Navigating the Future of Life Sciences: Insights from an Industry Leader with Dr. Arda Ural, EY Partner and Americas Market Leader for Life Sciences and Healthcare

[00:00:00] Welcome to the Chalk Talk, Jim podcast, where we explore insights into health care that

[00:00:07] help uncover new opportunities for growth and success.

[00:00:11] I'm your host, Jim Jordan.

[00:00:18] Join us for an insightful discussion with Adi Urel.

[00:00:21] He's an EY partner and America's market leader for life sciences and health care for E&Y.

[00:00:26] He's over 30 years of experience going from Pfizer to biotech consulting, and he brings

[00:00:31] unique perspective on the rapid evolution and innovation going on in health care industry.

[00:00:36] In this particular episode, we dive into the complex challenges and exciting opportunities

[00:00:41] shaping the future of life sciences, Arshid's insights on the impact of macroeconomic trends,

[00:00:47] geopolitical shifts, and the groundbreaking advances of AI on drug development, clinical

[00:00:53] trials and health care delivery.

[00:00:56] We explore how companies are navigating rising costs, regulatory pressures, and the quest

[00:01:00] for health equity in a transforming landscape.

[00:01:04] Adi also reflects on the key lessons from his remarkable career journey and what it

[00:01:07] takes to make a meaningful impact in an industry that touches all of our lives.

[00:01:12] So Adi, thank you for joining us and tell me and the audience a little bit more about

[00:01:16] yourself.

[00:01:17] Jim, thanks for having me.

[00:01:18] This is Adi Urel with Ernst & Young as a life sciences sector leader and happy to be your

[00:01:23] guest today.

[00:01:24] So maybe a little bit about myself.

[00:01:26] I started my journey with the sector about 30 or so years ago.

[00:01:30] I'm Turkish, I was born and raised in Istanbul with the public schools over there.

[00:01:35] When I joined Pfizer after a couple of years, they decided to relocate me to New York.

[00:01:39] That's how my journey in the US continued.

[00:01:43] Obviously immigration is for anyone.

[00:01:45] It's a trade off you're leaving your network or friends and family behind.

[00:01:49] In return, I'll try to make a bigger impact, learn more things and get up your game if

[00:01:54] you will, in the life sciences business, which is usually a global business as you

[00:01:59] know.

[00:02:00] And so that was I think an interesting turning point for me.

[00:02:03] So I got fortunate in Pfizer when it was growth years to launch Viagra or manage Celebrex

[00:02:09] in the US.

[00:02:10] So those were great goings and then took an entrepreneurial spin in 2002 to join a biotech

[00:02:15] company that was developing a first anti-VGF treatment for the wet form of macular degeneration,

[00:02:22] which is a preventable form of blindness.

[00:02:27] So we launched the company, IPO'd the company, launched the product, I got acquired and then

[00:02:31] moved to Bechtel Dickinson to run a couple of businesses there.

[00:02:35] I was their strategic marketing lead.

[00:02:37] And then I made the twist from the industry to the consulting side of the advisory side

[00:02:43] of the business.

[00:02:44] And then the last eight years with EY and I led our M&A practice for life sciences.

[00:02:50] And then for the last several years, I am accountable for our life sciences sector,

[00:02:56] spanning all of our services to our life sciences clients.

[00:03:00] So it's a multi-billion dollar business.

[00:03:02] It's been growing double digits over the years and I'm privileged to serve our partners in

[00:03:07] the business.

[00:03:08] Yeah, we could talk about so many ways you fit into life sciences because I was following

[00:03:12] some of your posts.

[00:03:13] You're into synthetic biology, you're into helping people do M&A and organize.

[00:03:20] So maybe, how would you describe your role within this healthcare continuum in helping

[00:03:24] all these folks?

[00:03:25] Thank you.

[00:03:26] Look, I think we are fortunate to be in this industry because I just got into the industry

[00:03:30] by total coincidence.

[00:03:32] It could have been another industry, but certainly this is one that makes a difference in people's

[00:03:38] lives because ultimately we are here for whatever, 80 years, 90 years, whatever the biology permits

[00:03:43] us and then to the point that we improve the quality of life and or prolong the longevity

[00:03:48] of human beings, that's the best impact we can have.

