Paula Brown Stafford: Modernizing Trials Without Breaking Them

Ram Yalamanchili (00:04.259)

Hi, Paul. Welcome. How are you doing?

PAULA BROWN STAFFORD (00:09.27)

I'm well, thank you, Ram. Nice to be speaking with you again.

Ram Yalamanchili (00:11.119)

Yeah, I'm very excited to speak to you today. And I think just for our audience, I'll introduce you quickly. So Paula Brown-Stafford is a highly experienced clinical research executive with over 35 years of experience. She's been, I would say, early to the industry in terms of seeing it develop from, I would say, the early stages of CRO formation, the whole industry, guess, having been one of the early

contributors at Quintiles and eventually president of clinical development and now CEO of Allucent. Paula is also an author of the book Remember Who You Are, which is focused on leadership, success, balance and fulfillment. I'd love to get into that today and also named the distinguished alumni at UNC Chapel Hill and also top 10 women in biotech by FIERCE. So I think that's

probably a small list I could gather. I'm sure the list runs long, but I'm very thankful for you coming on today and hopefully we'll be able to explore quite a few of the questions I have around where you've seen this industry come from and also where you think it will be going down the line, right? So yeah, with that, I will start with my first question. One of the things which is I think really unique and great for a perspective is,

You were there, I feel, at the beginning of what we are today calling the CRO industry and the clinical research industry, right? So what I'm curious about is what can you tell about your early journey and also just the evolution of the business itself, right? Why is this industry in existence? What was the need for it to form? And of course, now it's a large industry, but I'm just curious if you could kind of face yourself back into the early times and then sort of give our...

audience a bit of a journey on that.

PAULA BROWN STAFFORD (02:15.758)

Happy to. I'll try to do it somewhat quickly. So I joined the industry actually in 1985 and Quintiles, one of the first, had incorporated in 1982. So I came in about three years later and I was the 23rd employee. So I always remember, you know, it was 20 or so people. They were pretty much statisticians and programmers. And

There was, think, one other company out there at the time, and they didn't call themselves a CRO, it kind of evolved over time, right? What I joined was a statistical consulting company, and I joined it as a statistician still in school at the University of North Carolina, Chapel Hill. And why did it come about is that two professors were consulting and bringing expertise

to large pharma companies in Europe, actually, and they were bringing expertise to help bring products to market. So they were helping design and analyze data after the fact, analyze the data to try to prove a hypothesis. And they were bringing as professors in the School of Public Health,

and they were professors of biostatistics, they were focused on data. And so when we think about today, it all starts and ends with data. And how it has evolved, I won't go too far because I know we have a number of other topics to discuss, but it really was, and the company started growing because it was about the statistical analysis.

And then it was about, well, we have what we call dirty data. The data, there were extraneous data points. And you would get the data sometimes a year after a trial had completed because people had to physically go to a physician's office and collect data on paper and bring that back in-house. And we had to enter the data into a system and

PAULA BROWN STAFFORD (04:38.306)

Then you did QC on the data, et cetera. So it just took a long process. And as you think about the industry now, it's around making decisions better and faster. And that really is how the industry has evolved is continuing to, and also take cost out.

You know, early in my career, was shared, it was a triangle shared with me from a customer in California and it must have been about 1990. And, you know, he said, and I've used it many times, that it's all about time, cost and quality. Because the customers want to get a product to market faster because they want to get their return as quickly as possible. They don't want it to cost as much.

We see at the time I was saying it takes 500,000 to get a product to market. Now people are saying 2 billion to get a product to market because you're paying for all the failures as well as the successes. And then quality, you have to provide quality data or the FDA is not going to accept the data and approve a product. So those three steps are true throughout my now 40 years in the industry.

Ram Yalamanchili (06:00.517)

I So that's fascinating. I've heard the triangle previously and I think I've heard it in the context of you can get two out of three. I think that's what I remember about it. But I think the other thing you're mentioning is the cost went from 500 or something substantially lower to billions now for these amount of work, which is getting done to bring a drug to market.

I'm curious still, right? Like in terms of the structure itself, did quintiles and some of the work you've seen building with you and your colleagues, did that grow because the market itself grew because of the number of new drugs and new opportunities, new biotechs or pharma investment to R &D? Or is there a structural reason why you had to sort of like create a new CRO industry versus maybe just doing it within the pharma? Like why did it evolve to the way it is today?

