What If AI Could SPEED UP Clinical Trials by 90%?

Clinical trials are fundamental to developing new medications, but they face significant challenges, including lengthy timelines, high costs, and complex data management.

I'm Michael Cricggsman, and today on CXO Talk, episode 877, we're discussing the impact of AI on this critical part of our health care system.

Our guest is my old friend Jay Pharaoh, executive vice president and chief information technology and product officer at Clario, a leading provider of clinical trial technology solutions.

I oversee IT product data security uh marketing and corporate communications.

Uh all the things that you normal normally would find in the traditional CIO role.

all the things that you normally would find in the the CTO role, enterprise architecture, etc. And then product and marketing. We also get to build the solutions that empower clinical trials all around the world.

Uh and I get to have a hand although I leave it to the experts in the marketing of that uh of those products all around the world for our customers and ultimately the patients that we support.

Chay, it's in a very unusual role.

Again, chief information technology and product officer.

How does a role like that actually come together?

I' I've have not heard of anybody with that exact title before. To me, it comes down to trust and delivery and transparency.

I work for a terrific CEO. My team and I deliver uh we're transparent. We own issues.

Uh we're business focused first, technology focused second.

In no way am I minimizing the important of staying ahead of technology trends and leveraging emerging and transformational technology.

That is not the point.

But the point of an organization especially with what we do is serving our customers and it's not just about the technology.

It's about empowering clinical trials.

So walking a day in the life of of what a patient goes through, of what a a clinical trial investigator goes through, a trial site, what our sponsors deal with when they're the ones, you know, funding a trial in truly understanding the business of what we do, I think has built trust with my CEO that I can I could have handled uh a broader role.

We have talked for years about understanding the language of the business but yet I still see so many CIO CTOs struggling with how to do that with they lead with technology and then kind of maybe put a business wrapper on it and it really starts with an understanding of the value chain acquiring customers delivering your solution whatever that may be or your product servicing the customers at the end making sure that they are having an amazing experience you're staying ahead in the innovation cycle so you're constantly delivering and all of that stuff is powered by technology, but it's not technology that's the endgame, right?

It it's removing friction.

It's delivering value.

It's delivering services on time. It's making sure things are up, of course.

Uh it's delivering highquality data when you say you're going to do it. Uh it's the new endpoints that are being brought into a clinical trial.

And when you can do that consistently and show that you have a good understanding of whatever domain you're in and you're having open and transparent conversations with your CEO about your aspirations. Part of this came from me just raising my hand and saying I'd like to when you do have other opportunities I'd like to be considered and and so um you know part of that has come through delivery part of it has just come through transparency and good relationships.

So what is the benefit or the value of combining these multiple functions under this particular umbrella?

Well, my CEO only has one throat to choke. He knows where to go.

Uh if something's not on time or it's delivered with with excessive bugs or defects.

Um, but all kidding aside, we own the solutions, the technology portions of the solutions all the way from inception from a product management point of view uh all the way to marketing.

Now, we have other groups that are responsible for delivering uh our services, our solutions, our science, um all of those things and they're amazing at what they do.

That doesn't follow under my remitt.

The other advantage it gives Michael is we're in a lot of different areas right we do we deal a lot with cardiac safety with respiratory with medical imaging what's called ECOA or electronic clinical outcome assessment all of those things are different but there are common threads so being able to unify those technology solutions or those products and those solutions into one tech stack and provide a more seamless experience for our customers customers and our customers are of course the sponsors who are underwrite the the clinical trial that could be large pharma perhaps a CRO or a biotech the clinical trial sites all around the world who are actively running the the trials on behalf of the sponsors and of course most most importantly are the patients the the people enrolled in a clinical trial wherever they may be around the world right and and we want to make sure they have uh the most frictionless seamless experience they have.

They're all overworked. They may be going through tough times if they're going through a clinical trial.

We want to keep them front and center. And because this role is now unified and we have one throat to choke and we have a unified product management organization, we were able to see and leverage technology and products all across our ecosystem versus having siloed products or siloed technology.

Um, and we now talk about Clario in terms of an overall ecosystem in platform versus a bunch of point solutions and our customers want that.

They they want a Clario to deal deal with not a Clario, XYZ solution add infin item.

So the ultimate point then, correct me if I'm wrong, is by unifying these teams uh across what are typically silos, you're enabling a hopefully seamless experience for your customers.

I think that's one of the largest benefits, Michael.