[00:03:51] And we are fortunate that anyone who's listening to this probably is fortunate to participate

[00:03:55] in that industry.

[00:03:56] So what did we do overall in my role and Ernst & Young?

[00:03:59] So we have about 400,000 people worldwide and about 80,000 in the US.

[00:04:05] Probably depending on the surges and more balanced out seasons, we have 10 to 20,000

[00:04:11] people serving our life sciences clients in that time period.

[00:04:16] We have a range of services to help our clients from an end-to-end perspective.

[00:04:23] We have M&A services that you indicated, M&A and strategy and transactions.

[00:04:28] We have consulting services focused on functional expertise.

[00:04:32] We have very deep tax expertise and then also insurance services, audit services for our

[00:04:38] clients.

[00:04:39] So across those four service lines, we serve companies in the pharma, biotech and medtech

[00:04:44] and also like life sciences tools and how fortunately no boring day, if you will, the

[00:04:51] challenges you're attacking are very diverse and intellectually challenging you and our

[00:04:57] team.

[00:04:58] So that's the role I've been doing for the last several years.

[00:05:01] And then certainly every day is a new day.

[00:05:03] Every day is a different day that keeps our journey going.

[00:05:07] To your point about one day you are dealing with how does the human genome can be utilized

[00:05:13] as a monetizing asset.

[00:05:15] The other day you deal with what's the synergy model for an acquisition or the next day you

[00:05:20] deal with what's the best supply chain methodology and approach for a tech client that's going

[00:05:25] to lower their OPEX.

[00:05:27] So these are really, you know that what you do is something, but why you do it is also

[00:05:31] very important because ultimately when we do our jobs, it will help prolong lives or improve

[00:05:37] quality of life, which is great reason to be waking up every day and then going to work.

[00:05:42] So maybe we can get one of the things I love about talking to someone that's part of a

[00:05:46] large company, the amount of market data that comes to you on a daily basis is every time

[00:05:51] I talk to someone like you, you're reading at least two plus hours a day just to absorb

[00:05:54] it all.

[00:05:55] If you look at life sciences right now, what do you see as the most interesting trends

[00:06:00] for you?

[00:06:01] I think great point because you've got to really follow otherwise your advice will be

[00:06:06] generic or not value added.

[00:06:08] So that's a great point.

[00:06:09] So you need to really keep yourself fresh with the content that we are generating and

[00:06:14] or just third parties generating.

[00:06:16] You need to be on top of.

[00:06:18] So in terms of looking at the market today, 2024 and beyond, maybe there are, I would summarize

[00:06:24] three things we need to watch for our industry.

[00:06:28] And they are, I would say macroeconomic trends are certainly we are in the middle of a inflection

[00:06:33] point, which I'm going to come back to in a second.

[00:06:36] Global challenges is another one, those variabilities, how they affect the global industry like life

[00:06:41] sciences and third one, the advances of AI.

[00:06:44] Of course it has tremendous opportunities, certain challenges to manage, but those are

[00:06:50] the three as I can expand on them if you're interested.

[00:06:53] On the macroeconomic one, we are coming off the end point of tremendous quantity of easing.

[00:07:00] So we are now looking at the timing, not if, but when the Fed will start T-prank the interest

[00:07:06] rates, which is going to be an inflection point for us because if you're an M&A or if

[00:07:10] you're in the CapEx investment cycle, you watch the cost of capital and that's what's

[00:07:16] determined right now.

[00:07:17] I think we believe we saw in the first quarter of 2024, we saw some movement in the transactions

[00:07:23] as well as IPOs, as well as some easing in the deployment total capital.

[00:07:28] We do believe it can sustain if the rates will start to be cut sometime over the summer

[00:07:37] and that's what the odds are today.

[00:07:38] But we are recording today and then like two weeks from today, you get a different payroll

[00:07:42] report or a different personal expenditure report.

[00:07:46] These things will be articulated differently, but at some point during the next six or nine

[00:07:51] months, we believe a cut will happen.

[00:07:54] And then when that happens, I think the markets will be very favorable in deploying capital.

[00:07:58] And I don't mean capital markets, I don't mean stock markets, capital markets in general.

[00:08:02] And that will have a trickle down effect on down from boards to the operating committees

[00:08:07] to the operators of the businesses.

[00:08:10] So that's one thing we are all watching.

