IQVIA Holdings Inc. ($IQV)

Good morning, everybody. Luke Sergott. I cover life science tools and diagnostics for Barclays. With me, I have Mike Fedock, CFO of IQVIA.

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 bogey of AI is coming, right? And it's really hard to just prove the negative. So kind of -- and already talked -- and you guys talked about having 70 agentic modules running out. 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 and then like interest in where you think like the initial demand is going to translate into business growth.

Yes, yes, absolutely. No, great question and obviously incredibly timely. Firstly, this AI phenomenon's has -- it's a great for us, because, a, AI is a net positive to IQVIA on both in terms of revenue and margin expansion over time. And 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. And that's the first thing, I think, that was being misunderstood was the data, right? And you get this like kind of this high-level narrative with the AI bogeyman to say, well, you have data, and you sell data to pharma and therefore, you're going to be displaced. And that is just fundamentally false. If you think about our data, and obviously, everybody has kind of gotten around the notion of if you're building models, your models are only as good as the data that is built upon. And we, by far and away, have the most robust dataset 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, it's coming in. And that raw data that comes in every day is, in a sense, useless. And where -- what our secret sauce is, is that we take that data and you -- it's de-identified and you clean it and you code it, you bridge it, you link it together to actually make it useful. And that's our data moat. So that data is not available out there in the marketplace. And so clients have realized that. And it's actually changed -- it's fundamentally changed the way clients are engaging with us. The whole theory of the merger in October, we'll have our 10th anniversary as IQVIA was to take that at the time, 60-plus years of IMS data and use it to completely transform clinical development, right? So that's the whole theory of why IQVIA came to be in the first place. And 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. And we would sit down with a pharma company and they said, you ask us to bid on this protocol. And we bid it to spec because it's competitive, but here's our AI team has 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 going to do to speed up enrollment and reduce sort of dropout. And years ago, pharma would go, "oh my God, that's amazing. But thank you. We've always done it this way. But now that's changed because now pharma wants to use the data to inform decisions. So it's like elevated. So now they're actually pulling us in. And in '25, I think we've deployed over 150 agents. Our roadmap is by '27, have over 500 agents. So we're going sort of at pace. And 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 built within their operations. So yes, it's a net positive for us, and we're excited about the outlook.

Is that across both the research side and...

Yes, both clinical and commercial. Yes, 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 do the deal. I remember when you guys came out with a heat map, and we were just like, Oh my God, this is amazing. You can figure out which doctors are ordering based on this data and just accelerating. And this just feels like giving that backbone of your business like steroids, this is like a natural evolution of how things are going. And so when you're engaging with customers now that their mentality flipped to be like, oh, we know what we're doing, to, how can you help? How much are you leading with the AI piece? How much of that is your biggest differentiator right now?

Yes, we're leaning hard into it. And our teams are super excited because that engagement is being received on the other side. We -- one of the big fears that kind of came out is particularly on the commercial side, there was like, oh, people would have this hypothesis that your consulting business is going to go away. No, it's not going to go away. And we -- our teams are 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 net gains to have there. And when we looked at like our analytics and consulting, there are some offerings like primary market research or key opinion leader searches where you could probably scrape together good enough data that's out there. But we even kind of ran the simulation say, let's use Claude to come up with the top 10 key opinion leaders in a particular therapy and compare it to what our data shows us. And out of the top 10, Claude got like 3 out of the top 10, right? So even in the most basic use cases, it's still not as good. And what our clients -- what we're finding with our clients is there's so many use cases out there, particularly in the commercialization 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. And we even learned that one pharma company in particular, I think, started out with doing 700 internal AI initiatives, and they've already killed half of them. So everybody is playing. And that's from drug discovery to clinical and to commercial. So the level of engagement we're really leaning into the AI effort and what we bring to the table.

Yes. And I mean, I feel like it's one of those -- it's all promise right now. And we -- the rapid adoption and potential disruption really needs to come from showing that it is shrinking -- 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 what you're -- 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, our trial execution would have been like 10% or 20%. Have you guys done anything like that on internal studies or looked at that?