I think one of the other benefits is internally, if you want to put kind of a a tech spin on it, is um I'm able to, and I say I'm as a proxy for my team, is able to see across our entire tech landscape, look for commonalities, look for differences.

You don't want to build six of the same thing because you have product silos all over the organization that are kind of doing their own thing. So unifying that vision and being able to see where you can build once and deploy many is huge.

There are the economic benefits of that.

I build it once and I get to use it all over the organization. That's wonderful.

Keeps my capex lower than it, you know, otherwise would be. Keeps my spend.

Supportability gets better. All of those things that we care about. But at the end of the day, the downstream impact is going to be felt by the customers, the sites, and the sponsors.

They're not getting a different experience every time they interact with a different product line or anything.

They're used to seeing things a certain way.

They're used to dealing with Clario a certain way.

And that is really what we're striving for.

If you've ever walked into a clinical trial site, and I'll describe it for you, right? And and these investigators are working their tails off.

They're terrific, hardworking, brilliant folks.

You see stacks of devices, laptops, you know, respiratory devices, cardiac devices, and stickies on each one of them to to kind of talk about, you know, which company it's from, which study it's in.

All very, very important to keep everything organized. But I can't control what my competitors do.

I can't control what other parts of the clinical trial ecosystem do. I can control what Clario does.

And what I really want more than anything is when an investigator or a patient deals with Clario, whether it's a BYOD app during the life of a trial, a connected device during the trial, a portal that a sponsor is going into, is they have a frictionless, seamless experience.

And if that sounds familiar, it should because really every industry wants that, right?

And and every industry, I think, thinks it's unique and that, well, we can't possibly think about it in consumer terms. And I would argue that you absolutely have to think about it in consumer terms. If every time I went to Bank of America and I had 17 different apps, well, this isn't the transfer app. You got to use that.

This isn't the loan app.

That's a different app. This isn't the check your balance app.

You got to fire up something different.

You'd be like, man, out.

I'm out of here.

and and and so we really want that unified experience while retaining speed and quality uh integrity of the data.

very very interesting as you're describing the comparison of this clinical medical system, but from a user experience standpoint, we're all just people and and we want that we want that um non-siloed seamless experience as you were describing with a bank.

You nailed it. Um and and that's that's it.

And and I think the the secret is you always have we are in a highly regulated industry.

So in no way am I saying that you freewheel it just to make it ease of use and that's your only bar.

There are regulatory hurdles.

There are scientific there's scientific validity that you have to meet and so we are always focused on the science.

Uh my chief medical officer Dr. Todd Rudo and I have a great relationship and the the hundreds of scientists that we have in our organization uh are amazing partners, but within the context of keeping everything valid and reg, you know, uh meeting our regulatory burden as much as I can, I want to make that a consumer-like experience uh and and as friction-f free as I can. And I just want to tell people that you should ask questions.

If you're on Twitter, use the hashtag CXOT talk. If you're watching on LinkedIn, just pop your questions into the chat.

And truly, it's a unique opportunity to ask Jay Pharaoh pretty much whatever you want. So, so I hope you folks take advantage of it.

So we have let's see our first question comes in from Chris Peterson and he says this is a touchy subject in Clario's niche.

Are you seeing or expecting customers hedging because of research funding cuts?

We're certainly keeping an eye on that and you can't help but read everything uh that's going on in the news and wondering what the knock-on effect is.

And thank you, Chris.

Uh my good friend Chris, uh who has been a regular viewer of yours. I know that.

And and I I am going to say that the last time I was on here, which was years ago, he asked a question. So I am honored that he showed up again, so I didn't scare him off, which is great.

But um yeah, we obviously have to keep an eye on that. It's an uncertain environment.

I don't think you can pop open a news app and not see something about volatility, um funding cuts. Um I I personally Jay Pharaoh's opinion want to keep him you know the United States on the forefront of uh of of medical research but there's so much good research going on all around the world. Um you just don't want to see any letup in in clinical research going because people are depending on it.

there are life-saving, potentially lifealtering cures or treatments uh in in the pipeline uh that we want to prove that are safe if we can and then uh get them out into the to the people.

So, we're keeping an eye on it.

Um clearly, Chris, we we we don't want to see that type of impact.

Um the clinical trial space, there's a long tail in it. generally these things are not done overnight.

Um and and hopefully I think we can withstand kind of the the chaos that's happening right now and we get a little bit more clarity and predictability in the coming weeks and months so that we can get back to business. Uh but right now we're we're keeping on keeping on.

