Clifton Leaf/Brian Caveney at the 17th Annual Personalized Medicine Conference

[00:00] Thank you, Chris. Let's just bring up Brian Cavity, who is chief medical officer and chief scientific officer of Lab Corporation of America, one of the largest providers of laboratory testing. Hey, Brian. Hey there.

[00:20] who also has a law degree, a medical degree. Don't hold that part against me. And MPH, and my first question is, why did you ever leave school? I left school. Yeah, exactly. It's like such a safer space than the rest of us here here. Yeah. This is a great opportunity to talk about.

[00:40] tip of the spear, diagnostic testing. You know, I read that the CDC says there are 14 billion, 14 billion laboratory tests per year in the United States alone. You, Laboratory Corp. offered a menu of 6,700 tests, which by the way is more than

[01:00] them to combine movies and TVs on Netflix, just so you know. That is an extraordinary amount. Is anyone sort of flipping? I didn't know we were competing with them. Well, if you're flipping through Netflix and you're trying to think, what can I watch? And you go through that menu, imagine this is significantly more a medical test you can order. You know, we've had some sort of discouraging remarks.

[01:20] about the innovation space. And I'm going to add to that because you, as the tip of the spear, a huge number of medical decisions are based on your laboratory tests, and yet your margins stink. It's very, very difficult to innovate.

[01:40] We love our biopharma partners. We would love to have their margins as well. Exactly. We do not in the diagnostic situation. So will all the pressures, the regulatory pressures now, the pressure of laboratory-derived tests that you now face, and these challenging margins and the fact that you live in an environment

[02:00] where payers can sort of decide one way or another whether they're going to pay for your test or not, and you've got to deal with those results. How do you innovate? How do you innovate? Well, you're right. That wasn't very depressing start. It's a depressing start. I specialize in the depressing start. I mean, I was lucky enough to practice medicine for my own life.

[02:20] about 10 years full time before going into other venues, including being at a payer for a while. And I can say, you know, any doctor, you can't go into your clinic every day without knowing that you're gonna have a laboratory available to give you the answers that you need to make decisions for your patients. Now the issue is, or one of the issues is, the diagnosis

[02:40] is up front. You want to get a good, precise, accurate diagnosis, but then as soon as you get the diagnosis, then you're onto what matters to the patient and the treating physician, right? What am I going to do about it? A surgery, a particular medication, etc. And so we've got that one point in time up front when the patient comes in to help the doctor make an accurate diagnosis. The problem is even though we have all of

[03:00] these different lab tests, we have an unlimited amount of information. Some reports still suggest that up to 20% of patients are incorrectly diagnosed or misdiagnosed for complicated diseases up front. So anything we can do to innovate in the diagnostic space, not just laboratory medicine but radiology and all of the other modalities up front.

[03:20] To help a doctor or other clinician make a better diagnosis up front is going to create better outcomes down the road. So a lot more effort needs to go into that space. So when you talk about the classic case where you're looking at a protein for example in the blood and you're determining is this a marker of disease progression or what level?

[03:40] should it be. You talked about the opportunity to look at multiple proteins and see them in complex with one another and and look at how that may inform decision-making. That's an extraordinary promise. Talk a little bit about the challenges of that but also the opportunity. Sure.

[04:00] For a hundred years, a pathologist or laboratory scientist has either been getting a piece of tissue and looking inside a microscope to see what's changed with the cells, or we've been looking at one particular biomarker in blood, urine, whatever it is. And that can be incredibly helpful for a doctor taking care of her patient, making a decision based on the number

[04:20] that we send back to them. But I think more and more, with the computing power that we have, with the information that we have available, you can learn a lot more than just looking one biomarker at a time. We're doing a variety of things, whether it be in complex autoimmune diseases, neurologic diseases, others, where you can learn a lot more from looking at the complex

[04:40] of different proteins together to predict disease progression, likelihood of radiographic progression of rheumatoid arthritis as an example, other things like that. Of course the challenge is we don't yet have the coding structure, the reimbursement methodologies in place to account for the

[05:00] math of looking at individual biomarkers because sometimes not every individual biomarker may be independently clinically significant, but it's the combination of them together and how they're acting biologically in your body that can give the treating physician more information. We need to get a lot better at figuring out how to look at those multianalytic

[05:20] algorithmic analysis type situations and get better coding structures. In terms of the reimbursement structure, that really is fundamental to your business. You have talked about the sort of wild west of payers out there where there's no single threshold that determines whether a payer

[05:40] will pay for a test or not. So you have to deal with that every single time you have a test for the thousands of pairs you work with. You work with something like 1,900 pairs. We do. You know, Helmi from Garden talked about this a bit yesterday as well. It's very complex because not only does every commercial plant have different lines of business with different ways.