PAULA BROWN STAFFORD (07:00.428)

Yeah, no, it's a good question. you know, in the early days, it was around bringing expertise. There was so much work going on in the industry that they needed more bodies, if you will. But then it went through a phase that I would say was more in the 90s, was more around. And this, feel like is cyclical and others will say that as well, that it was around taking fixed costs.

inside the pharma companies and making them variable costs. And so it was around pharmaceutical companies until the 80s. They did everything in-house. They did everything themselves. And so if they needed a clinical pharmacologist, they might need 20 hours a week from that clinical pharmacologist. But you know what? They had to hire one and they paid 40 hours a week. So they got to the point that they wanted to outsource

and so that they can have a variable cost and they could bring in resources as they needed them with the expertise they needed. Another reason to me is because of the M&A. the mergers and acquisitions within pharma, was all, you know, they used to be that they would buy a product not necessarily in their therapeutic wheelhouse.

And if they had been a cardiovascular, and there were a lot of cardiovascular companies, but if they were wanting to get into oncology and they would go, you know, buy a company, they bought the product, but they didn't want to buy all the people. But then they realized, not that they then realized because they knew, but they didn't have all the expertise in the house that they needed. So they would come to a niche player, a CRO, who had that expertise. And that still occurs today.

They generally try to buy more in their wheelhouse, but when they do, any M&A opportunity, any M&A that happens, what are the financiers looking for? They're looking for synergies. So when they look for those synergies, it means that they do reduce their head count. But then I think they find over time, they still need expertise in certain areas for those products. And so they go out. So it's a combination of

PAULA BROWN STAFFORD (09:28.418)

Moving from fixed cost to variable and it's also bringing in expertise that they need for a specific therapeutic area or a platform.

Ram Yalamanchili (09:38.277)

That's interesting. So clearly I see a financial sort of like reason on the variable to like capex optimization, right? But the other, guess, is also what you're pointing out is as you become a platform style company, as you go from one therapeutic area of focus to like multi-therapeutic area of focus as a biopharma, you're acquiring assets, you may end up yourself in a situation where you don't have that expertise and you need that quick. And the right way to do that is basically go out to

a CRO. like Quintiles right? So, and then that's what you get. see. Or a loose end now. Yes, of course. Yes. Yeah. So that is the interesting. So I guess what happened over the last 40 years is we've sort of just what started off as an early, maybe like smaller sets of these strategies have expanded. And of course now pharma is a very heavy M&A market. And so that kind of propels this kind of same structural requirement. And it's going as far as we can see, it's still going right now.

PAULA BROWN STAFFORD (10:14.552)

Allucent.

Ram Yalamanchili (10:38.501)

So, okay.

PAULA BROWN STAFFORD (10:41.614)

And they still need fixed costs, but there's always going to be a variable component that they want to be able to bring in and out. And so they're CFOs. You know, it's a little cyclical. We see some of the larger pharma now kind of shifting back to bringing in more fixed as they grow. But as they bring in an M&A, they're going to always have those areas that either they don't want to keep all of those

type of resources in-house that they want to rely on others and be able to stop and start with resources more quickly.

Ram Yalamanchili (11:20.901)

Got it. So one of the areas which I think naturally lends to my questioning is the early start of this whole industry, you've just described, there's a specific need on that. Data is a huge part of it. Collecting data quickly at an appropriate cost and quality are all important. And I guess the industry certainly has evolved in terms of modernizing itself and how these processes are performed, right? I'm certain...

in the new first started, it's probably a very different process. You just told us that it takes, know, somebody has to literally go to the site to collect the data. I mean, those days are not the case anymore. have EDCs, we have ways to capture this data in a quick format. And I also know you have been instrumental in developing data strategies for the industry. You've published on it. You've been in front of Congress around that. some of the, I guess, walk us through that, right? What was like, would you say the first

PAULA BROWN STAFFORD (12:01.55)

Thank

Ram Yalamanchili (12:17.125)

modernization effort and what did that look like in the industry? And I'm particularly thinking maybe like mid-2020, mid-2000s sort of a timeframe. I'm just curious how you would describe it.

PAULA BROWN STAFFORD (12:33.134)

Well, and it was the early 2000s when we started moving more towards electronic data capture. But I'll tell you, I remember moving from the paper and having to go out to the sites. And it was the white and then pink and then yellow, the three carbon copies. And we had to go out and pull one and leave one at the site. And then it was...