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And we have another question this time from Arcelon Khan who is also a very long time. He is another regular.

He's another regular. And we're grateful for Chris and for Arcelon and the other folks who listen and who just ask such excellent questions.

And Arcelon says this, "How important is it to say yes, but also say no to all of your teams?

You're juggling multiple teams. And how do you decide when to say yes and when to say no and when to prioritize one versus the other?" It is something that every CXO or head of IT or anybody that is responsible for uh software de anybody in our space has to deal with there is always more supply or more demand than supply always.

I don't care what company. I have been a CXO now since 2008 and I cannot remember one time where I ever said, "Nah, I'm good.

I got plenty." And so ruthless prioritization is absolutely key.

And you don't want to do that on an island.

For me, what does that mean?

It means partnership with my GMs who run our business units daytoday.

It means partnership with my CEO.

naturally means partnership with my CFO and he and I are absolutely joined at the hip with what we want to see. We want to see near-term value.

Certainly, there are strategic investments.

We're completely aligned on payback and in the making the decisions that have the most benefit for the company but also our customers.

Now, there are certain things that you just have to kind of pay the dues every year.

cyber. You never want to take your foot off the gas with cyber. I am in an industry of trust.

All of us, I think to some degree, are in an industry of trust.

When that trust is broken, it takes a while to rebuild from that. So cyber is always kind of pinned to the top of our priority list.

Regulatory requirements, I think those always get, you know, pinned to the top. And then there are customer requests which come in and and have to be juggled with those things.

But Arcelon, the bottom line is it comes down to ruthless prioritization.

And I try not to say no.

It's more of a not yet or no, here's what I can do. Can we agree on this in 2025 and in 26 we'll do a phase two.

I really do my best to try to deliver some value even if it's a no. I prefer it to be like a no, no, but we have this.

This gets you 40% of the way there.

Can we start there and then put a plan together to to pick up the rest of it in 20 in in 26?

So, it's not just a uh knee-jerk reaction philosophical well this is something we don't do and so therefore the answer is no. It's there's there's a reason there's there's a there's a you know I will say this if it's a customer request that comes in and it's just something that's not in our wheelhouse or you know something that's not a core competency or yeah there are going to be times where you say look it's just you you have to be mature and self- select out of it or if it's a capability that just is doesn't make sense for us to build we are always going to try to find a way to partner or build or or serve our customers if it's internal [Music] Um, nobody wants the house of no.

I mean, Michael, you've been at this for a minute.

You and I probably sat here 15 years ago and talked about the house of no and the CIO being the CIO and all of this other kind of thing.

Nobody wants that. And I try never to say that, but it's it's always, you know, when I do have to decline or just say, you know, we just cannot get to that this year or this cycle.

uh it's it's usually followed by a comma, but here's what we can do and let's figure out a way together GM or CXO how we can tell this story so maybe we can get some additional funding to do this.

So um I I you know there's there's some to me it's about relationships and building and being transparent about how decisions are being made in the company and and why we're choosing to do what we're doing.

Okay, let's go to some additional questions.

Joseph uh Pugilisi on Twitter.

Ah, Joe up in Philly.

Philly Joe. Okay, so you so friends.

I know Joe. Great. And Joe says, "Will AI or other innovations lower the cost of health care?

This is so needed in today's economic environment." I think it has the potential to to perhaps do that.

Uh certainly uh we don't look at it that way. Um we we look at it from a quality uh efficiency and privacy point of view.

So I I think you're foolish not to look at AI and say there's not going to be some sort of you know cost arbitrage.

Uh we hear we read about it every single day.

Uh, I think Bill Gates said something the other day, Michael, that he thought it would replace physicians or replace many doctors or healthcare roles.

You know, I don't know how comfortable we are with that just yet. I I think we're at the beginning of our AI AI journey.

To me, we still want humans in the loop.

Given given the regulatory hurdles and the importance of trust in the drug development process, humans are still very very much in the loop. And where AI plays a huge role is tackling things that maybe machines are better at.

Looking at large volumes of data, finding anomalies, assisting with document uh you know uh interpretation or image interpretation, excuse me. Um being able to make predictions, those types of things.

But we're still at a point where I want a physician or I want an expert overseeing that work. But yeah, I mean the short answer to Joe's question is I I mean if there there's got to be a cosplay down the road. I mean AI isn't free and and but to me it's less about removing people.

