I think we can look to get started. Thank you, everybody, for joining us, we're here at the Citi MedTech Access Day. I'm Patrick Donnelly, the tools and diagnostics CROs analyst here. Happy to have a unique opportunity here with Ron and Mike, incoming CFO, outgoing CFO. It should be a good conversation. You know, Ron, maybe we can start with you, and obviously, we'll kind of work our way around. Yeah, I wanted to start on. Mm-hmm. Not surprisingly, given the level of focus there. You had a pretty good fourth Q. I think it grew about 7%, constant currency. Can you just talk through, you know, the different components of that? Obviously, consulting is a focus. Right. just the AI stuff, which I'm sure we'll get to. Maybe talk through tasks, and then we can kinda. Sure. -there. You're right. We did have a strong fourth quarter. I mean, actual currency, we were close to 10% growth, constant currency, about 7%, strong organic growth in TAS. That was versus a pretty tough compare in the prior year, where we grew over 9%. We're happy with what we saw in the TAS business. If you break it down into the components, you know, historically, now, TAS is gonna become the new Commercial Solutions segment with a few changes going forward. Looking back historically, we would break it down and say: Okay, the fastest-growing piece historically has been our real-world business in TAS. Now, we've shifted a good piece of that business to Commercial Solutions, I mean, to R&DS, going forward. In the fourth quarter, TAS, the real-world part of the business in TAS grew double-digits. The other pieces, which is consulting and analytics, info, and tech, all grew in the low- to mid-single-digit range. You know, overall, a really nice quarter for us. I'll say, in particular, since you mentioned consulting, we're a little disappointed earlier in the year about the bounce back in that business, and we did see sequential improvement as we went into third quarter into fourth quarter. That's a positive sign. Yep. Then maybe just for people to contextualize, I think we've gotten a lot of questions recently about just the components of TAS in terms of what makes it up, in terms of how big is consulting, how big is real world? Yeah. Can you guys just help break down... Maybe we can use legacy TAS, and then... Yeah. We'll start with legacy TAS. About a third of it is real-world, about a quarter of it is info, and then you have the consulting business, 20%, and the balance is the tech business, which is low 20s. Okay, perfect. Mike, maybe, you know, we can look at the go-forward, you know, the new Commercial Solutions segment. Yep. I think you're guiding for that to grow 8%. You have R&DS, you know, more mid-single, 4%. Yep. Can you just talk about the underlying growth components on the Commercial Solution. Sure. -side? You know, what part of the old task pieces are in there? It'd be helpful to kinda talk through this. Yeah, I think it's. Listen, we were, as Ron said, you know, we finished out the year with a lot of momentum, and we were encouraged by a lot of the leading indicators within the commercial business. Things like drug launches are something we keep a close eye on. Our pipeline is good. Client decision-making was improving in that segment, as well as within sort of the R&DS segment. I think our range was about 7%-9% reported, like you said. Again, I think the growth drivers are the same as what we've seen historically within TAS, right? It's now the patient solutions segment, which is really the remaining pieces of that, commercially oriented real-world business, are still growing, you know, quite strong, as well as, you know, the, you know, info and some of the other parts of the business as well, kind of in that, you know, low to mid single digits sort of growth range. Yeah, we've got a lot of good momentum, and, you know, you guys probably saw that the Cedar Gate acquisition, that we did at the very end of last year, that was, you know, a really nice platform in the U.S. to add to our payer and provider segment, which is part of that real-world patient solutions, you know, part of our segment. Yeah, there's a lot of good stuff happening there. Yeah, maybe you mentioned the deal front. You know, we always get questions about M&A, M&A contribution in each segment. Can you just help kinda frame up which. Sure. What's the right way to think about M&A in each part? Yeah, within our guidance, I think we said about 150 basis points at the enterprise level. It's still about the same, right? It's still about maybe two-thirds would be towards Commercial Solutions, and then, and the balance in R&DS. I mean, listen, R&DS growing at 4% is terrific, actually, in this climate. It was actually somewhat rewarding that we started to get the recognition, I think, from investors that there was a bit of a nice separation last year in the growth rates versus some of the other traditional CRO competitors there. Yeah, we feel pretty good about this year. Yeah, and Mike, maybe just given, you know, the recent shifts in the segments, can we just talk through Commercial Solutions, R&DS, the margin profiles of both. Mm-hmm. progression, how we should think about the two will be helpful. Yeah, the from a revenue growth and margin standpoint, I don't, you guys aren't gonna see sort of much difference. The clinically oriented real-world pieces that we moved into R&DS, which