Ram Yalamanchili (12:51.407)

Yeah, carbon copy, yeah.

PAULA BROWN STAFFORD (13:01.262)

Actually in 1999 that I was collecting data via fax machines. So this was for a late phase study, but we were having sites fax data to us and then doing our entry from there. So you move from paper to fax and then quickly we moved into EDC. So the electronic data capture, which took a very long time.

for people to really embrace and adopt the EDC tool. Many pictures have been shared in the industry of going into a physician's office and seeing many different laptops and all these different plugs. And it was just so onerous on the sites. EDC came around and it was like, you just need one laptop.

but you may use five systems on that laptop. And so, you now you have issues with passwords because, you know, the physicians will not give their passwords to anyone, but, you know, they have to keep up with all these different passwords. So, you know, we do advocate that sites use, work with as few different partners as they can just because the sites have to keep up with so much. anyway, so the EDC came around. you know, then the need,

that it hasn't changed, certainly the tools and our capabilities have changed through the years. And so then you went from EDC to being able to capture via EHR, EMR. But that's also proven to be a bit problematic in that there have been so many different tools. Is it Epic or is it Cerner, which I think is now owned by

Ram Yalamanchili (14:49.605)

Oracle.

PAULA BROWN STAFFORD (14:50.862)

Oracle. So, you know, they all combined, but you know, there's two different. So then it's all about standards. So I did join the board of CDISC in, I don't know, 2007-ish and was on their board until 2015. And CDISC is all around standardization so that we could help deliver data to the FDA in a more standardized format, basically.

So that the review time at the FDA would not take as long because we would provide it in a more standard format. even with standards, people still have their own way of delivering data. But we focus on the C-disc standards here. So there's been, and in there, it was in the 2000s, maybe late 90s, maybe late 90s.

that we started using, we called it voice response, is how we started. People could key in on their literal phones, the old fashioned push button phones, where people could key in data for really patient reported outcomes or randomization of trials. And then that turned into IVRS, interactive voice response systems.

which then became IRT, interactive response tools. And I think today, what are we calling it? IRF, and now we've kind of moved to just ePro, electronic patient reported outcomes. So there's been this evolution that, yeah.

Ram Yalamanchili (16:26.465)

IWRS maybe, like the web-based tools.

PAULA BROWN STAFFORD (16:42.606)

Anyway, I could probably go on, Ram, but I think probably gives you a feel for just the tools continue to change. so now today, AI is upon us in a good way. And that's yet another tool. I know we'll get there in our discussion. But really, that's that 2012 to 15 evolution there.

Ram Yalamanchili (16:42.915)

Mm-hmm. Mm-hmm.

Ram Yalamanchili (17:08.741)

So normalization or standardization of data was one of the big things, suppose. I mean, can palpably tell you like right now everyone follows the C-disk, some kind of normalized data format, right? So we're there and we've been, I think that's a huge win. I think the tools are not, I wouldn't say it was a big win. I continue to see a proliferation of many tools, many passwords, logins. think everyone's kind of talking about that all the time with few solutions to come about there.

PAULA BROWN STAFFORD (17:15.886)

Nope.

Ram Yalamanchili (17:39.013)

So I guess one of things which I want to, like one of my last questions around your early career at Quintiles is, was there a moment where you had like a sudden inflection of growth or has this been sort of like a linear growth story? And if it's nonlinear, I'd be curious on what's the reason why there's an outlier growth in Quintiles versus everybody else, right? Just from you on the ground.

perspective.

PAULA BROWN STAFFORD (18:11.862)

You know, I think that we understood data very early on and the data on the case report form is only part of the data. So we very early on acquired our own central laboratory at Quintiles. I think that did help with the inflection point because so much of your data comes from the central lab. You know, now there are so many different lab and niche labs out there.

And there's so many places that data comes from, but for many, many years, was the data collected at the site, and we call that the case report form. And then there was the lab data. so purchasing a small lab in Atlanta, Georgia, 1995, I think was the year. And I think that was a huge inflection point because we then held all the data.

And as we were growing, we then just started buying other companies because there were so many companies out there. And I kind of see that we're back there again today. There's so many niche providers. And I really do think there's going to have to be another consolidation because there are just so many niche providers. Who are the good ones? Who are the ones who are going to make it, not make it? Everybody's buzzing in the sponsor's ear.