That's not the point to me.

It's about getting our scientists and our amazing people at Clario to focus on a higher level of challenge and augment them with the technology on LinkedIn.

Greg Walters says, "When implementing AI in trials, is each application of AI unique to that specific trial or part of a standard AI process?

" And he also asks, "Is the AI homegrown or partner?" The answer is yes.

The AIs are models that are it well it depends. they are limited in functionality to a certain a certain function and that model can then be used across trials.

They are trained more often than not they're closed model so they are not continually learning uh so they are closed as of a certain point.

So whether that's a data privacy model that anonymizes medical images, it's a QC or quality control assist uh uh model that um looks at early identification of quality concerns to help us ensure timelines.

Maybe a read assist where you're having a a um a radiologist look at images, an MRI, a CT scan, those types of things. And you're identifying it's it's identifying different things for you.

uh and it can reduce inter and intraobserver um variability.

Those models are built and are fit for purpose for that function, but they're utilized across uh across studies.

So uh and there's many more.

We at this point we have 50 models, 50 plus models that are proprietary homegrown um across ECOA, cardiac imaging, respiratory and precision motion.

Um we do have a proprietary Gen AI platform that we have built internally on enterprise class you can think open AI you know Gemini etc um that are private uh we named her Claire we're not super creative Michael so Clario declare I know that's a you can see the leap we took there uh and uh well hey you're in a conservative business right the health healthcare.

And if you saw the AI image, and I'll share it with you sometime.

If you saw the AI image that AI created, we said, "What would Claire look like?

" It it is absolutely terrifying. Uh it it it is terrifying.

But what I love about it is a year ago within the organization, if you had asked, I don't know, a thousand people, what is CLA?

They they wouldn't have known.

Maybe a year and a half ago.

Today you're now hearing people say, "Well, we're going to put that in CLA or we're claring it." And and it's become part of our lexicon because we've built capabilities to do a protocol summary, uh user story writer, RFP and contract analysis translations um you know, document chat where you have a large volume of documents and you're trying to ascertain what exactly is and so many more.

and the line of people behind our AI team with just use cases that uh for for CLA and what we're doing is huge.

Um but going back to the question, uh we try to leverage third party wherever we can as long as it's safe, it's private.

Um but a lot of our other proprietary models are built on our homegrown Aquarius engine.

When it comes to Gen AI and summaries, how do you ensure that there are no hallucinations?

For example, summarizing a patient record, the uh AI could potentially think to itself, think whatever that whatever that actually means to the AI.

that the AI says given all of these symptoms the patient must also have X Y or Z condition and then inserts it.

How do you how do you deal with that?

Constant oversight, human oversight. Um first of all, we don't deal with anything that can be attributed back to a you know a Michael Cricggsman or a Jay Pharaoh or anything like that. We deal with synonymized uh and anonymized data.

So, first and foremost, you know, we're not dealing with Joe Smith or or, you know, Jason James or anything like that.

We're dealing with uh synonymized and derived data.

Uh which is which is super important.

Uh number two, uh constant refinement of the model. Uh we have an internal AI team under my chief AI officer who reports to me that I hired and brought onto the organization last year, Marco Topalovich.

uh we are ruthlessly challenging our models to look for bias and hallucinations.

One of the ways that I think I'm really proud of is right out of the gate when when I joined the organization and I realized that AI was a big part of our story and we got a little bit of a running start when I I think when I joined we had maybe one model in production uh that was scientifically validated and today we're at 50 and and growing which is super exciting.

But one of the ways you do that is transparency within the organization.

You want organizational literacy on what AI is, what it isn't, what we're doing, why we're doing it, more importantly, what we're not doing.

And so we created a group right out of the gate including my general counsel Lauren Mishtal, my chief medical officer Todd Rudo, my CISO Mortisan Nisar, my of course my chief AI officer Marco that I talked about uh my head of quality uh Todd and and and all unified with our passion for the technology but all coming at it from a different point of view and making sure that everything we're doing is built on trust, transparency responsibility um, bias control, etc. And I urge anybody out there that is just at the beginning of their AI pro program, do not approach it as a CIO only or a CTO only.

Don't do it. Okay? Don't throw all your stuff in an LLM and be like, we're on a AI, man. We're great.

You know, when cloud came out, you just started throwing stuff in the cloud and you wondered why, you know, proprietary information was suddenly gone.