was ostensibly real-world late phase, that people are most familiar with, had a very similar, both margin and revenue growth profile as existing R&DS segments, so you won't see anything there. That part of the business had a lower margin profile than some of the more traditional TAS. If you did nothing else, you would expect the margin sort of uplift, but then we moved the CSMS business into kind of this new Commercial Solutions group, and that has a lower margin profile. Net-net, you won't see any changes there. Okay. All right, interesting. Then, Ron, maybe on the kind of R&DS side, you know, are you seeing pharma clients consolidating vendors more aggressively on the commercial side? How do you guys think about your share capture on the consolidation side? What's the opportunity there for you? Yeah. Well, look, on the, we historically talked in the R&DS business, CRO industry in general as being very fragmented. We've picked up share over the years there, and there has been some consolidation. You know, when you look at the commercial side of the business for pharma, the vendor landscape is even more fragmented. It's in part because there are so many different components to the commercial business, and in part because there's a lot of local competitors as well. We are seeing consolidation, in fact, in the Commercial Solutions area, and I would offer up a couple of examples of that to demonstrate why. One, is we're increasingly seeing pharma clients come to us and want to outsource chunks of their commercial organization, analytics, and even the end-to-end commercialization of products in certain cases. I think we announced on our fourth quarter call that we had our first deal with a large pharma client in Asia to take over end-to-end commercialization of their products. The reason we can do this, it's a good opportunity for us, is we have of course, we have the data, we have the analytics, we have the domain expertise, but we also have a contract sales organization, which was part of CSMS. That is the biggest part of CSMS that we're now rolling into the Commercial Solutions business. We can offer pharma end-to-end. The reason our pharma clients are looking to outsource more is they're trying to decide how to allocate resources between new drugs that they're launching and existing platforms. Very often for existing drugs, they're looking for someone to help them out so that they, you know, they can utilize their resources, allocate them more efficiently. We're at a very good position to do that, given the assets that we have. So we're seeing more and more of those sorts of deals. Yeah. come down the pipe. We even just got awarded another one of those programs this week. It's definitely, the trend is continuing. Mm-hmm. Okay, interesting. Then maybe we can talk some AI. you know, I know... Surprising topic. surprising topic. Yeah, what a surprise. We waited ten minutes to get into it, so. Yeah, Ron, maybe we can start, and we'll kind of go through different pieces. You know, I think a lot of investors are concerned AI is a threat to kind of the core business. You know, the data moat, I know you guys have talked about. You know, can you talk about just how that can stop AI vendors from partnering with pharma- Yeah ... bypassing you guys. Yeah -of the data? You know, I know that's a big focus, and obviously, Ari... Sure. Sure, and Ari has talked about it on the call, and I'm gonna repeat some of what Ari said, because I think it bears repeating. I'm not sure it's fully sunk in yet in the market. Look, in order to be effective in deploying AI, you really need three things: You need data, and you need it at scale, and it needs to be fit for purpose; you need domain expertise; and finally, you need the technology, and you need to know how to use the technology. Right. And all three of those, we think, work to our advantage. Not just are they competitive moats against our business being broken, you know, broken into or taken away by AI, but they actually offer us the opportunity for organic revenue growth. Increasingly, clients are coming to us for AI solutions. Let me talk a little bit about why this is a moat that is our data in particular. The first reason is that our data is proprietary. You know, there are certain things out there where you've seen some articles about Anthropic and others putting out variations on their agents that can, for instance, analyze legal cases and things of that matter, maybe displace a LexisNexis or something like that. In our case, our data is not publicly available. In fact, it's all very proprietary data that we've collected over a very long period of time. The other thing about our data is our data is, I'll use the term very messy, which is to say, you need to not just be able to gather the data, but you need to be able to cleanse the data, bridge code, anonymize, link the data. What we get in terms of data is extremely messy. I mean, it's multiple ontologies. It comes from various spots around the globe. It's not like there's just one big trove of data there. The third distinction I would make about our data is it's very dynamic. It's ever-changing. It's not static. I mean, it changes daily. We process more transactions daily than the New York Stock Exchange, so you have to be up to date with your data to meet your clients' needs. The last thing I would say is the data is very