[00:08:12] That's the macro look out.

[00:08:14] And the second piece is in the geopolitics.

[00:08:17] Up until COVID, I think the conversations were mostly about globalization and how we discover,

[00:08:24] develop and manufacture and then distribute products globally.

[00:08:28] But I think COVID and then the ensuing Russia's invasion of Ukraine created people to think

[00:08:34] maybe we should rethink the globalization because political tension can get in the way.

[00:08:39] So what that means is our global supply chain, which was heavily relying on China for API

[00:08:45] and semi-finished products from India.

[00:08:48] And those numbers were, FT took down those numbers, but I think it was first originally

[00:08:52] discussed about 80% of the all after product ingredients were coming from China.

[00:08:58] Is a risk for decoupled economy that especially for lifesaving medications, whether they are

[00:09:04] generics or not, you just cannot rely on a foreign sovereignty to be upstream at the

[00:09:10] beginning of the faucet.

[00:09:12] So for that reason, I think everyone, not just you guys, but everyone is looking for

[00:09:15] self-sustained strategies or near shoring or friend shoring, ally shoring, your picture

[00:09:21] methodology.

[00:09:22] So that's important also in, that's the manufacturing side of the house, supply chain of the house,

[00:09:28] which we got all very sensitized during COVID.

[00:09:31] But then on the expansion side, global expansion of your portfolio was a major factor for determining

[00:09:38] your valuation and your robustness and scale.

[00:09:41] So now I think the interest is shifting more and more toward local or regional and self-sustainability.

[00:09:49] So that's clearly having a big impact on how our industry thinks about it.

[00:09:53] So those are the geopolitical piece.

[00:09:54] And then the last piece, which is, I think you just can't finish a talk or panel without

[00:09:59] mentioning Gen AI.

[00:10:01] Where we are with the Gen AI, I think it's clearly a revolution, probably the most significant

[00:10:08] technological advancement that we have seen in our lives.

[00:10:12] And potentially our people in the earlier, in their careers will live through notwithstanding

[00:10:17] another breakthrough comes along.

[00:10:20] Maybe if that's maybe it's quantum computing, that's going to make things really faster,

[00:10:25] unimaginably faster than what we have today in cracking things.

[00:10:29] So AI of course can help us in two ways.

[00:10:33] One, the industry has been stuck at a high cost basis.

[00:10:37] If you look at 10 years back, the industry's SG&A is about 28, 29% didn't change.

[00:10:44] And R&D cost of R&D as percentage of revenue has been increasing steadily.

[00:10:49] I think the number was 12% or so 20 years ago and now it's 18% of the revenue.

[00:10:54] So something's got to give in terms of lowering the operational cost basis.

[00:10:59] And then AI is extremely well positioned to do so by automating things that would require

[00:11:04] involvement.

[00:11:06] Now that involvement would be flipping over as a human supervision.

[00:11:10] So that's, I think, very exciting to help the industry.

[00:11:12] The second piece on that is not just the cost lowering capability, but also accelerating

[00:11:18] drug development and commercialization and supply chain on the easiest use cases we have

[00:11:24] seen so far has been on the clinical trials.

[00:11:27] Clinical trials require a lot of regulatory and administrative and document capture steps

[00:11:32] by asking AI to be accountable for that.

[00:11:35] So it's looking at the data and just a co-pilot would summarize the data on behalf of a person

[00:11:42] and just significantly accelerating it.

[00:11:44] I just tested early on about a year ago, what if I ask AI to write a protocol in a particular

[00:11:50] therapeutic area?

[00:11:52] And I was impressed, it was 70%.

[00:11:53] This is just generative AI, nothing proprietary, nothing trained on a particular database.

[00:11:59] It was like 70% there, the data point, the primary endpoints, the inclusion exclusion

[00:12:04] criteria, the interpretive area, the nuances were baked in.

[00:12:08] And this is again, just generic, everyone can do it with publicly available open source

[00:12:13] data.

[00:12:14] Just imagine how this could be more effective when you start training that large language

[00:12:19] model on your library of assets.

[00:12:23] And those are very easy use cases to prove how we can get there.

[00:12:28] I think that's very exciting.

[00:12:29] And then a group of people as they should are also raising the challenges and threats

[00:12:34] that come from AI.