You don't want to do that. Do it in a controlled way.

And people immediately hear that, Michael.

And what do they say?

Oh my god. I involve attorneys and woo, that's just going to slow down in a absolutely not.

If anything, it has sped it up because there's no daylight between us and because our customers know that we're approaching it for from a responsible point of view. And the last thing I'm going to do is put a model into production that my general counsel, my head of privacy, my head of quality, my chief medical officer, my CISO, my CEO for that matter, of course, that that we all haven't seen and are are signed off on that we did it the right way and that we did it responsibly.

So I, you know, if you're tackling this as an IT problem, I I just I encourage listeners to, you know, broad open the aperture a little bit.

We have another interesting question again from Arcelon Khan on Twitter. How do you use AI on clinical trials?

And of course, what's the impact? But he's also wondering would removing AI guard rails and regulations make clinical trial trials better or faster?

You remove regulation um would they make them faster?

Maybe. Would they make them better?

No. Uh, I I I would argue that the FDA, and I have had numerous conversations as recently as this week with our colleagues over at the FDA, they are very bullish on the technology, uh, they're doing it the right way.

I think they're moving at a speed.

I think people hear FDA and what do they think?

Red tape, right? You know, grind to a halt.

See you in three years.

And, and that is just not true. Uh, I I might have said that coming into the organization 5 years ago. It would it would have been an ignorant judgment.

And uh I have learned that our our colleagues in the FDA absolutely want to do what is best for people.

They want to protect people, but they want these these drugs and these therapies to be trusted, safe, effective, and they want them to improve lives. That's what they want.

and and in so much as AI can impact that they they want to lean into AI.

Now the first part of this question which I think is really really good is where can AI where does AI fit into the clinical trial?

Now I I'll give some examples where I where I'm seeing really good effectiveness in the trial process.

we don't play in all of these roles and I've talked a little bit about how we use it but um patient recruitment and retention um finding and enrolling the right patients in a trial is not easy.

There's not a line of people hand you know standing right hey you know it it can be timeconsuming expensive difficult patient retention you're taking a a treatment or a pill or an injection or whatever over time that may or may not have side effects that you may not have just real world things that impact you uh your ability to participate in that trial um and retaining patients is key and it's an important challenge and So um minimizing dropouts uh is absolutely key. What can AI do about that?

Well, first of all, it can it can manage or analyze large data sets, potentially electronic health records, genetics, social determinants.

Uh it can identify potential candidates who are likely to meet trial uh criteria uh faster, more effectively.

um using predictive capabilities, it can predict uh dropout risks so that those can be mitigated ahead of time where you can say, "Hey, look, there's a a chance that Michael may or may not make the cut because of we're seeing those behaviors and that way I can intervene potentially and keep Michael in the trial." That's a huge application in ripe for AI disruption.

Uh I think trial design and optimization where we do play a role.

Um trials are complex intentionally so because they're important and there's a lot of science behind them and you want scientific rigor.

You want meaningful results but a protocol can be very very complex.

You're balancing patient safety statistics cost effectiveness, I so many other things.

uh an AI can simulate different trial designs and predict outcomes with various configurations.

Now, you wouldn't want to rely on that alone, but it can at least directionally move you uh in a in a path to optimize a protocol and looking for the most effective study designs, not just cost effective, overall effectiveness, which ultimately would have the benefit of speeding up the development process, which is is exciting.

And those are just a couple of top-of-mind examples where I I see AI making a uh you know, a hu a huge difference.

We have another related question that's come in from LinkedIn from Lori uh Noruggov.

Before we get to Lori's question, I just want to remind everybody that we have shows like this every week.

Subscribe to the CXO Talk newsletter.

Just go to cxot talk.com so you can sign up. We want you as part of our community so that you can participate and it's fun and it's great. So sign up for our newsletter. And here is Lor's question.

He says, "Does regulatory compliance create limitations for some of the more advanced AI use cases?

If yes, what would those be and how do they work with regulators for making innovation more accessible?

The regulatory environment being what it is and keep in mind this is not the FDA only.

You have the EMA and you have other regulatory bodies all around the world all with their own criteria.

The FDA is very thoughtful and very measured uh in what they do as are many other regulatory bodies filled with smart people who want to do the best for the most.

Um this is to me about partnership with the regulatory bodies.

uh and I don't mean like co-development or anything like that but understanding what the regulations are understanding the hurdles and the barriers that we can over that we can overcome showing them I I'll be honest and the question is such a good one and I think and I don't want to come off as an FDA homer or anything like that but as I've gotten to know them I I will say they want to do the right thing uh and I don't see them at all as a quote obstacle or anything.