complex, and it's very sensitive. When I say sensitive, in the sense that we need to meet very strict privacy and compliance regulations in order to use the data, and those vary across the world. You have to have experience working in very specific jurisdictions. It's just not like you can go out and get the same data and use it in the same way in Germany as you can in the U.S., as you can in Japan. You have to know how to work with the data. Yeah. Now, look, theoretically, someone could... We get asked this question all the time: Could someone recreate what you have in data? The answer is theoretically, yes. Practically- No ... it's very difficult because we've been at it for 71 years. We get the data from 150,000 different data feeds around the globe, and we do a lot. We spend $hundreds of millions annually on that data, and we spend additional $hundreds of millions making that data fit for purpose. Yeah, theoretically, someone could recreate our data set. Many have tried. Practically speaking, nobody has to date. It's a very difficult thing to do. We think it's a very durable moat around that data. Another thing that makes it durable is just knowing how to use the data, and that's a domain expertise. You need to know the business rules. You need to know how to work with the data. It sounds perhaps trite or trivial, but it isn't. It's very, very tough thing to do. You know, the last thing on AI, you need to know how to use AI to use the data. A given process may take dozens of AI agents because you have so many sub-processes that need to be agentified, and then you have to have one kind of orchestrating agent over top of it. In order to use AI data, it's not a simple thing to do, and that's why so many of our customers are coming to us to ask for AI solutions. Theoretically, a client could take the data and say, "Okay, we're gonna try to do something with it." It's very hard for them to do, and there are economies of scale and having us create solutions, like launch planning solutions, that we can sell across multiple customers. In fact, there's another restriction there, that when we license data to our customers, they have we do it for specific purposes. It's an end product that we're giving them. Right ... not all the ingredients that are underneath that. We have third-party arrangements or agreements that specify exactly how that data can be used. It's not like a client could just take our data and go give it to, you know, one of the AI companies and say, "Hey, have at it." They would need our approval to do that. There are many reasons that we don't feel we're vulnerable here. Actually, on top of that, many reasons, particularly the economies of scale, are developing these AI agents for... and selling them across multiple customers, we think it gives us good upside looking forward. In fact, we haven't seen client behavior change, where they're not buying stuff from us that they did before. In fact, quite the opposite. Right. They're coming to us and saying: Look, we want to do things more efficiently. We've got this huge staff of people, again, I'll go back to the launch planning example, you know, working on taking various data sources and spending months doing planning for a launch. Can you do that for us much quicker using AI? That's just an example of one of the applications. In fact, I think we now, at by year-end, had done 150 different AI agents covering 30 use cases. It's changed since then. It's gone up. It changes daily. Yeah, this whole shift to AI is fantastic for us. I mean, because I mean, listen, if you step back and go back to the theory of the merger of IMS and Quintiles coming together, right? The whole ethos of our company was taking that, you know, 70-some-odd years' worth of data and disrupting sort of, you know, clinical trial development. What it's done now is that it's put it front and center in our clients' minds. Now, the conversations with our clients, we are elevated in their minds, right? They're restrained on capital, and they're sitting there going... You know, at the end of the day, can they build some models themselves? Sure. Your models are only as good as the data it's trained on. Right. We have the best data in the industry, both on the clinical and the commercial side. The types of engagements, now are completely sort of elevated, and that's why we have clients coming to us. Yeah, rough estimation of the amount of, where pharma gets its data, it's about three-quarters of the data that pharma uses comes from IQVIA across the industry. That gives you an idea of how important our data is. Yeah. Yeah, one of the questions I get, and again, I think people are trying to get to the root of the AI question is- Sure ... you know, where does the data come from? Why do you guys have so much versus others? You want to just spend a few minutes in terms of the root of the data and why it's such- where does it come from? I mean, it, Yeah ... it comes from multiple sources. It comes from scripts, it comes from electronic medical records- Claims data. Claims data, lab data, genomic data. One of the keys is the ability to link data longitudinally on a de-identified basis. Right. I can go and look at your history. You're person X, you're not Patrick. We don't know who you are, but we can trace your prescription habits, look at the electronic medical records, look at the claims data. That's one of