over-rotate both to the good and the bad on any quarterly book-to-bill. We don't forecast book-to-bill. It's an impossible sort of task. When you take a step back and you look at book-to-bills over time, it's an indicator. Yeah. It's interesting. What I can say is that from the metrics that we track and the conversations that we're having with our clients, it certainly is encouraging in the outlook. Our demand metrics, like our RFP and our qualified pipeline, are healthy. We watched as we went through 2025, the decision timelines kind of moderated. The conversations with our clients, there is clearly more certainty this year compared to last year. It just feels better. Then you throw on top pretty robust, actually, biotech funding. Mm-hmm. All of that together certainly feels like, you know, 2026 is gonna be a better year. Now, the rates and pace of that and how that translates into the quarterly book-to-bills, you know, I don't know. Nobody knows. Certainly the interactions with our customers is a lot more optimistic. Yeah. To use that term. I mean, that's all we need is just better than last year, right? Better than last year. It's kind of a low bar, but we're excited about it. That's true. On the See More, Win More strategy with biotech, talk about early traction there. Any new logo wins that, you know, obviously you're not gonna give those. Right. how that has really translated and kind of revitalized the part of your business. Yeah. It's been great. You know, I think part of maybe the misnomer and maybe we didn't do a good enough job at sort of explaining kind of the See More, Win More strategy. Everybody just went to like it's like a price thing. Yeah. That's really not the case. I mean, when you're competing for EBP work, you know, price is always a factor. Really, you know, giving EBP customers the confidence that you're gonna give them the attention. Mm-hmm. Right? We have a biotech delivery model. I think Quintiles bought Novella in 2013. That was 6.4. That's like our IQVIA Biotech. None of this is new for us. You know, doing a better job at telling our story and highlighting, like, we have a bespoke delivery model for what you need, is key. The other thing that we did was really twofold. One is looking at our engagement model with these customers. Mm-hmm. We realized that we probably needed to engage with these customers early on, even well before they have an RFP to go out the door. We also capitalized, quite honestly, on the churn and with the FDA, where you had a lot of reviewers and regulatory, therapeutic and regulatory experts leaving the organization. We were snapping them up because, you know, you take people. Mm-hmm. With that experience, and then you get that early engagement with chief medical officers and chief scientific officers of these biotechs. That engagement is there. The other thing that is very encouraging about sort of biotech is that obviously the funding is in a good spot and continues to be. It's the fastest-growing segment of the market. It's generally full-service work that comes with higher margins. You are seeing biotechs take their development further into Clinical. It kind of used to be, as you probably know, that, you know, they used to get to like a phase II-A proof of concept, and then they would outlicense it. Now they're going deeper. Now we're even seeing, you know, biotech companies actually wanna go into some of the commercialization, which is great for us. Perfect. Yes. Yeah. On the, I mean, that was one of the feedback since, but, like, also your definition of emerging biopharmas. Some of those are pretty big biotechs, right? I mean, it's under $500 million revenues, $250 million- It is. I am constantly amazed at the depth of that market. I mean, you know, there's so many companies out there across the globe. It's doing great science. Part of our, I would say vetting, but, our process around sort of EBP is that, you know, obviously we're very disciplined from a funding- Mm-hmm. You know, standpoint to make sure that, you know, when we make a sale, right, and we put it into our backlog, the fund we have that funding sort of, you know, certainty. Also from a scientific standpoint. We really kind of are pretty particular about vetting the science and making sure that, you know, what the client has when we want to invest in that early engagement to help them, that the science is robust. Yeah, it's an amazing part of our industry. Given the depth of that market right now, and you're talking about this being the fastest part, like is there a certain size that's outstripping the other? Or is it just kind of broad-based across that sector? I think for us, I think we've been really pleasantly surprised at, you know, kind of going deeper into that market in the smaller size. Yeah. Really seeing the science that's out there and their openness to work with us and their engagement with us to help them through their problems. It's really encouraging. Yeah. I mean, you're talking about getting in earlier and earlier with the customer. It feels