I think a bigger obstacle is organizational readiness.

If you said Jay, is it the FDA or regulatory body?

And to be sure, we are in a really highly regulated and for good reason.

We're in a highly regulated industry and we have to be, right? Patient safety is absolutely paramount and trust is absolutely paramount and the science behind everything we do is absolutely important.

The reason I say that it's organizational readiness is because you're dealing with very complex.

You're dealing with an industry that does not pivot overnight.

We've seen it with healthcare over time. We saw it with fintech in the '9s and the 2000s, etc. If you had gone back in time and asked somebody in the '90s, hey, how safe are is it to to use a cell phone for millions of dollars of financial transactions?

They would have looked at you like you sprouted and tell, "Oh, that'll never happen. You got to have people.

You got to have whatever.

" And here we are today moving money all around the world at a moment's notice.

It's going to change, but you're still seeing organizational resistance.

I I think in some ways for good reason because there's a a bar of rigor that you want to hit. Part of it is just culture change and making sure that people understand the power of AI in this truly unique fundamental force that we have.

Uh so a lot of it comes from education as well uh in overcoming some of the organizational inertia in older thinking.

I I mean look I'm I'm not I don't want to be too hard on people Michael but I mean if you had walked into a and and and were hanging out with a 25-y year veteran in the fintech space in 1994 and said I'm going to paint a picture of what the future's going to look like.

They would have been like, "No, let me tell you the 52 reasons why that's not going to work." Lori clarifies his question to say, "How do you work with regulators to make innovation more accessible?

" I was at a conference not too long ago, and Lori, you you'll appreciate this.

Um, and it was an FDA panel and and one of the FDA guys that uh and I won't say his name because I I I just it's not important, but he came off and I I greeted him because I just was blown away by the the discussion and it was all about AI and what they thought of it and it just was in went in a totally different direction and I said, "How?" And I almost asked Lor's question verbatim and I was like, "How do we partner with you?" Uh, you can email me. And I was like, "Oh, oh, well that's uh I mean that's interesting." Uh, you know, we we want to hear, we we want to learn.

Um, but to put a finer point on, I would say proactive collaboration.

Engage early. How do you do that?

Well, talk to them. Okay? This isn't an ivory tower that I I will say every FDA person or every regulatory person that I've ever talked to has been willing to have a conversation.

So establishing clear communication and being proactive uh with the regulatory authority whether it's the FDA, you know, EMA, etc. Number two, understand regulatory frameworks.

Show that you're compliant with existing guidelines.

making sure that you're familiar and you understand what they're trying to accomplish and that you're not coming at it from a purely tech point of view and be like, "Yeah, but if we could just release the guard rails and let this, you know, thing go nuts, imagine all the good.

" I probably, yeah, maybe some truth to that, but I think the reality is that the regulatory frameworks exist for a reason.

They change over time.

Guidance has changed over time. If you had said 20 years ago, we're going to have an AI reasonable use policy, I think most companies would have been like, what?

Why the hell do I need an AI reasonable use policy?

Right? So, making sure you're familiar with existing guidelines and and that you're adapting your AI to fit that compliance.

I think that starts you off in a in a very good conversation with uh with regulators, making sure that you emphasize safety and risk management with regulators.

The FDA often requires riskmanagement strategies.

They don't want to hear about the art of the possible without the other side of the coin. What are you doing to manage risk to ensure that the AI technologies that you're proposing are safe and that any potential risk to perhaps the patient, the study, etc. uh are are are mitigated.

And the last thing I'll say, the last one is develop a regulatory friendly development practice, which I kind of harped on at the beginning.

Um, following best practices, having SOPs in place that can pass regulatory scrutiny, uh, transparent and training models, uh, bias mitigation, um, all of those types of things build trust with regulators. And on this topic of transparency, Arcelon Khan from Twitter comes back and he says, "If we want transparency across industry, should companies share their next AI with others so collectively whole industries can get better and what about the role of gatekeepers in all of this?

" I do think there's an opportunity across industries to promote transparency and drive positive outcomes across the industry.

Uh whether it's healthcare, life sciences, fintech, etc. I think I I think there are some benefits of doing that.

Um certainly speed, collaboration for innovation and you're going to get more faster generally.

uh public confidence I think when they see collaboration and trust and transparency across industry.