the basis for using real-world data, is being able to do longitudinal studies across large masses of people. Like I say, it comes from 150,000 data feeds, and we are the only company that can do this globally. We have competitors on the script side in the U.S. or Germany or Japan or wherever, but we're the only person that can put together a global view for a brand manager of how the brand is doing, and that's a huge differentiating factor. It's all of those thousands of business rules that govern, you know, what Ron just talked about, how you pull the data together, that only we have. Our clients don't have access to it, which is why it makes sense for them to come to us. Yep. Okay. Then another area of tasks, you know, from our conversations with investors, people are looking at is just the durability of the consulting business. Yep ... inside there. I mean, what would you guys kind of frame up as a response to the consultants? The, the first thing I would say is there will be small areas of our business that are going to be eroded by AI. There's no question. I would emphasize small, limited, and an example of that would be in the consulting business, in primary market research, in particular, in places like the U.S., where a lot of this data is publicly available. To put a number on that, if you look at primary market research is maybe 5% of the consulting and analytics business globally, which is 20% of the TAS revenue. We're talking about relatively small numbers here, and even within that 5%, not all of it's exposed. There may be other, there probably are gonna be other little pockets of low-end work that are gonna be exposed. The upshot of it is, we really feel like the opportunities far outweigh what we're going to lose. Right. Mike, maybe you can expand on some of those. I think, you know, kinda sizing me to the numbers Ron was throwing out there, I mean, you wanna take a pessimistic case, maybe a $100 million. That's the kind of sort of scale of revenue that we think could be at risk, but people really need to start pivoting and think about sort of the opportunities there. I'll give you a couple examples on sort of several different dimensions about what we're doing. You know, let's just say from a revenue protection standpoint for some of that lower level kind of work, right? We launched last year our agentic AI kind of like copilot kind of thing, that we've put on top of several of our offerings that we have out there, right? We're modernizing some of the lower level to keep it relevant and to keep clients sort of stuck into us. You guys may have seen a press release we did with Boehringer Ingelheim, fairly recently, with that they bought our DaaS +, Data-as-a-Service offering. That's an agentic AI offering, which essentially allows a client to take their subnational, national, and global sort of prescription data with an information management platform, to then help hook in sort of data that they have, so they have one single source of truth for all of their data. That inherently brings a lot of value to our customers. What it also does for them is that if they want that capability, they have to buy all of our data, right? It protects our data sales, right? It also, in areas where they may have had, let's say, a specific country, they were sourcing that script data in that country for somebody else, well, they have to, they have to now buy it from us, right? That's another kind of example here. Then you have, and Ron mentioned it, you know, kind of the more transformative offerings that are coming out on the commercial side, like our launch planning tool. Pharma employs thousands upon thousands of people who are specialized with, let's say, sort of market research, and competitive intelligence, and sales forecasting, and things like that. At our TechIQ conference last year in London, we rolled out, and we have some clients on it, this launch planning sort of agentic AI module. Our teams came back and said, literally, like, pharma's jaws were, like, on the floor. Because, you know, one person can go and say, "I'm gonna launch this drug. Give me a global sort of launch strategy." The agents are going through all of our data and all of those sort of verticals, the forecasting, market access, things like that, and just spits out, like, a board-ready sort of, like, launch plan in a minute. That gives pharma options that they can, you know, either redeploy those thousands of resources sort of internally, and that brings a lot of value. To Ron's point, you know, any technology changes, some things are gonna go away. One thing on the clinical side, just to kinda give a corollary there, you know, I was thinking back to, like, with all this AI hysteria going on at the minute here. You know, if you go back to, like, the early 2000s, right? The narrative at the time, I remember, was going from paper case report forms to electronic data capture. The headlines were, "CROs' business models are gonna collapse," 'cause they make a lot of money with people sitting there sort of, like, doing typing. What happened? Like, if you look back in retrospect, CROs didn't collapse, they grew. The ones that adapted, like IQVIA is adapting with this technology, grew even faster, and the question is, why, right? Well, in that specific instance, right, yes, certain line items, let's say, of a CRO budget, like double data entry, those went