[06:00] is

[06:20] tell our R and D teams here's the evidence you need to generate to demonstrate clinical utility that we can then take to the public and private payers and have some reasonable likelihood of getting a fair and adequate reimbursement for the work that we're putting into it. So that does stifle innovation or at least distort the mechanism by which the funding takes place.

[06:40] Mike's been involved in so many companies that have been trying to crack this nut for years. We just need better visibility, better certainty around the framework of what's going to be expected. If we had more health plan medical directors like Mike Sherman yesterday who was a pioneer in this place, then I think we would have a lot more investment in R&D and diagnostics.

[07:00] And we'd be a better partner to pharmaceutical companies to be able to develop more therapy selection and better diagnostic methodologies to get patients on the right drug. It's interesting, this idea of visibility. I know you have obviously a complex process and infrastructure.

[07:20] of payment here. But I can go into any Walmart in the country and I can pick out a product and I'll have a price tag on it. So Walmart has this extraordinary price visibility. They know exactly what their inventory is, what someone's going to pay for it, and they get that money right there. How do you actually...

[07:40] with a business, how do you actually run a business where you have very little price visibility? Yeah. I guess reimbursement. Yeah, a couple of things to that of even so an individual lab test that we do, we may have a different negotiated allowable amount with every individual health plan based on some percentage of Medicare or some other kind of thing.

[08:00] like that. Another difference which is problematic if we talk about the way the FDA is considering regulating laboratory-developed tests is it's more of a service than it is a product, that you can follow good manufacturing practices for whether it's a pill or a widget that you would get at Walmart. It's very different in laboratory medicine, particularly for the

[08:20] more complex assays that we're bringing to market. So this is a solutions-based conversation. So I'm pleased to say. So you have some thoughts though. If we were just to take, for example, the publicly paid people who are on Medicare or anything.

[08:40] government program and say if we were to harmonize some of those rules, we might have a huge benefit from that. I think so. Probably at least half of Americans are on some government-sponsored taxpayer-funded insurance scheme of some sort, whether it be Medicare, all of the Medicaid plans, you know, DVA, Tricare, FEHBP, which

[09:00] million federal employees and their dependents are on. If we even just had some more visibility into the coverage policies and reimbursement policies there, if it was pegged to Medicare or something like that, then I think that may stimulate some more willingness to invest more R&D dollars, take a little bit more risk in the diagnostics industry.

[09:20] So we because we have more visibility to do it. How hard would that be to just harmonize those rules? I think our friends that are more politically connected know how difficult it is to get things done in Washington, D.C. So Michael Barr, he's going to help you do this. Farmers can partner with you on this. So we have we're going to have a handshake deal afterwards. OK, this did come up a couple of times yesterday.

[09:40] Jay Wogamoth and others mentioned that the diagnostics industry is so small as a relative percentage of the total healthcare dollar, call it maybe 3% of the healthcare system. So it's hard for us independently to get a seat at the table and be paid for the value we believe we bring to treating physicians into the industry. But I think more and more as we work across the industry.

[10:00] as we work with pharmaceutical companies and biotech companies to identify the right patients for their therapies, truly getting to personalized medicine, then I think we're gonna be a better partner, maybe get a little bit more opportunity to get innovation dollars going into diagnostics so we can improve the system. At the same time, you are innovating. You've got a

[10:20] group in Boston that's looking at AI and looking at the longitudinal history of a patient, an individual patient, so that you're finding potential signs, red flags early on in that patient's journey. We're lucky enough that we've been doing this for a long time. We have something like $46 billion.

[10:40] test results in our database and we've just not even begun to tap the insights that are in there. But we've done some really fun projects as we discussed with some biotech and pharma companies trying to identify the natural history of disease. So once you can once you eventually diagnose somebody with a particular disease if there's not a pathognomonic test for that then we might look at every lab

[11:00] test that we have in our database for 8, 9, 10 years before that final diagnosis, and then look for patterns of what you might think are not associated biomarkers to see what's changing over time that might give some element or prediction of the risk of the eventual diagnosis. And then that might enable us to help.