Um there's certainly uh an opportunity for better regulation and you're seeing that already with Europe, right?

Their AI their AI regulations are not just for life sciences or healthcare. It's AI in general.

matter of time before the United States does it either at the state level or the or the federal government level.

Certainly you have some draft guidance uh already uh out there but um I think it speeds that up uh and I think you get a higher quality of regulation when there's more collaboration and sharing. So there are a lot of reasons uh to to do it.

I'll just mention for folks that are interested in Europe, European adoption of AI and regulatory efforts. Just a few weeks ago, we had two members of the House of Lords discussing these exact issues here on CXO Talk. These are folks who are creating policy in the UK.

So if you're interested in this topic in Europe and the UK specifically, just go back and look at CXO Talk. We have it there's a really great discussion.

Well, I'm sure I mean look, they are always at the forefront uh of regulation. Um and I don't mean that in a snarky way, but I mean I I think they've done a nice job in balancing innovation with risk mitigation transparency and accountability.

Um it's not perfect.

Nothing ever is. Um, but the E the EU AI act uh I mean they came out of the I mean what is that in 21 I think they launched that and and which is crazy. It it it was very very well thought out and what I like about it is it triages risk unacceptable high limited minimal uh etc. Right?

So, this this risk approach where hey, if it's a system that poses little to no risk, uh it's an AI in a video game, it's an AI in a spam filter, have at it. You know, you're going to have to check a few boxes, you're going to have to do a few things, but yeah, we we don't want to slow stuff like that down, right? And and it seems to me they at least tried to rightsize uh the regulation, which is which is good.

So we have another question from Greg Walters who is aware that you have a background in cement. You can tell us about that.

Greg outing me like that Greg.

All right. And Greg Walters wants to you to compare AI to quote cementitious materials given the fact that concrete has been around for thousands of years.

Every industry is more alike than not.

I I know we like to not think that, right?

I I I think every industry thinks it's a a perfect little snowflake, Michael, that uh you know that that is uh it's a unicorn, every little thing. And to be sure, every industry has nuance and has its own lingo. It's got its own ecosystem and it's got its own special uh spin on a regulation or whatever.

But I can tell you the discipline of product management, technology management, financial management, software development, security, etc. is 80% the same across industries.

So if you look at manufacturing, my time as the CIO of Quick Creek companies and even before that, you know, at AIG uh or the American Cancer Society or Earthlink, you were doing many of the same things.

Now the size, the scale, the severity may be different, but when are you not protecting customer data?

When are you not trying to deliver highquality results on time?

When are you not trying to leverage emerging technologies to deliver a higher quality product uh or have an amazing customer experience uh or improve operations or drive revenue?

And I would challenge CIOS and CTO's and aspiring CXOs to think about things that way and not box yourself into one particular industry.

Uh but how is cement like AI? I know there's a punchline Greg somewhere out there and I don't know what it is. Maybe uh maybe somebody will suggest it. But uh Joe P on Twitter comes back and he says, "How do you keep your team focused on the outcomes and avoid becoming enamored with the technology? In other words, avoiding shiny new object syndrome.

Education, transparency, um building financial literacy, education, educating the team on why we exist as a company.

And what what does that really mean?

That those are all a lot of really flowery words.

site visits, discussing with patients, showing them what we do, visits from, you know, different departments, building those relationships so that people, no matter where they are in the organization, in my team, I don't care if you're a health test level one.

I don't care if you're a coder and you're a junior person that just joined the team.

I want them feeling the importance of what we do. I want them recognizing that there's a patient at the other end that is using an app on either on a provision device or a phone or is using a connected device whether that's a a blood pressure device or a respiratory device in clinic that we built or that we built an interface for or that we have AI integrated with.

I want them understanding that what they're doing has real human impact around the world.

And when you do that, yeah, you're still going to get excited about the technology.

It's what we do but it's technology with purpose.

It's not technology for technology.

So we try to do a lot of education Michael uh and JP but and uh keep people focused.

So what does that mean in practical terms?

Site visits, site education, voice of the customer type activities, making sure we're hearing from patients, making sure we're showing teams the impact of the technology that they're building and that they're delivering.

uh whether that means you know hearing directly from customers etc so that they understand the impact it wasn't just a bunch of code on time which is nice I want that but there's purpose behind it on this topic arcelon comes back again and he's wondering about the future of AI uh let's keep it focused on clinical trials and he says as AI becomes increasingly more of a commodity if deepse has showed us anything, it's that I I think the idea of a of a trillion dollar one-sizefits-all, one magical product to rule them all is not going to be long for the world. I I I think there will be some commoditization of of of technology uh over time. And I think what you'll see is far less one giant model and far more fit for purpose.