away, okay. What that did do was, is that because the data is now in an EDC, coming in in a more contemporaneous fashion, it allowed for new services to pop up, like centralized monitoring, right. Risk-based monitoring, or you can do more interim analyses because the data was coming in more frequently. With any technological disruption, like, there are going to be upshots. The other thing that happened there is because it was easier to collect data, it actually helped study trials to become more complex. People started adding more assessments in the trials, and that's obviously a net benefit. Whether it's on the commercial side or the clinical side, you know, there's a lot of opportunity there. You know, our moats that we have around our data and our workflows is key. Yeah, it's easier to visualize the downside in AI than it is the upside. Trust us, what we're seeing is that there's going to be a lot of upside here. Yep. Mike, you've framed that $100 million number. Is that more... Obviously, Ron talked about the 5% of the 20%- Yeah. - of the fifty percent. Yeah. Is that kind of. Yeah, that's what I'm talking about. Yeah, yeah. Yeah, sure. Okay, gotcha. Maybe on AI, you know, just overall improving efficiency and workflows in clinical trials... Yeah. right? If timelines get shorter- Sure ... burn gets faster, what are you hearing in terms of how those savings, if you will, would be distributed to CROs? Yeah IQVIA? What's the right way to think about this ecosystem? There's no large pharma procurement people listening to this call, are there? No. I mean, listen, just to give a another kind of, like, framework here on how to think about this. You know, you hear pharma companies out there now: AI, AI. I think when Pfizer had their call recently, people were like: "Oh, my God! Albert mentioned it 15 times. Like, what does that mean?" You know, most of what we're hearing from our clients is that where they're focusing AI first is, like, on the drug discovery side. Mm-hmm. Right? Our theory, and it's a pretty prevalent sort of theory in the marketplace, is that that is going to be an area where we start to see the first kind of, like, step change benefits of AI, is in the drug discovery space. You know, you can easily envision, pick a time prize in 3 - 5 years, probably somewhere in that window, where more molecules are going to be identified with higher probabilities of success, which fundamentally changes the ROI calculations. There's going to be, in our estimation, a lot of molecules coming through the discovery area into clinical. By the way, I just mentioned discovery. We announced yesterday, you know, we bought a great asset off of Charles River's, you know, hands in the discovery space. Again, that sort of played into our thinking on that front. You know, pharma, and I think Pfizer even said it, pharma is going to reinvest the savings and the economies into improving their pipelines, because at the end of the day, that's how pharma companies are valued, and they always have these patent cliffs looming over their heads. There is going to be a virtual cycle of this efficiencies. To get to the specific part of your point about how this is shared, I mean, look, in the clinical space, I think people need to realize a couple things. One is, it is highly regulated, and it moves very slowly. We're looking at quite literally 1,000 individual processes that underpin our CRO for Agentification, right? We're going as fast as we possibly can to them. Once you develop an agent, in some cases, you can't just pick that agent up and deploy it on studies in flight, right? There's that regulatory break to how fast this stuff can come through. I think the other thing people need to sort of remember here is that, you know, at the end of the day, we have, with large pharma, we have deals and rate cards that are three to five sort of years long. The fears of some immediate deflationary shock to the CRO numbers, it's just not gonna happen, right? Generally, what happens, kinda going back to that EDC analysis, is that when we get more efficient, yes, we pass some of that sort of on to our clients in the form of negotiations. In our budgets, some people kind of misconstrue that CRO budgets because they're heavily labor-based. They're not time and materials contracts, right? You have unit-based rate cards that have certain effort assumptions baked into it, but it's a unit. If I can agentify faster, right, I get to keep, you know, a big part of that upside, you know, for myself, and some of it will be shared through the negotiation. You know, at the end of the day, you know, what we think is gonna happen is that our margins are gonna continue to improve in R&DS, and we're gonna continue to take share. Pharma will with the better ROI that they're seeing on their investments in research and development, you know, the big question is, well, are they just gonna put that in their pocket and not develop additional drugs? I would argue, and what we're hearing from clients, is the opposite. No, improving ROI means we're gonna invest more in drugs because we're valued on our pipelines. To the extent that we can put more drug candidates into our pipelines that have now better return on investment prospects, we will. Yep. Mike, you touched a little bit on it, but, you know, in terms of that upstream versus downstream, it sounds like your guys' view is