[00:12:36] That's obviously a legitimate concern, data privacy, cybersecurity, those are data governance,

[00:12:44] very real concerns.

[00:12:45] We are probably far away from this Skynet moment, but if we don't do responsible management

[00:12:52] of the AI, we can let chatbots taking over elections or cybersecurity being at the hands

[00:12:59] of the ill-intended agents can become a big threat for the industry.

[00:13:05] So I think AI is clearly positioned very well to do a positive impact assuming we cover

[00:13:10] it.

[00:13:11] That's where I see the three big buckets of how the industry got launched over the next

[00:13:14] couple of years.

[00:13:15] I would probably add in too, the US government negotiating drug pricing would be a pretty

[00:13:20] significant change too in the macro.

[00:13:22] Absolutely.

[00:13:23] Great point Jim.

[00:13:24] I haven't seen the immediate impact of the innovation reduction.

[00:13:28] I keep saying innovation reduction, it's like inflation reduction act.

[00:13:30] I think it's a joke, I think for us, but the inflation reduction act will have its impact

[00:13:35] in three to five year timeframe because today while a few biotech companies have maybe deprioritized

[00:13:42] some of the programs, I think the bigger impact will come down the road because the program

[00:13:47] compels you to start multiple indications at the same time so that the clock doesn't

[00:13:52] start ticking down on the lead indication and you will be exposed to that.

[00:13:59] Obviously you're going to make that list of whatever that number is going to be for you.

[00:14:03] Say you started at 15, it's going to be 25, 30, 40 in the next few years, but you don't

[00:14:08] have already access to capital to start your initial trial, let alone your multiple trials.

[00:14:15] So I think the larger pharma companies with the balance sheet to afford this will be favorably

[00:14:22] positioned versus emerging biotechs who needs to, who has to prioritize their initial indication.

[00:14:29] You called it out wild.

[00:14:31] So IRA and other regulatory issues are going to start weighing in on the innovation pressures

[00:14:37] that we'll be facing.

[00:14:38] Yeah, and I think I tell this story sometimes about how, what a chief economist would have

[00:14:44] said for drug pricing 40 years ago, not anticipating it would set us up to be a challenge.

[00:14:48] So for our audience, I'm going to do a little accounting nerd with you.

[00:14:51] So I'm going to, one of my favorite models is the Duplatt model.

[00:14:54] And for the audience, it's net income over sales times sales over assets.

[00:14:58] It's over equity, you cancel it out and you get return on investment.

[00:15:01] And what that helps you see is net income over sales as I sold something, how much money

[00:15:04] did I make?

[00:15:05] And in the drug industry, that tends to be high because for the drug industry, it's the

[00:15:10] sales asset, which is that capital talk that you're talking about.

[00:15:14] The drug industry a long time ago when other governments said we'll only pay so much for

[00:15:19] this pill, anything over variable cost.

[00:15:21] I'm trying to get money back from my clinical trials.

[00:15:23] So I think for our audience, just to maybe peel back some of the brilliant things that

[00:15:28] you said is you're fighting to keep your price, your revenue.

[00:15:32] It's really the productivity of your asset to fund your trials, which is cost of capital

[00:15:36] is in there and then time to do the clinical trial, the number of patients that are in

[00:15:39] there.

[00:15:40] And so it's a little different from other businesses that are more driven on their return

[00:15:44] and assets from net income over sales.

[00:15:46] I was at McKesson and we obviously, they're Fortune 7 or something like that.

[00:15:52] And for us, it was sales over assets looking for productivity things there.

[00:15:57] Whereas when I was with Johnson and we were selling medical devices, it was a different

[00:16:02] model.

[00:16:03] So this challenge with drug pricing, it would be very hard from a PR perspective to say

[00:16:08] to the person on the street, drug pricing's high, look at the margins they're making.

[00:16:11] But the average person doesn't understand that the number of assets that have been deployed

[00:16:15] for a decade or more.

[00:16:17] And it's a real challenge.

[00:16:19] And so the question is, how can AI make that drug discovery process?

[00:16:23] I think that's going to be the partner as you were referring to, to bring down in the

[00:16:27] old days, they used to say 2% of drug starts end up in a commercial and you can go into

[00:16:32] the various phases and watch them drop off.

[00:16:36] And good friend of mine, Lance Taylor, invented high content screening and he's a CMU and

[00:16:40] now at Pitt.