[11:20] Enroll patients in clinical trials a little bit quicker or get them in a certain pathway where there's an intervention that might stem the tide of disease and intervene. Give us a couple of examples of that. Many of the rare diseases, of course, are genetic mutations. Most of the cancer subtypes are just simply a genetic mutation.

[11:40] So, you know, any type of a genetic test earlier on in someone's life, you know, often there's a one per lifetime policy for payment for things for the wet lab component, the commodity part of doing a genetic test. But then we've got that raw sequence data available. And then as the variant data banks get richer, as we learn more

[12:00] about what particular genetic mutations might mean, there's no current mechanism to sort of retest that sequence data and then identify new insights of potentially a pathogenic variant that has now been discovered that wasn't known. It was a VUS or a variant of unknown significance before. There may be an opportunity to sort of unearth those.

[12:20] of the enzyme deficiencies, for example, where we've been able to see some other proteins, liver function tests, kidney markers that are starting to degrade that may not seem associated with a particular disease a couple of years before the eventual onset of symptoms that then lead to the manifestation of the disease that's eventually diagnosed.

[12:40] diagnosed, but then by then it's usually in one of the later stages. So again, if you can identify those earlier on and there's either a research protocol or some intervention that can be done that could be helpful to patients. So that key issue if there's an innovation that can be done, that's always a challenge about identifying somebody way early in

[13:00] terms of a disease process or telling them they're at risk for Alzheimer's 35 years from now without having an intervention. Exactly. Yeah. Not to mention the ethical and other issues that sometimes get raised by giving people information that they can't necessarily act on right away. Brian, like five years ago, you couldn't have a conversation with people in

[13:20] this room without hearing the weird microbiome. Everyone talked about the microbiome, and it was in every paper. There was every book about it. Talk a little bit about some of the promise, but some of the false starts that came out of that effort. I think there is an unbelievable amount of untapped information that we haven't found yet.

[13:40] not just your gut microbiome, but others as well. We're learning more about the vaginal microbiome, obviously oral microbiome, et cetera. I think the problem is there was so much media hype about it, and I'm sure Fortune never did this. We never touched it, never touched it. Very responsible media. But there was so much hype about it that I think

[14:00] think, then when we find out we're many, many years away from actual interventions, and it's not just if you have the raspberry yogurt versus the blueberry yogurt, you're going to magically cure your ex. I think that was a problem because now the public doesn't have the patience to do good science and to figure out what these insights are and then the interventions. But we have to remember.

[14:20] Tremendous interventions already from that early research. Just think of treating recurrent C. diff in hospitalized patients that came from a lot of the early microbiome research. So we're going to get there, but it just takes a long time to do good science and then figure out what the innovation is going to be. Another area of innovation is the sort of medium where we're trying to get to.

[14:40] would you get those biomarkers? For example, instead of blood-borne tests, there are urine tests, but there's also cheek swabs and other things, breath tests. Where are we on that front? Yeah. I mean, nobody really wants a piece of steel stuck in their arm. We know that, even though we do it a million times a day.

[15:00] The problem is the venous blood is just so homogenous and very predictable and we have decades and decades of great information about what we expect normal to be for certain people in there. But there's a lot of great research research being done on alternative matrices, alternative specimen collection. You know we can get a piece of anything and learn something about it.

[15:20] The problem is doing really good concordance studies between venous blood and anything else that you're taking a look at. There are some issues with capillary blood as well. Everybody wants just a simpler finger prick. That wasn't the only problem with tharanos, as most of you know.

[15:40] also violated the laws of physics and what they were suggesting. But we just have to make— I hate to tell you, but she was on our cover. I know. I know. I know. I'm sure that was not your editorial decision. No, it was before I was edited. Oh, okay. It was before I was edited. You came in and cleaned it up. I was deputy editor. And were more evidence-based.

[16:00] But I think we're getting there. I mean, we're doing quite a bit of research on salivary and capillary blood. Hopefully we can get more from urine, that the urine sample is easier to get than a venous blood. But frankly, even if we not just think of venipuncture as terrible, actually the solution, think of

[16:20] how amazing it's going to be when we get liquid biopsies rather than having to put somebody under anesthesia and have a surgeon go and try to harvest a piece of tissue from them. Or even think of the emerging science that we have now in CNS and neurodegenerative diseases. Nobody wants a lumbar puncture or a spinal tap.

[16:40] So if we can get better blood-based biomarkers to look for neurodegeneration, Alzheimer's disease, Parkinson's, myasthenia gravis, multiple sclerosis, that's going to be a tremendous advance over giving more patients lumbar punctures. So this seems like a great opportunity to lobby the cancer moonshot to sort of put in.