AI, kind of in the upstream molecule screening piece- Mm-hmm ... it almost is gonna increase the number of viable programs. Is that- That's our opinion, yeah. Yep. That's what we're hearing from our clients as well. Yep. The one thing to keep in mind, is that still most of the development that's going on, work or research work, is going on is traditional still. Yep. I mean, it will accelerate over time, but it's not like you're throwing a switch here. The second thing to remember is that drug discovery is still, to an extent, serendipitous. For instance, if you look at, you know, Viagra and Minoxidil, those drugs were originally indicated for conditions other than ED and hair loss. It just so happened that in a serendipitous manner, the industry discovered that they had other uses and that were even higher valued, and that happens all the time. That's gonna continue to happen, even in the face of more rigorous use of AI for discovery. Yep. Okay. maybe we can flip a little bit to kind of the core business. you know, on the R&DS side, you know, can we talk through, I guess, four Q, you know, bookings, cancellations? You know, it sounds like cancellations were a little bit at the higher end. It was a little unclear. Was it one or two big chunky ones? Sure. Was it not? Maybe you can talk on the cancellation side, and then we can dive into the. Yeah. Bookings as well. You're gonna bait me into a book to bill rant here in a second here. Now, listen, I think, you know, we've talked previously that 2024, we really saw elevated cancellations. About in a normal year, the CRO side would see about $2 billion worth of cancellations. 2024 was about $3 billion, and that was really driven by the mass pipelined reviews that were really triggered by the IRA. 2025, we absolutely saw that trend stop. Our cancellations for full year in 2025, even with them being a bit elevated in the fourth quarter, were really back to normal reasons like drug futility and things like that. I just want to be crystal clear, given the AI hysteria, nothing that we're seeing relative to cancellations, RFP flow, or anything, is being impacted by anything related sort of AI, right? What you're seeing from a cancellation standpoint is just study-specific, you know, idiosyncratic sort of events and things like that. You know, we feel pretty good about, you know, Q4 has some seasonality to it. Q2 and Q4 are generally the bigger kind of like gross bookings. You know, cancellations, there's no seasonality to them. Whenever they get reconciled and come out, that's when they come out. I say that to caution people not to try to extrapolate some linear sort of trend there, because kinda Q1 and Q3 are generally lower quarters coming off of a year-end, and obviously, the summer sort of holiday period, just for some additional context for some of youse who overly obsess on this quarterly sort of book-to-bill metric. no, it was there was nothing out of the ordinary to call out there from a cancellation trend standpoint. you know, book-to-bill is actually being highlighted, I think, because one of our competitors is undergoing some accounting scrutinies, and it's calling into question, you know, book-to-bills. Again, I'll maybe do a micro rant here, listen, it is without a shadow of a doubt, particularly now that there are only four people who talk to book-to-bill, it is the most misunderstood and misused sort of metric in the industry. It's a long cycle business. I hope you guys know this. I'm sorry for repeating it. The way our stock moves, you know, with whatever quarterly book-to-bill we put out there or whatever somebody else puts out there, that has nothing to do with us. You know, it feels like our stock always moves down no matter what we do. I'm sure that's not the reality, we just want to caution people that, you know, when everybody-- it's not a GAAP metric, everybody's got a different sort of booking policy. One of the first things Ari did after the merger was, you know, Ari comes from manufacturing environments and defense, right? You know, he said, "Well, what's, what's the industry standard?" It's like, everybody does it on this as awarded, on verbals, and stuff like that. The first thing Ari did was like: No, we're going as contracted. We firmly believe, and we stand behind, that as-contracted basis to put things in your backlog is absolutely the right measure, right? You look at the GAAP measure that everybody's out there, this remaining performance obligation, which is a little bit different than backlog, but it's close. You look at what our CRO backlog is versus what our enterprise RPO number that we disclose every quarter is, right? Those numbers are really close, right? There's, like, $3 billion. To stress, the RPO is a GAAP number. Correct. Correct. You look at some of the other competitors, and they have their backlog is far in excess. I mean, you could drive a truck through some... You know, it really caused us to ask ourselves sort of a lot of questions as to why that is, right? Again, at the end of the day, you know, we stand behind sort of our processes. We feel that we have some of the most robust sort of non-GAAP, as well as sort of kind of GAAP disclosures in the industry. Yep, understood. I appreciate that, the micro rant. Thank you. maybe on just the overall backdrop, again, gross bookings seem like they're ticking up. What are you guys seeing