And I think there's going to have to be some consolidation and bringing these tools together and the CROs being in a position to deliver more for the customer. And a lot of that comes through streamlining and partnerships and making it easier. on our customer for the CRO is the sponsor. And when they can contract with one as opposed to 20,

I think that's easier for them and it's easier for everybody. So it's up to us to manage those partners. And I spend a lot of time, I was on the phone with at least two yesterday, I've already spoken to one today. I I spend a lot of time talking about, speaking with our partners and making sure that we have the right relationships, et cetera, to be able to deliver for our customers and make it easier on them.

Ram Yalamanchili (20:33.669)

Right. So I actually have this, this is a fascinating viewpoint because it sounds like quintiles core focus or core competencies in data because you're statisticians to begin with and you're used to large data, analyzing large data. And then you got closer to the data by essentially going to the lab and acquiring a lab. And I like the terminology you use. You said we understood data. So it's basically a skillset you've developed at the corporate strategic level.

then say, okay, if we're able to do that, then the inflection essentially came right after, right? So that's very fascinating. I guess one of the things I'm curious about, I don't want to get into that just yet, is what are those inflection points we're developing right now, or will be developed into the next coming years? You brought up AI, yeah, we'll get into that. But before we go there, I do want to understand sort of like...

What are you building right now? You're at Allucent and it's a different focus, different, I'm sure, strategy, but I'd be curious on how you would describe your mission right now going forward, right, with where you are.

PAULA BROWN STAFFORD (21:52.046)

You know, the big CROs are typically well suited to work with the big sponsor companies. And after I left Quintiles, I took a break and I wrote the book with my friend Lisa. And then I joined a very small, less than 30 people, maybe it was 35 people at the time, anyway, a biotech company.

here in North Carolina. while I was at Quintiles, I recognized that we were built at that point in the 2012 area, around about 2012. I recognized that we delivered well for the big pharma.

And so we went out, long story, I'll make it short and say that we acquired a small company about the size, well, a Allucent smaller, I mean, bigger than it was, but we bought a company at my direction and request and diligence, et cetera, in 2012 and delivered, and it was specific for biotech companies because

That's where lot of the innovation is happening in the industry. And that's where the M&A happens from the big pharma companies buying these biotech companies. So the innovation is happening in biotech. So I joined a biotech. I saw this in real time. And so when that company divested of its assets and I took another little break, I was looking at where can I continue?

to contribute to this industry that I love, that I've been in for my entire career, where can I contribute? And really, Allucent came knocking. And what I want to do here is deliver where the innovation is happening and really build upon a purpose-built CRO and purpose-built then that it was built for biotech.

PAULA BROWN STAFFORD (24:10.286)

Those are who our customers are. And so trying to focus the organization in a few therapeutic areas and the platform of cell and gene therapy and rare disease. So they're more platform because they go across multiple therapeutic areas. And, you know, I just want to continue to build a company that delivers in that niche area. I'm not trying to become a quintiles or an icon or a

you know, PPD, who's now, you know, part of Thermo Fisher, you know, they're the big companies, you know, right now we're focused on really delivering for our niche customers, which are the biotech and, you know, these therapeutic areas, primarily oncology, CNS, and infectious disease. But then again, the platforms that I mentioned, Rare and Cell and Gene. So just focus.

is what it's about and delivering and really those partnerships. How can I partner better and bring solutions to our customers and utilize AI to do that?

Ram Yalamanchili (25:20.687)

Yeah. So that's an interesting segue, right? Because it seems like one of the other things happening right now is we are moving, I guess, to a certain extent away from pure therapeutic focus to platform focus. Because as you've said, cell and gene therapy and rare disease are applicable in potentially any disease. It's not just, I guess, I can't really name one particular TA. So does that mean that you have to structurally think different as an organization? Are there nuances about building

a CRO for these platforms versus say a CRO building for cardiovascular, which is a therapeutic area, which has a certain, I guess, trial design and whatever other qualifications, right?

PAULA BROWN STAFFORD (26:03.404)

Yeah, So The data that you're collecting might be different. Yet it's the same, But the patients that you are looking for, when it's a rare disease, you're looking a little bit more for the needle in the haystack. The standard of care is different in different countries.

but you're probably not going to find all the patients that you need in your lifetime if you look at one country. you know, it's developing protocols that can cross multiple standards of care. They're not tremendously different, but they're nuanced across different countries, and you have to keep that in mind. So that is something that, you know, not everybody gets. And so we've got to be able to do that, and we do that.