[17:00] put a chunk of research money into this, into this sort of new age of diagnostics. I think it's a whole continuum and we shouldn't look at it as little pieces. So for example, again I mentioned diagnostics and therapeutics need to be thought of together.

[17:20] particularly for complex diseases like cancer. But even the whole continuum from the early development, drug discovery, non-clinical, pre-clinical animal models that are necessary that have to be homologous to the human immune system, we need better access to those animal models.

[17:40] And, you know, organ on a chip, organoids, other ways of trying to do quick toxicology screening before we do human interventions. And then, you know, a better pathway for the clinical trials necessary to look at both the diagnostic and the therapeutic match together, and then commercialization of both.

[18:00] you off there. If you look at for example the semiconductor industry they have a pre-competitive organization that allows them to look for these kinds of things which would be of common value to all of the providers. Is there something like that with the diagnostic

[18:20] world that you live in. Do you and your folks at Quest and Garden, I saw Helene before, you know, others, you know, work together to try to solve some of the sort of big pre-competitive problems in terms of, you know, making sure that there are enough reagents, for example, around that your supply chain for all of these critical components

[18:40] components and diagnostics are available to you. We certainly learned a lot during COVID about the global supply chain challenges. You know, there's a there's a drive to go to single global suppliers so that you can get maximum volume discounts, do everything at scale superficially. And in the normal world, that's fantastic.

[19:00] The unit economics of that are really good. We learned in COVID that's a little bit of a challenge though if there's an outbreak in Italy and all of a sudden you can't get swabs or you know there are no more machines because of there's no exporting out of Germany and these other kinds of things. So you know it all comes down to the trade-offs in

[19:20] your supply chain of having some redundancy built in in different countries, different geographies, which is also good for natural disasters too, not just COVID. And so we and others are trying to make some of those balances. Working with state and federal authorities, of course, for customs, importation, exportation laws, all of these kinds of things. So there was a lot of controversy during the COVID era.

[19:40] especially early on in terms of the CDC and regulating diagnostic tests and who could do those tests and the quality of those tests. What have we learned from that era? We just went through a crucible. I assume there are some good lessons that came out of it. There are. You know, I think, Board, if there's one thing

[20:00] saying, as a physician, what I never questioned or thought that physicians would question is the credibility of the CDC, which happened unfortunately during COVID, a little bit because of the reagent issue with the COVID testing itself a little bit with the potential allegation of politicization of what was happening.

[20:20] There that's a shame because they're clearly the best epidemiologists in the world and we need to rely on the information that they're giving to the industry. And to the medical community to work together. So I think public private partnerships are always going to be important. You know another example there where competitors can can do good together quest.

[20:40] LabCorp did the majority of the genomic sequencing for the CDC to follow the variance. So when you would go to the Fortune website or New York Times or anywhere else and you would see the latest variance, a lot of times that data was coming from Quest and LabCorp who were submitting those sequences to the CDC every week and working with their scientists.

[21:00] Do we owe you some money? No. The taxpayers have already taken care of that. All right, go ahead. At a very low rate, I'm not saying. I keep hearing that. Our best discounts in the federal government. I keep hearing that in your industry. The low rate. It's, you know, in terms of, but COVID was a great example of what happens when an emerging disease, an emerging

[21:20] virus comes and suddenly overtakes the world that we were completely unprepared for then monkeypox showed up and you were very very quick to come up with a diagnostic for that. Well the good news is because we do so much infectious disease testing because we already have electronic interfaces for all of our infectious diseases with the CDC through the communicable disease

[21:40] reporting standard. We published papers with them on the epidemiology of emerging diseases. Our microbiologists are on their emerging pathogen committees. So we knew about it right away. And I think because we were so quick to act, along with our other industry partners during COVID, I think they were quick to call

[22:00] and say what can you do to help because we need scale quickly if this becomes another pandemic on top of the one we already have. So again I think showing that public-private partnerships are critical along with the academic partners that were often involved in some of the research that was taking place there. But it takes scale and reach to

[22:20] all of the physicians of America and beyond to be able to actually deliver a service, again, as opposed to a product or just a digital intervention. And you have to be on the ground as well. Yes. There were recent reports about a sort of flu-like disease in China, a known variable, a known origin.