[00:16:41] And he would say, fail early and fail often was his mantra.

[00:16:45] If we can bring the failure, when you're doing something in the lab and early, that's a really

[00:16:49] significant amount.

[00:16:50] So how much of your specialist practice is geared towards that optimization of drug

[00:16:56] discovery and clinical trial?

[00:16:58] Very good point.

[00:16:59] And I would also add that we are in an election year and then drug pricing is going to keep

[00:17:04] coming up, obviously more so than before.

[00:17:07] Maybe before diving into your question, couple supplementary points to your great narratives

[00:17:12] there.

[00:17:13] The cost of drugs, average cost of drugs have been creeping up because the lower hanging

[00:17:18] fruits have been mostly picked up.

[00:17:21] Today you don't develop an antihypertensive or antidepressant agent or even an antibiotic

[00:17:28] because the challenges to get approved because of the generics that are available will be

[00:17:33] very hard.

[00:17:34] So what that pushes the industry is to become more targeted precision products.

[00:17:39] And those are obviously much more difficult to come up with the right precision targeting,

[00:17:44] whether it's like the interop, anti, or interop conjugates should be very popular recently

[00:17:48] or monoclonal antibodies, which have been helping the industry lift from the 2010 patent

[00:17:54] clip to those and then cell and gene therapies, which is, I think we got a lot of, I would

[00:17:58] say buzz about them, but only a handful have been in the market so far because of the supply

[00:18:03] chain and commercialization, of course, the challenges.

[00:18:06] So the bar on the industry is getting higher and higher for a foundational reasons.

[00:18:11] And like you indicated, maybe the first pill costs you like $2 billion, but the next ones

[00:18:15] are like a couple of cents.

[00:18:17] So there's the problem is to get to the first pill to get there.

[00:18:20] But the industry has really strong, I'm very impressed with the innovation.

[00:18:25] Obviously the engine of innovation is certainly very strong and all the entrepreneurs who

[00:18:31] are pushing their, pushing hard to, to get to their products.

[00:18:34] So a question on the drug discovery and how maybe AI can help there is, is the kind of

[00:18:39] a source of a lot of dialogue.

[00:18:41] Let's give an example of the protein folding and at some point there are 150 million proteins

[00:18:46] and how they approach, how they connect to the cell receptors or block certain things

[00:18:52] is almost a geometrical problem as opposed to a chemistry problem.

[00:18:57] And for a human brain to, to compute all those with the computational skills we have today

[00:19:02] is not fast enough.

[00:19:03] And yet the open AI, the company was able to, the AlphaFold that is, was able to solve

[00:19:11] those problems much faster than a person.

[00:19:14] So there is the Moore's law, if you will, that you apply to how speed of the transistor.

[00:19:20] And then the opposite of this like Eroom law, like spelled from backwards, which is actually

[00:19:25] the cost of products increasing exponentially.

[00:19:28] We need to make those both laws to come together and help with the product development.

[00:19:33] So drug discovery, very early stages of it, but there are companies who have been doing

[00:19:38] it for decades.

[00:19:39] And my hope is that there's not solid evidence at this point.

[00:19:44] My hope is that it will help generate a lot of targets that are de-risked early on to

[00:19:50] help with the clinical trials because we still go by the FDA guidelines for submitting a

[00:19:57] investigation, new drug, the INDs.

[00:20:01] Still, there is the animal models, there is the toxicology, there's the two species you

[00:20:06] got to pick up. Then you move on to the phase one after our INDs improve.

[00:20:10] Then the phase one takes certain time and money and then you move on.

[00:20:13] I think we will probably not break that cycle, but can we accelerate some of those

[00:20:20] individual modules within that to get there?

[00:20:23] One, I think, law that's not getting a lot of attention is 2030, I believe.

[00:20:28] I understand, if I'm not mistaken, the industry got to stop testing on animals.

[00:20:33] And so if that is indeed accurate, I need to check that we can do that offline.

[00:20:37] But so that requires a lot of in silica testing.

[00:20:41] So how can we test the safety and effectiveness and early proof of concept of all these

[00:20:47] products in silica without requiring animal organisms, animal models?

[00:20:52] So that's a major lift that's getting from AI.