kind of like investment banking where you wanna be involved at the very beginning. Sure. Kind of my terrible way of segueing into the Charles River deal is, I'm not really sure you knew where I was going with that. Segway. Yeah, whatever. Just walk us through the strategy here on those European assets from Charles River getting even further. Yeah. You know, upstream from where you guys have traditionally played. To give you a little bit of context on that, we started looking at a little bit more focus on discovery, I would say 2021 and 2022. We started looking in that area. We saw that it was an opportunity for us to expand our capabilities. We also saw the prospect of, you know, where this AI could potentially go and help drug discovery and kind of, you know, identify and pull more molecules through. In 2022, I believe it was, we bought a company called Specifica. We put that in our lab business. Specifica is a large molecule drug discovery business that we're delighted with. You know, since then, we've been looking in the market for a small molecule discovery sort of business. You know, we looked at a bunch of companies, either the valuations weren't right or the capabilities. We were delighted when, you know, Charles River obviously has been very vocal about their efforts to look to divest what they term non-core parts of their business. When our Head of our Lab business, Dave Morris, and our corp dev guys came to us and said that, you know, Charles River reached out, you know, they laid out, here's the capabilities and the footprints that they have. They meshed it up with what we already have with Specifica, and it was like a hand in glove. you know, we were delighted to sign the deal on that asset, at a very good price at that. Is it more because of the couple deals you do envision or is it a strategy just to continue to I don't know. It's either we wanna get even bigger in there or we're just gonna be more opportunistic when we see really quality assets that fit well with what we do. I think it's a little bit of both. We're pretty excited about the prospects for discovery in general. You know, I mean, if you look at the client segmentation when it comes to discovery, typically large pharma keeps a lot of that in-house. We also see it as another mechanism that biotech really needs discovery. To your point, it helps us, you know, get in- Earlier and earlier with them. Yeah. That makes total sense. In the last 2 minutes here with the CFO, and I think we should probably talk about margins. I'm a captive audience for 2 minutes. Go. Right. We've talked about the pass-through of FX headwinds kind of coming through, but when the FSP has been a continued trend here, pass-throughs are relatively elevated versus what they've been in the past. Can you just kind of walk us through those changes and how you see you know what are you guys doing from an offset? What levers are you pulling? Sure. You talked a little bit about AI, but, like, what else can you do in the near term or long term? Yeah. I mean, look, we have a great track record at IQVIA in expanding margins year in, year out. I think that it was the only two times in the past 9 years where we haven't expanded margin. One was 2020, and obviously that was the pandemic. Last year in 2025, where our reported EBITDA margins contracted by 70 basis points. You know, what we've been telling people is to say, if you look at our margin, and this is maybe a construct, especially going forward, on how to think about our EBITDA margins. You know, you have non-operational dynamics like pass-throughs and FX. On the operational side, you have mix issues, mix in pricing that you were alluding to, and our productivity programs. If you take just 2025 and that 70 basis points, almost all of that margin reported margin degradation was because of non-operational. We just wanna make the point to investors to say, operationally and structurally, right, we are very sound. I had somebody, you know, tell me one time they're like, "Yeah, you can't you gotta focus on the EBITDA dollars, not the margins, because you can't buy a sandwich with a percentage," you know, kind of thing. But we certainly understand people's focus in there. If you look at the mixed headwinds from things like CSMS and CSM, let's say ran faster than some of our higher margin parts of our business, our productivity programs generally cover or are the things that kind of give sort of the margin sort of accretion there. Our productivity programs are things like the blocking and tackling, like spans and layers and looking at the level of the numbers of managers to employees and real estate and all those other things. You know, automation has been sort of our cornerstone, whether it was robotic process automation and now agentic AI is just the next level. We remain confident that, you know, our productivity programs will continue to kind of, you know, outpace any sort of, you know, mixed headwinds we have. Great. Thank you. No problem. That's all the time we have, unfortunately. Appreciate it.