Yes. I would say just to help people think how to think about kind of AI and how that will start manifesting in our numbers over time here. And I think time is the key thing to put out there. On the commercial side, it's a shorter cycle part of our business. So I think that you will see organic revenue growth acceleration and margin accretion as those agents get at scale and are adopted at scale. And we're already selling them, and it's already in our numbers, but that's $7.3 billion part of our business, right? So 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 identifying our internal processes. So it's more of a margin expansion play there. And the thing that people need to realize is that in quite literally the 1,000 individual processes that kind of 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, right? Where you have to get the sites contracted and inform consents and things like that, huge potential. But when you have that agent, because of the regulatory nature of those studies, you can't drop that into live studies, so, it's going to come out as new studies start to get launched, you'll apply those agents on a go-forward basis. So there's a ton of promise in the clinical side around accelerating particularly site start-up, how you handle the regulatory documents for like Trial Master Files. It makes your CRA more efficient and you can get more throughput through them. So -- and then obviously, there's some benefits in like Data Management. You can speed up the setup of the database and things like that.

Yes. And that's one of the key questions has been and pushing back on just broad cloud adoption and disruption is like you have to plug into the funnel, like there's a lot of hesitance to put like your tax returns up on cloud right now. Like pharma, that's like that's it. That's their whole terminal values like on that side.

Exactly.

So it's like this -- they're already working with you, 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. And obviously, with the -- it's built on our data, which is more robust than then building it on their internal datasets. And I think one thing that's been resonating over the past 3 weeks or so with investors on the clinical side that to kind of dispel the bogeyman in that part of our house is just reminding people to give an analogy, right? And I remember like when the headlines were coming out to basically say AI is going to fundamentally disrupt the CRO business model, right? You kind of -- you talked about PTSD. I go back in the early 2000s, right, when I remember the headlines were CRO business models are going to collapse because people are going from paper CRF to Electronic Data Capture and pharma was going to have all the data and CROs make a lot of money. And what happened? If you look back, CROs and budgets grew and even accelerated. And absolutely, there were certain line items or services in the budget that went away. I mean CROs used to charge $2 a page or whatever it was for double data entry of paper, and that goes away. But because you had Electronic Data Capture, we can get access to the 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. And trial complexity accelerated because it's like, oh, if I can collect data easier, I want more data to inform my trial. So we think that AI is going to do something similar on the CRO side. It's going to open up new potential offerings.

Yes. And so I promised I wouldn't go over half our time talking about AI. I'd love to talk about other than -- 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. And I think from a -- when you think -- so let's talk more about just the demand environment itself on the clinical side. It's been recovering. Book-to-bill has been improving. You guys have been showing nice growth in the bookings side. Can you talk about just that existing demand environment right now? I mean, -- and we all -- the problem is we all go back to like the heyday of pre biotech spending, right? And like pharma was just like everything was up and to the right. And so now it's been this kind of -- is this one of those another false starts that we're getting? And 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. So just give us the lay of the land of what you see right now and not how that comped before, but like how -- what's been changing?

Well, with book-to-bill, I think it's pretty well known about our feelings on that particular metric. I mean it is used metric in the industry and people over-rotate, both to the good and the bad on any quarterly book-to-bill, and we don't forecast book-to-bill. It's an impossible test. But when you take a step back and you look at book-to-bill over time, it's an indicator, and it's interesting. What I can say is that from the metrics that we track and the conversations that we're having with our conversations, 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 '25, the decision timelines kind of moderate. And the conversations with our clients, there is clearly more certainty this year than compared to last year. So it just feels better. And then you throw on top pretty robust actually biotech funding. All that together certainly feels like '26 is going to be a better year. Now the rate and pace of that and how that translates into the quarterly book-to-bill, I don't know, nobody knows. But certainly, the interactions with our customers is a lot more optimistic.

I mean '26, 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.

That's true. And then on the See More, Win More strategy with biotech, Talk about early traction there. Any new logo wins? -- obviously, not going to give those, but how that has really translated and revitalized that part of your business?

Yes, it's been great. And I think part of maybe the misnomer and maybe we didn't do a good enough job at explaining kind of the See More, Win More strategy, everybody just went to like it's like a price thing. And that's really not the case. I mean when you're competing for EBP work, price is always a factor. But really, giving EBP customers the confidence that you're going to give them the attention. And we have a biotech delivery model. I think Quintiles bought Novella in 2013, and that's like IQVIA Biotech. So none of this is new for us. So doing a better job of telling our story and highlighting like we have a bespoke delivery model for what you need is key. And the other thing that we did was really twofold. One is looking at our engagement model with these customers. And 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. And we also capitalized, quite honestly, on the churn with the FDA, where you had a lot of reviewers and regulatory therapeutic and regulatory experts leaving the organization. And we were snapping them up because you take with that experience -- and then you get that early engagement with Chief Medical Officers and Chief Scientific Officers at these biotechs, and that engagement is there. And the other thing that is very encouraging about 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. And you are seeing biotechs take their development further into clinical. It kind of used to be, as you probably know, that they used to get to like a Phase IIa proof of concept and then they would out-license. But now they're going deeper. Now we're even seeing biotech companies actually want to go into some of the commercialization, which is great for us.