You know, when I think about what our customers want, and I guess this isn't really any different than, you know, biotech versus the large pharma, but specializing across that platform is site engagement and patient engagement. We don't have direct interface with the, with this patient, right? But how do we make it easier on the sites?

to have that relationship with their patients and give them tools that will keep them engaged in the study by collecting data from them, by providing data to them. And the more we can do that to keep not only our sites engaged and our patients engaged, because the thing again about data is missing data. Being a statistician, very...

keen and very aware of what missing data can do to a project. It can kill a project. You cannot prove your hypothesis if you don't have the right number of patients at the end of the study. So patient engagement is real. It costs money. It can, and I've experienced it, it can kill a study. And then you have to go out and do another study because you didn't have enough.

PAULA BROWN STAFFORD (28:24.814)

patients to prove your hypothesis. So that patient engagement and the site engagement is critical to the success of a project, a protocol, a study, and a sponsor.

Ram Yalamanchili (28:38.885)

I think it's all these challenges compound, especially in the rare disease and cell genes, because I guess you can't really power your study in a way where it's okay to lose 20 % of your data, right? If you don't have the luxuries as you would in other trial designs.

PAULA BROWN STAFFORD (28:47.468)

Yeah.

PAULA BROWN STAFFORD (28:56.428)

We don't have the luxury. In rare, every patient is so special and you need that patient. You spent weeks, months, and maybe a year finding that last patient and you've got to keep them. For someone seeing gene therapy, no, it's not rare, but there it's the logistics. The logistics are different and that's what's the key around

Ram Yalamanchili (29:10.277)

Mm-hmm.

PAULA BROWN STAFFORD (29:23.374)

a cell and gene. it's learning that it's not just running a different, know, moving from cardiovascular to CNS is easier, you know, for a large molecule or even a small molecule, it's going to be easier than a CNS product that's a cell and gene therapy or rheumatoid arthritis that's cell and gene therapy. can't just go from a traditional, if you will, cardiovascular trial

and then go over and run a cell and gene therapy in something else because the logistics around the trial are just completely different.

Ram Yalamanchili (29:58.853)

That makes sense. from a, I guess, capability and even the structure of Allucent, you're dealing with a very different type of a problem set is kind of what I'm taking away. It's very different from the large CRO world where you're catered for maybe very large trials versus here it's more bespoke, smaller trials, lengthier trials. Every patient counts. There's no real room for maybe a lot of things which could normally happen which

PAULA BROWN STAFFORD (30:12.341)

Right.

Ram Yalamanchili (30:27.525)

You're okay with, but here's probably like a lot more bespoke, right?

PAULA BROWN STAFFORD (30:32.769)

It is.

PAULA BROWN STAFFORD (30:36.472)

can end up being large because if we've run and this has happened where we've moved from running a phase two study of 200 patients, we're moving straight into, because of our success, moving straight into running a phase three study with 800 patients. So we do run large trials, but it starts from proving in the phase two space in the bespoke model that you described.

Ram Yalamanchili (31:02.213)

Got it. Okay. So one of the curiosities I have is, is this all happening right now because there's a, I guess new modalities are coming out right now. We've had mRNA platforms and different types of modalities, are, think, like coming out or have come out in the recent past. But has there also been something around the regulatory pathways, which have sort of improved this type of trial design being more prevalent or

I'm just curious like why now versus 10 years ago, why is there a sudden need to build these kinds of platform specific CROs or services, right?

PAULA BROWN STAFFORD (31:43.502)

So, I mean, obviously the science is changing. you know, and bringing in the expertise, hiring the right people who know about that. But you mentioned the regulatory and, I think that the regulators are really trying, you know, I think you mentioned it maybe in the intro, but in terms of the 21st Century Cures Act, which was in 2014,

You know, I testified before Congress because we were trying to modernize clinical trials and the FDA and the government continue to try to, I think, do what they can to streamline our processes. so the most recent effort is that they came out with this plausible regulatory pathway. And that's just been in the last month. I think that that's been described. It's you know, FDA

FDA guidance that enables a more flexible trial design. You know, they've been working toward these, you know, people call them now used to be called something else. I'm forgetting the old term, but now it's called basket studies where, you know, in oncology, you can run a trial for, you know, many different types of cancer, you know, because, you know, 35, 40 years ago, you know,

there were like seven different kinds of cancer that people were running clinical trials in. And now we've got hundreds of, and that's really the precision. It's more finite, more specific, more precision medicine. anyway, the FDA has also come out and in certain instances they've said upfront, we're not gonna require two pivotal trials.