from, I guess, both pharma-? Yeah. Obviously, biotech has had this. Yeah -funding recovery. I know you guys have plenty of exposure there. What are you hearing from customers, and what are you seeing just on that gross bookings backdrop? Well, generally, if you look at the leading indicators we indicated, we gave you in Q4, it all looks good. The pipeline is good, the RFP flow is good. We saw a nice bounce back in the back half of the year in emerging biopharma funding, and our conversations with clients have been good. You know, I always caution that, as Mike did there, don't put too much emphasis on quarterly book-to-bill because things fluctuate around. Look, if you're gonna choose a statistic to track the 12-month rolling anyway. Overall, the environment looks very healthy. Anything you want to add to that? No, I would agree. Okay. Again, it seems like obviously we had the pharma, there was, you know, multiple headwinds for a long time. It seems like things did loosen up mid-year. Again, biotech funding picking up. Are you seeing customer conversations kind of steadily improve on both fronts? Is biotech notable with the funding piece? No, I think they're both good. They obviously are dealing with they have their own sort of, kind of flavors to them. You know, there is, you know, the, this general sense of comfort and people more willing to make the decisions right now, with whether it's sort of policy, sort of uncertainty, sort of being clarified, or funding on biotech, you know. That's why we've said on both the clinical and the commercial side, you know, we've steadily seen sort of client decision times, trend in the right direction. Okay. Maybe talk some guidance metrics, which I guess you now own, Mike, I'll point them towards you. I guess, how do you think about, you know, maybe down the P&L, the gross margin piece? We get a lot of questions about some of the. Yeah pricing stuff that's happened Sure over the last year. Obviously, some of the peers with pass-throughs and pricing, have some noise there. Yeah. Maybe we start with gross margins, what you guys are seeing, and maybe talk a little bit pricing. Yeah, let me kind of frame this out a little bit because, you know, I think given the dynamics and what's going on. Yeah ... you know, we probably should talk a little bit deeper than we have historically about it. If you look back at IQVIA since the merger, I believe every single year we've expanded margin, EBITDA margins, with the exception of 2020 when the pandemic hit, and 2025, right? Where we declined 70 basis points on a reported basis. I'll give you. I'll use 25 as kind of a construct, right? An illustrative construct. You know, there's a couple things going on here. One is, you have some very significant non-operational dynamics going through our EBITDA margins, right? That's FX and pass-through. When the dollar changes, particularly when it weakens, our revenue goes up, but our, the denomination of our cost base, IQVIA, is pretty sort of muted from any sort of currency changes. You don't see a lot of change on profit. FX kind of can throw swings and roundabouts into your margin from that standpoint, and that's obviously a gross margin-related item. You have pass-throughs, right? Yeah, I would love if we never had to report on pass-throughs, let alone try to forecast multiple billion dollars of pass-throughs and when they're gonna hit and all that stuff. We saw, you know, pass-through tailwinds. Those two things just mathematically compressed our margins. If you take those two non-operational dynamics themselves in 2025, I'm speaking in rough generalities there, those two things were about a 70 basis point headwind to our reported margins. You get into things like mix and a little bit of pricing kind of in the mix. When I say mix, meaning, you know, where we saw things like services, where, like FSP, with lower margins growing faster than the core, CSMS growing faster than some of the Commercial Solutions, things like that, and maybe a little bit of pricing kind of thrown in the mix here. You know, that in 2025 was about another point of margin, sort of headwind. Absent us doing anything else, our margins would have declined, on a reported basis, 170 basis points. We have our productivity programs, right? That we do sort of all along. To be honest with you, agentic AI is just another tool in that toolkit there on the horizon. You know, that added about a point of tailwind, right? If you look at our 70 basis points and how you should think about IQVIA's EBITDA margins going forward, you know, really, our productivity programs kinda offset mix plus or minus, and that's what gives us confidence when we're constantly asked about that long-term outlook we disclosed in our Investor Day. That, look, in any given year, we expect EBITDA margins to be between 0 to 30 basis points of margin expansion. That's kind of really what we're talking about. Could FX and pass-throughs kinda distort that? Yeah. Kind of operationally, that's really what's going on in our business. We're very disciplined there, and we're really trying to get people to focus more on the EBITDA dollars than the margins, just given some of those distortions. Sure. Yep, you mentioned the mixed pricing piece. I know that was probably a bigger concern and discussion. Yeah. -maybe a year ago at this time. Yeah. Seems like things have eased up. What's