[00:20:56] And at least there is a solution path for these once immense kind of sounding goals or

[00:21:02] challenges. At least there's a path that AI will continue to.

[00:21:06] We are very early stages, Jim.

[00:21:07] I mean, you called it out earlier.

[00:21:09] So we are early.

[00:21:11] So how do you keep current on all this?

[00:21:13] There's a lot of different activities that you focus on.

[00:21:16] That was one of them.

[00:21:17] We didn't even talk about M&A trends.

[00:21:19] Those are all things that you're faced with every day as part of your broader track.

[00:21:23] The M&A and capital deployment, I think there's enough resources there.

[00:21:27] And then we obviously are, we have a pretty robust team that consolidates and summarizes

[00:21:33] and we are able to articulate the implications for the industry.

[00:21:37] And in fact, in a couple of weeks, we'll be out issuing our 34th Biotic Beyond Borders

[00:21:44] report.

[00:21:44] That's impressive before like the industry was really as mature as it is.

[00:21:49] So the UI started doing that.

[00:21:51] So that is clearly a team effort, but also having an open mind and not being misled by

[00:21:57] a single KPI, but more so multiple signals, including the, some of them like the macro

[00:22:03] we talked about.

[00:22:04] In terms of the overall, I think you can get lost in trying to be on top of everything.

[00:22:08] There's some, you've got to follow some good books.

[00:22:11] Every six months I make recommendations for five books and those are mostly kind of

[00:22:16] biased towards life sciences, but that kind of keeps your perspective and context on the

[00:22:21] bigger things.

[00:22:21] And then there is the daily flow of content.

[00:22:25] Most of it's free.

[00:22:26] If your listeners here are interested in finding, I think they spend 30 minutes online,

[00:22:31] they will find many very insightful resources that they can gain access to to stay on top.

[00:22:39] But it's an effort.

[00:22:39] It's a commitment.

[00:22:40] Like you said, you mentioned like two hours.

[00:22:42] That's almost that time because you've got to follow the MNA, but you've got to also

[00:22:46] follow JAMA and NEJM and other subspecialty public issues as well.

[00:22:51] So it can, you can get, I'd say, cheat in a candy store, but also you can get lost.

[00:22:56] So when you reflect back, what's the biggest lesson you've learned in your journey so far?

[00:23:01] I think, look, this is a interesting, I've been like 30 years in this and you're going

[00:23:06] to have the plan that the moment things start happening, the plan will be useless

[00:23:11] because if somebody asked me 32 years ago, like an engineering student in Istanbul,

[00:23:16] or you will be part of a 400,000 people firm being accountable for a multiple

[00:23:23] billion dollar P&L, I wouldn't understand what it is and wouldn't even imagine.

[00:23:27] So I think my counsel to everyone, obviously they have their own lessons, but my counsel

[00:23:32] to folks who are in their early on careers, have an open mind, just have a plan, but be

[00:23:38] ready, recognize that be ready.

[00:23:41] That plan may be useless, but it's the planning, not the plan.

[00:23:44] I think Eisenhower called it out, but also I'll call out another great philosopher,

[00:23:49] Mike Tyson, everyone has a plan until they're smacked in the mouth.

[00:23:53] I think that is, that's how I looked at the journey.

[00:23:56] The other one I think recently, the show weeks have been very popular.

[00:24:00] So I recommend folks taking a look at the Marcus Aurelius.

[00:24:04] I just bought that book actually.

[00:24:08] I mean, the guy was a Roman general.

[00:24:10] His life was literally out there in the field and the campaigns living in the mud

[00:24:15] and fighting in the mud and ultimately became the emperor, but his, the slowing

[00:24:21] down the life philosophy to just focus on what you can control basically.

[00:24:26] Don't let your emotions get in the way.

[00:24:29] I think that's so true even in 21st century business world.

[00:24:34] Yeah.

[00:24:35] It things change so quickly and so fast that it's hard to keep track.

[00:24:39] And I was, I will have some of my students look at my background and my resume, which

[00:24:44] was life sciences, startups, nonprofit profit, venture capital, and academia.

[00:24:49] They say, Oh, I'd like to do that.

[00:24:50] How do you do that?

[00:24:51] I'm like, you can't make a plan for that.

[00:24:52] That just, for me, I think it was finding really good companies to work with, whether

[00:24:57] large or small, but importantly, good people to work for.