Ram Yalamanchili (33:13.017)

Yeah, every mutation is a new cancer, a phenotype, right? Yeah.

PAULA BROWN STAFFORD (33:36.898)

for certain indications that might be rare or terminal illnesses that they would be just one. But that's the FDA. But we're seeing some differences in the FDA, MHRA, EMA in terms of some of these trial requirements and whether or not you can allow patients in a trial on placebo.

or if everyone, it is a terminal disease, then they want all the patients to be on treatment, which is understandable. there's a lot of discussion and the FDA is coming out with different things, like I say, with this new plausible regulatory pathway, which is...

you know, accepting of non-randomized trials. And in the past, you had to have two randomized trials. But that's where, you know, for certain indications, you know, there being, and I say upfront because sometimes customers have gone and, you know, asked, you know, can we, here we have one trial, can we use this? And, you know, then you get different regulators who, if you have somebody,

One day who says no, then you go back three months later and you've got a new person to deal with and they say yes. know, trying to keep consistency within the agency comes through the different guidance that they put out and I think that helps everybody. So, yeah.

Ram Yalamanchili (35:08.965)

I see. Does that mean that operationally you would have to, I guess, change or are there things which are top of mind in terms of how you deliver into the new regulatory pathway? does this, what is the impact on the industry, the service industry?

PAULA BROWN STAFFORD (35:25.538)

Yeah, so for us, we thank you for asking that because for us, have a regulatory consulting group. And one of the things that we're able to provide because of our expertise, the number of ex regulators that we have in the company that we can give what I call regulatory intelligence. So trying to guide our customers and advise our customers based on what we're seeing in the agency.

as we submit INDs with one customer and we see the responses, then we can take that knowledge, that learning, if you will, and help other customers understand the pathway that we're seeing at the agency. So we really call it regulatory intelligence and being able to provide that upfront and help guide.

our customers as to what is the drug development pathway? What is your journey look like from a regulatory standpoint? We provide a lot of that expertise and yeah.

Ram Yalamanchili (36:31.151)

Yeah, and then it sounds like it's an evolving space right now, given the guidance is coming out. said in recent months, right? So this is sort of a new area for everyone. Okay.

PAULA BROWN STAFFORD (36:41.592)

Yeah, it's one. it's always, you know, new guidance is always coming out. You know, there's been different guidance even on cell and gene therapy and that continues to evolve. But as the regulators, we bring that into our practice and, you know, the regulatory really is how many studies do you need to do? What is the trial design going to look like? And so it may help guide whether or not we're running one study or two studies and then

and the size of the studies. Is it 100 patients or is it 1,000 patients? So all that comes through with discussion with the FDA.

Ram Yalamanchili (37:17.711)

Got it. So given the backdrop of this and clearly your positioning to be a force to recommend that space, right? With Allucent it sounds like the focus was very clear. It's to provide the right partnership for companies who are dealing with these kinds of type of trials and therapeutic areas and platforms. What does that mean from your perspective in terms of what does the future of the Seattle industry look like at this point, right?

I also ask that because I am trying to understand as someone who have had conversations with around AI and how the implications of that would be in the industry. So sort of like some of the natural forces which are driving change, as well as how the new technologies are going to hopefully help or if they will help or not. I'm curious to take your view on that.

PAULA BROWN STAFFORD (38:11.564)

Yeah. Well, I think, you know, it's moving from just being operational to the intelligence, which I mentioned. So not only just being an operator, but operating intelligently. And then from an operational standpoint, how to be as efficient and effective as possible. And if I go back to that triangle, when I think about the time,

and the cost and the quality, what can help us cut time? And really, if you cut time, you cut costs, but always delivering quality. And I do believe that AI is already and will continue to find ways to help us be more efficient and deliver at a lower cost and shorter time.