the pricing environment? Pricing environment is stable. I mean, really and, you know, one of the reasons why when people would push us, like, "Aren't you worried about sort of the pricing?" We're not being dismissive of it, right? Because pharma is very sophisticated, you know, but, you know, here's the reality. If we make, A, we're very disciplined, where we make sort of very smart, strategic, disciplined decisions in our pricing. When we do make a bet on something and lean into a particular, sort of price, it goes into our backlog. It goes into a $32+ billion backlog, and that study is gonna burn over 3 - 5 years, right? We have our ongoing productivity initiatives, and we consistently monitor... Like on a full service trial, we monitor the margin that that study was sold at versus how it's being delivered. That's actually one of the beauties of the EAC methodology, is any given point in time, you know, that's what you stare at. You know, we consistently deliver on a portfolio basis, you know, 1 to 2, 3 points higher than what we sold at, right? We're confident in our ability to continue to drive productivity. Okay. Maybe the balance sheet, you know, leverage. Uh-huh. I think 3.6 at this point. Can you just talk about where we're heading on that front? Again, you guys have done a good amount. You had mentioned the Charles River deal. Yeah. You've done some deals, some share repos. What are the priorities, and how should we think about the leverage piece? Nothing's changed on that front, is the short answer. I mean, leverage within a 3-4, you know, kind of turn range is something that we're more than comfortable with. You know, we always try to do acquisitions, 'cause they're obviously platforms for growth. You know, if you asked me that same question three weeks ago, before the AI drama sort of ensued, I'd say we'd probably be more opportunistic in M&A, but certainly our share is a screaming buy, or our stock price is a screaming buy sort of right now. Yeah, we are opportunistic, which is to say, how we divide up our capital deployment between share repurchase and acquisitions depends on the strength of our pipeline and pricing, what people are asking for, and then also our stock. Obviously, given where our stock is today, you can imagine where our head is about the balance between the two. Yep, that's fair. Then maybe in the last few minutes, you know, unique opportunity here with the outgoing and incoming CFOs. You know, Mike, as you take the seat here, is there any different approaches you have versus what Ron did, whether it be capital deployment, cost savings, et cetera? What a devilish question to ask with Ron sitting right next to me. Ron, why don't you put on some earmuffs here for a second here? Listen, the short answer is no. I mean, the word that comes to mind is continuity, right? I've worked with Ron and Ari for 9 years. You know, we're gonna continue to be sort of very disciplined, sort of financially. We're gonna continue to have very high standards across the organization and in all areas, including in ethics and compliance and things like that. Look, I'm excited to where this agentic kinda runway we have in front of us and to be able to support taking the business forward. I don't know if you wanna- Well, look, I'd be disappointed if Mike didn't do stuff differently than me. That's one of the advantages of making a change, when you've had a CFO or an executive in a seat for a long period of time, and you bring somebody new in, you always get new ideas, and that's a good thing. I'm sure Mike will be making some changes. As he said, we've worked together very closely, so it's not like bringing somebody in off the street, where, you know, we've kind of worked hand in glove and share a mutual philosophy. It's a great opportunity now. I mean, we were, you know, I was sitting there lamenting kind of the weekly report that the IR team, you know, sends us. You know, we're currently trading at a PE of 13, which I'm not gonna speak for other companies, right? It surely doesn't make sense for IQVIA. You know, our historical PEs are high teens, sort of low 20s, right? You know, to people who own our stock, who we talk to and are frustrated, well, you know, look, this does not make sense, where we're being sort of valued right now. Our fundamentals are incredibly strong. I mean, look at the guidance that we put out there relative to what's, especially relative to what other people are starting to put out there. The entire IQVIA team is laser-focused in just keeping their head down and executing on that. Kinda to those people who don't own our stock right now, I would say this makes no sense right now, right? You know, the fundamentals are strong, and we're laser-focused on continuing to kind of, you know, keep delivering sort of value here. We're pretty optimistic. Look, we see AI as an opportunity, not a threat. It's clearly being priced into our stock right now as a threat. We feel that's inappropriate and see it as an opportunity, and we'll just have to prove that out over time, because it's very hard to disprove a negative, a generalized negative. Yeah ... like we're dealing with right now on AI. Yep, thanks for having us. Yeah, it's great to spot then. Thank you so much, Ron. Enjoy retirement. Thank you. The Nepal trip, I guess. Yeah. The famous Nepal trip. Will do. Thank you, guys. Thank you. Thank you.