Um what what the future I see I see some amazing things happening in the future particularly in healthcare in clinical trials keeping it speed improvement in quality um uh patient uh experience uh what what does that mean? It means if a patient is having a bad day or there's, you know, there there's just you're you're there's just some empathy that even models today can show um more time with an investigator or a physician if it's healthcare. Physicians will tell you constantly and nurses will tell you constantly.

I'm sure you everybody knows this.

They spend more time entering things into an EMR than they do with a patient.

EMRs are designed for one thing.

What do they or two things to bill and to keep street legal.

And I'm not trying to be depressing or snarky or anything like that, and I don't mean anything bad toward our friends at the big EMR companies, but there's a huge opportunity for AI, whether to listen to the physician as he's talking, to transcribe notes, where they can turn around and spend even another minute or two with a patient and improve that patient experience.

So, I am really excited about what the future holds uh uh particularly for patients and better outcomes.

The through line of our conversation seems to be customer experience and broaden it uh patient experience whatever domain that might be.

I think that's true. I I look if not them then who? I I mean if you're not doing it for for them then why are you doing it?

And and look, you and I, if I take off the motherhood and apple pie hat and say "Okay Jay yeah patient experience is super important, but really companies exist for shareholder value and to make money." Fine.

If you're not wrong, I would argue that one of the best ways to do that is an amazing patient experience and an amazing customer experience.

if I'm making my sights happy or at least less mad at me or am I providing a frictionless uh experience and they always know at the other end is a company or a team that is working hard to do the best.

We're not always going to be right.

We're not always going to get it right, but we're always doing what's important and what's the best for them and for their patients.

If they know that, I would argue that they're going to want to continue to do business with Clario and they're going to continue want to continue to partner with us. Um, so I think the two are inextricably linked.

I I I think you can have an amazing patient experience, an amazing site experience and sponsor experience, maintaining scientific rigor, high quality, privacy, speed, and all the other things that we want to do.

And you can still make money as an organization and build shareholder value and do all of those things. And I would argue that if I can do the first one really, really well and I'm making good choices, the second one will come.

What advice do you have to business and technology leaders in the enterprise when it comes to developing AI projects and scaling those projects as you have done?

Don't do it in a silo whereas my old boss used to tell me a highly polished cylinder of excellence.

Um don't look look partner you know uh talk to your partner ecosystem other CIOS other CXOs uh talk to your suppliers understand educate yourself but talk to your your peers in the organization and work with them not against them uh whatever you do don't make it a a a techon uh techonly endeavor uh in no way does that minimize the importance or the the excitement about the technology but I promise you if you can do all of those things it will speed up what you're trying to uh accomplish. And as always, Michael, and I think I said this on our first interview, think big, start small, scale fast.

Think big, start small, scale fast.

Great advice. Hey, we have one last question that's come in very quickly from again from Luri Noruggov who says, "Do you feel like we have the right people, training mindset, uh the site patients nurses etc. to enable and provide all of the data needed for the AI applications or is the technology far in front of actual adoption.

There's a huge educational hurdle that we have to hit. uh there are people at the sites and the you know with the patients I I think they are just handed a lot right they are handed a lot of different devices and it and and I promise that it's not because they are not smart people or hardworking people it's just a lot and if I mean the first part of the question is do we have the right people yeah I mean the ecosystem of of investigators and sites are amazing and and they work their tails off and they're more incapable of picking this up.

I think it's on us to train. It's on us to show them the power. It's on us to make it simple.

I think it's going to require patience, Michael.

I do not think we're going to be able to hand them a magical calculator and say, you know, and have them be enamored with the tech in in one day.

It's going to take some time.

And so, we have to be, I think, a little patient as we kind of change the paradigm.

Uh, but I'm I'm I'm optimistic that uh, you know, we have the right people.

But we just got to meet them where they are. And on that note, Jay, a huge thank you. I'm so grateful for your taking the time to be here with us today.

Really, really appreciate it.

My pleasure, Michael. Thank you for having me.

And thank you to everybody who watched.

You guys who ask such amazing questions.

You are so smart.

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