So what does that mean? When I combine that with also the intelligence, we have to have higher skilled staff to provide the intelligence, right? But from an operational daily task, when I think about collecting the data, et cetera, I do see the use of AI being a teammate, being a teammate that helps our

high skilled staff deliver more efficiently. So what does that mean for the CRO? We have made our revenue, if you will, on services, on our people. And if we need fewer people, what does the cost basis look like? And I do think that's going to evolve because as you have less people, you have less dollars. But then again, if you have more studies,

then you need more people. So it's a little bit of a shift, but also you look, I'm just thinking about it in terms of the different value drivers. You know, what delivers value for my customers? They want a product approved as quickly as possible. So if I have the tools, the intelligence and the operational tools to deliver for them in a timeframe that cuts

PAULA BROWN STAFFORD (40:36.846)

two years off of what right now people say, it takes 10 years to get a product approved. But if we can cut that down to eight years through the use of intelligence and our tools and our high skilled people, is the value not the same? So I think that we can share in that value proposition.

between the pharma company and the CROs. I think that's where it's headed. Is that going to be in the next two or three years? I'm not sure that the conversations are ready for that yet. but I think it will evolve to that.

Ram Yalamanchili (41:13.049)

Yeah. And it's actually really interesting the way you framed it. It's about your people and it's about delivering value to your customers. Right. And I think the coming wave of tooling, is highly automating some of the processes will have an impact, I think, on the industry and the way we do things in the industry. But I want to touch on the people part because that's, think, like a very key insight. You know, I think there's this notion that

AI is going to be really disruptive to people. And maybe, maybe not, I'm not sure. mean, I, I, but what I do think is really important from organizational and leadership perspective is what you just said, which is can my teams be equipped and able to become AI fluent, I suppose, right? In another word. And is that, is that how you're thinking about it? Like, is that one of the focus from a, from a team, uh, equipping the team perspective?

PAULA BROWN STAFFORD (42:10.05)

Yeah. Yeah. Thank you for leading me there because that's exactly it. I mean, I gave a talk 15 years ago at I think, the SDTM conference. And it was, the whole talk was on moving from calling people data managers to data scientists. And it was even before people are now, you know, talking about data scientists even in a different way. But the idea was, you know, repurposing.

Ram Yalamanchili (42:29.071)

Mm-hmm.

PAULA BROWN STAFFORD (42:40.32)

our people giving them the skill sets to work with the tools that we have. And the tools are going to be different, but the people are the same, but training them and helping them learn, you may need, you know, ultimately fewer people if you have the same number of studies. But if we can increase the studies because we have the number of people and it doesn't cost a pharma company as much, it doesn't cost them $2 billion to bring a drug to market, then

you know, they can do more with the two billion that they have. They can bring two products to market if we can be more efficient, right? So it is, I don't want to know if it's repurposing, but it is evolving our people into using the tools that are out there like AI to operate differently than we have for the, you know, last 40 years. But,

In my 40 years, we have continued to evolve, as I've mentioned, and I won't be here for the next 40, but I'm going to be here for at least the next four, and I will continue to see us evolve as an industry. It'll just keep evolving with the tools that people like you, are developing. It's going to continue to evolve, and hopefully, we can start to decrease and

instead of increase the amount that it takes to get a drug approved.

Ram Yalamanchili (44:10.005)

I couldn't agree more. I have personally started to really take issue with this view that AI is actually going to kill a lot of these traditional concerns on number of jobs. I don't think the reality is we're not seeing that. Even today in the market, we don't see that. Take the example of my domain, which is building technology companies, number of software engineers. Yes, we have some of the best products to generate code today.

cursor and there's so many tools which will enable you to write more code than ever before. When I started my own career to now my productivity could be a thousand X. And the number of companies which are being started today, like in the Bay area where I am, in the startup space, is probably an all time high record. There's so much room for entrepreneurship. There's so much room for having three people in a proverbial garage.

you know, start something new and kind of like disrupt the entire industry today because you have that power to do that at a, at a, what used to be a highly unattainable goal. You you would need enormous amounts of resources to take on any idea you have and actually deliver it into a product. Right. And I think coming from that perspective and looking at how biotech operates, pharma operates, these numbers are astronomical, 2 billion, 5 billion. this is, you know, this is not something an entrepreneur could ever aspire to.

do, or at least not enough of us can aspire to do that. I really hope that that changes. I think the idea is that we should enable those bench scientists who have great ideas to kind of pull out their hypothesis, and it should not take a billion dollars to get there. I think that's a huge disservice to the entire humanity in itself is how I look at it. And I think they've done it in computer science and traditional tech.

based on everything you're saying, I really do hope that happens in biotech as well. I mean, you know, we need more elucidants and more thought leadership like you are presenting here, I think to make that happen perhaps, that'd be a good day for all of us to make that happen.