Yes. On the -- I mean, that was one of the feedbacks. But also your definition of Emerging Biopharma. Some of those are pretty big biotech, right? I mean it's $500 million revenues, $250 million...

I am constantly amazed at the depth of that market. I mean there's so many companies out there across the globe and doing great science. And part of our, I would say, vetting, but our process around EBP is that, obviously, we're very disciplined from a funding standpoint to make sure that when we make a sale, right? And we put it into our backlog, fund, we have that funding certainty. But also from a scientific standpoint, we really are pretty particular about vetting the science and making sure that what the client has when we want to invest in that early engagement to help them that the science is robust. But yes, it's an amazing part of our industry.

And given the depth of that market right now, and you're talking about this being the fastest part, is there a certain size that's outstripping the other? Or is it just kind of broad-based across that?

I think for us, I think we've been really pleasantly surprised at going deeper into that market in the smaller size and 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.

And you're talking about getting in earlier and earlier with the customer. It feels like investment banking, where you want to be involved at the very beginning. But kind of my terrible way of segueing into the Charles River deal. Where I was going with that segue whatever. So the -- just walk us through the strategy here on those European assets from Charles River getting even further 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 '22, we started looking in that area. We saw that it was an opportunity for us to expand our capabilities. And then we also saw the prospect of where this AI could potentially go and help drug discovery and identify and pull more molecules through. But in '22, I believe it was, we bought a company called Specifica. And that was part of our -- we put that in our lab business. And Specifica is a large-molecule drug discovery business that we're delighted with. And since then, we've been looking in the market for a small molecule discovery business. And we looked at a bunch of companies and either the valuations weren't right or the capabilities. So we were delighted when Charles River obviously has been very vocal about their efforts to look to divest what they term non-core parts of their business. And when our head of our lab business, Dave Morris and our corp dev guys came to us and said that Charles River reached out, they laid out here's the capabilities and the footprint that they have and they mesh that up with what we already have with Specifica, and it was like a hand-in-glove. So we were delighted to sign the deal on that asset at a very good price at that.

And is it more because of the couple of deals, do you envision or is the strategy just to continue to -- it's either we want to get even bigger in there or we're just going to 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, but we're pretty excited about the prospects for Discovery in general. And if you look at the client segmentation when it comes to Discovery, typically Large Pharma keeps a lot of them in-house. And we also see it as another mechanism that Biotech really needs Discovery. So to your point, it helps us get in...

That makes total sense. In the last 2 minutes here with the CFO, I think we should probably talk about margins. So we've talked about the pass-through. You have 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 walk us through those changes and how you see -- what are you guys doing from an offset? What levers are you pulling? You talked a little bit about AI, but like what else can you do in the near term and long term?

Yes. I mean, look, we have a great track record IQVIA in expanding margins year in, year out. And I think that it was the only 2 times in the past 9 years where we haven't expanded margin. One was 2020, and obviously, that was the pandemic. And last year in '25, where our reported EBITDA margins contracted by 70 basis points. And 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 have non-operational dynamics like pass-throughs and FX. And then on the operational side, you have mix issues, mix and pricing that you were alluding to and our productivity programs. If you take just 2025 and that 70 basis points, almost all of that reported margin degradation was because of non-operational. So we just want to make the point to investors to say, operationally and structurally, right, we are very sound. And I had somebody tell me one time, they're like, yes, you can't -- you got to focus on the EBITDA dollars, not the margins because you can't buy a sandwich with a percentage thing. But we certainly understand people's focus in there. So if you look at the mix headwinds from things like FSP and CSMS, let's say, growing faster than some of our higher-margin parts of our business, our productivity programs generally cover or are the things that give the margin accretion there. And our productivity programs are things like the blocking and tackling like spans and layers and looking at the levels of the numbers of managers to employees and real estate and all those other things. But automation has been our cornerstone, whether it was Robotic Process Automation and now agentic AI is just the next lever. So we remain confident that our productivity programs will continue to outpace any mix headwinds we have.

Great. Thank you.

No problem.

That's all the time we have, unfortunately. Thank you.