[00:25:00] It's good.

[00:25:01] I think early in your career to get that branded experience.

[00:25:03] A lot of times my students will come out and say, Oh, should I go work for a firm

[00:25:07] like yours for a few years or should I go do the startup?

[00:25:10] I'm like, get branded first, get that experience.

[00:25:12] And later after when you've been trained, because business school does training,

[00:25:15] but it's not the details that you've talked about here are hard one to be

[00:25:20] able to be articulated so simply.

[00:25:22] When you look at it.

[00:25:23] Yeah.

[00:25:24] But the other thing, maybe if I can just interject there early on, if you operate

[00:25:29] in a process driven company that will teach you how it can be, or it should be.

[00:25:36] And then you will have a point of view.

[00:25:38] What can you accelerate without breaking the law?

[00:25:41] You know, kind of the integrity of the process and or getting in trouble.

[00:25:45] So the, this high integrity, high value system is certainly very key.

[00:25:49] And once you train that, once your muscle memory is there, then you can go ahead

[00:25:53] and explore the world if you will.

[00:25:55] Cause I, to that point, I think your processes are as much

[00:25:58] your brand as your product.

[00:25:59] Gotcha.

[00:26:01] So what's your biggest opportunity for growth and your biggest opportunity for

[00:26:04] concern for healthcare as you look out?

[00:26:06] I think we covered the Gen AI to a large extent.

[00:26:09] I think for healthcare life sciences, what it offers as an opportunity is

[00:26:15] everyone is working on making the use cases that will scale.

[00:26:19] So that's the one that we are forward.

[00:26:21] And then what can go wrong?

[00:26:23] And AI can go wrong if you don't govern it right.

[00:26:26] But also I think the, in the next couple of years, there might be scenarios where

[00:26:32] the macro conditions may actually not necessarily be conducive

[00:26:36] to global business to operate.

[00:26:37] And while that's not the scenario we would like to see, those are not,

[00:26:42] they're probably possible.

[00:26:44] I would like to see unlikely, but you need to be ready for the possibilities

[00:26:48] or wrong possibilities, so to speak.

[00:26:50] I agree with that.

[00:26:51] I think that I would love to have the data to be able to

[00:26:54] understand this a little better.

[00:26:55] But you ask yourself, if you brought back some of our manufacturing base to answer

[00:27:00] those security concerns and availability concerns, how would that help our economy

[00:27:05] and help with that pull up our bottom third of our economy into maybe the

[00:27:09] middle, which would be interesting.

[00:27:10] Absolutely.

[00:27:11] Yeah.

[00:27:11] And the other thing, maybe just a final thought here, there's the overarching

[00:27:16] sentiment and I presented so many times on it, looking at the ROI of the spending

[00:27:22] on health care versus to life expectancy.

[00:27:25] And US is not looking good when you compare to Europe or Japan.

[00:27:29] But there's one catch there, which I would like to leave everybody.

[00:27:34] It's about education.

[00:27:35] If you, there was an analysis, Wall Street Journal published it,

[00:27:37] I think it's JAMA did it.

[00:27:39] So I can't quote the author, but when you dissect that data for college education,

[00:27:45] US's life expectancy is like Denmark.

[00:27:48] Yeah.

[00:27:49] So 40% of the US population is college educated.

[00:27:52] I think if you take out 70%, it's a two year college.

[00:27:54] If you just take that out, it gets even more compelling.

[00:27:57] So education and health care go hand in hand and then health equity and

[00:28:02] education go hand in hand as well.

[00:28:03] So if you fix those things, education and health equity, I think everyone will have

[00:28:09] a very positive lift up from all the metrics we are looking and that will be

[00:28:14] probably a great long term goal for anyone with the ability to influence that.

[00:28:20] Fantastic.

[00:28:21] Anything else you'd like to share with our audience?

[00:28:23] I thank you very much for having the dialogue here.

[00:28:26] I think very interesting times with what AIGEN offered to us and looking forward

[00:28:31] to continuing the journey with all your listeners.

[00:28:34] Thank you.

[00:28:36] Thanks for tuning into the Chalk Talk Gym podcast.

[00:28:40] For resources, show notes and ways to get in touch.

[00:28:44] Visit us at ChalkTalkGym.com.