PAULA BROWN STAFFORD (46:18.542)

Well, thank you for that. You know, think people are a little afraid, some people, I don't say all people, but some people are afraid and think that AI is dangerous. And I think there are aspects of AI that can be dangerous, but I don't see that anything that we, you, me, we're trying to do in this industry is anything that is dangerous. I think what we're trying to do is help us to be more efficient and to bring more drugs to market without costing so much.

such that you can't get a new product to market in an area where we desperately need one. But I've seen too many companies lose funding in the last two years who have really viable products that patients are out there waiting for and wanting. But I don't see anything dangerous about us trying to do more with less, or trying to deliver more products with the same amount of money.

And the only way we're going to do that is if we use AI tools. So we have to embrace them and not be afraid of the danger in what we're trying to do in this industry. I think maybe there's some other areas and industries that people could be more afraid of, but I don't think there's anything to be afraid of that we're trying to do with AI. I just wanted to say that.

Ram Yalamanchili (47:35.439)

Yeah, no, I really appreciate that viewpoint. It's excellent. I couldn't agree more with you. So my final question will be in some of your writings and your book as well, you talk about fulfillment and balance. And I am curious what your advice would be to people coming up in their careers right now, entrepreneurs, early stage employees and...

know, people are building a career in this particular field, right? What would you tell them in terms of how to find that? Because the pressures are there. mean, you know, every day is a grind, I feel, at least to me. That's the vantage point I take. But be curious on what your advice would be.

PAULA BROWN STAFFORD (48:19.66)

Well, you know, I think when you work hard, it comes back to pay, know, to pay your pave your way. It takes hard work to advance and to grow. I was so fortunate in my career to start where I was and, you know, but I didn't get to where I am.

No offense to people, I didn't get to where I am working 40-hour weeks. But when I think about the balance is that I also have two grown children who I think have done quite well in life. And I'm very proud of the fact that I was able to do both, be a mother and be an executive, because there were times when I had to put the phone away. And when we had BlackBerrys and some

who watch this will remember the Blackberry and it would light up red when you got a new message. And my kids would say, mommy, you have a new message. And I would say, well, I'll deal with that after you go to bed. So you have to balance life. But if you're going to excel, comes from working hard. It comes from taking risk. You've taken a lot of risk on a lot of different companies that you've been in. I took risks joining a company.

with 23 employees and look how that turned out. And we built a culture. We built a culture that people wanted to succeed and they wanted to build something that they could be proud of. And yeah, I wanted children that I was proud of, but I also wanted my professional career to be something that I was proud of. It was just, for me, guess I'm type A and I'm an overachiever and

Some of it comes from just wanting to excel. Anyway, so you got to work hard. You got to work hard. That's easy for me to say.

Ram Yalamanchili (50:26.593)

Absolutely. It's such an excellent perspective. you say the pride and work matters more than the earn out or do both matter?

PAULA BROWN STAFFORD (50:43.176)

for me, it's the pride in the work and the other just hopefully comes. I mean, that's how I've always felt. the earn out comes, you know, I can be happy about that, but I honestly just love the work that I do. mean, you know, part of, you know, my grandmother, I worked on Metformin and was the project manager and helped get that product approved. And, you know, she was on that product for

Ram Yalamanchili (50:46.085)

Yeah.

PAULA BROWN STAFFORD (51:08.174)

almost 20 years from the time she was 80 to when she passed away at 99, she was still on that drug that I worked on. I love the innovation that we bring in this industry. so for me, it's just feeling like I have done something for others is what makes me happy.

Ram Yalamanchili (51:30.469)

Yeah, no, that's totally. I think it's so much easier to do that in our industry than most other industries. Like you could justify why you're working hard, the progress you're making, helping others make the progress. And it all kind of pays back in many forms, right? And one of that is just what you just said with our family's story on this drug. yeah, with that, Paul, I thank you for your time. It has been excellent. I've learned a lot.

And I appreciate you sharing your perspective on where we're going with the industry and how you're thinking about the future as well.

Thank you.

PAULA BROWN STAFFORD (52:06.798)

All right, well, thanks, Ram. Really great questions. Enjoyed the conversation.

Ram Yalamanchili (52:09.295)

Yeah, thank you so much.