[22:40] How do you, when you hear something like that, how do you organize your team to say how do we get on the ground quickly and identify? We're lucky in the fact that because about a third of our company comes from doing clinical trial laboratory work around the world, so we're already in over 100 countries and we are very well-

[23:00] connected with public health authorities and the pharmaceutical companies doing work in all of those places. So we tend to be very well connected there. But even just the scenario that you mentioned, because we are partnered so well with the CDC and other public health agencies here in the US, we tend to be ready to jump in and or lend our

[23:20] expertise or be ready to scale up the access necessary for different testing as soon as we can. So I'd imagine you'd have some generous profit margins to make sure you can handle all that work. I wish, I wish. We're doing a lot of it out of the goodness of our heart perhaps because it's the right thing to do for the system.

[23:40] the right thing to do. We're about to hear from one of my personal heroes, Kathy Justi, who founded the Multimalar Myeloma Research Foundation. And one of the things that Kathy did, and I hope I'm not stealing the thunder from her conversation, is to organize the patient community with the

[24:00] academic community and the drug development community, the drug makers, and force them to all talk to each other. And it seems to me that there's possibly an opportunity for you to integrate with the patient community in some of the work that you're doing. Have you guys thought about that? We have. We and others, we are

[24:20] starting to get more involved in either allowing consumer-initiated testing, where they're maybe having difficulty getting access to a physician, or they're curious, or they don't have regular health care, or they have a particular question they want answered, and then they might seek out lab testing and other types of diagnostics on their own.

[24:40] We tend to work more with the physician community in terms of where you're going with the next tests that are coming, the innovations, how to interpret it. There was a recent federal regulation effective last year called the Information Blocking Rule where now we and other diagnostics, radiology and other

[25:00] have to provide the information from the lab test results that we provide to the patient at the same time that we're sending it back to the ordering physician or clinician. And you know there was maybe from the historical paternalistic health care system a lot of our physician customers were very worried that some

[25:20] somebody that their patient was going to get the results of their BRCA test or another cancer test or the biopsy or an Alzheimer's test, something like that, before the nurse or the doctor at the clinic was going to be able to see it and then jump in front of that. So there are those types of issues of people deserve

[25:40] of access to their information, but yet at what point is the learned intermediary from the healthcare system that spent 10 or 15 years learning how to interpret this stuff going to be a helpful conveyor of that kind of thing? Sure. And we have sort of talked about the paternalistic nature of medicine and with patients

[26:00] patient, the patient populations oftentimes are very, very sophisticated because they're so personally invested in their own diseases, they have a lot of knowledge and so they may have insights about their own disease condition that would be valuable to sort of.

[26:20] give and take with the doctors. But in terms of, you mentioned the natural history, the natural course of diseases. In terms of that longitudinal information, patients are often the ones that have that own history and can give that to the researchers in terms of how to.

[26:40] What was it that was a red flag in my own blood or my own other markers that might indicate where I ended up? How do we, again, bring them into this? There are situations where they're going to be really important. So for example, if a patient is in a blood cell,

[27:00] moves around for a job or for other reasons and they go to different doctors in different health systems who might be using different laboratories that are run on different platforms using different reagents, you can't just take all of those numbers and compare them or throw them into one data and plot them out and say oh my disease is getting better or worse.

[27:20] who has to know that the context of those variations and nuances to help interpret that is often important. But the patient is often the only one that has that complete set or has access to that complete set of records. You know, even if it's something like hemoglobin A1, CDC, how their diabetes is doing, that's one way to measure over time.

[27:40] Another one that's perhaps a situation that's more complex, and maybe some of you went to the really terrific extra lunchtime session yesterday on pharmacogenomics is a good example, where yes, you can get a pharmacogenomic test because I'm thinking of prescribing an antidepressant for you and I get a pharmacogenomic test.

[28:00] genomic test to see how your liver might metabolize SSRIs and it might help me pick the right one. Terrific. That's clinically helpful information. Probably more valuable is three years from now when you're also on a cardiac medication and some other type of medicine and you're seeing a different doctor in a different state.

[28:20] who doesn't have the EMR access. How could we through either you as the empowered consumer patient or some other mechanism, maybe it's the pharmacy, the PBM, the health plan, the doctor, somebody, the cloud, maybe the lab that performed it, needs to persist that information, add new information,

[28:40] from new variants that we find. And then another physician who's gonna order a prescription for you, at that point, or maybe at the pharmacy, flags and says, wait a minute, Clif had a PGX test three years ago that suggests they're an ultra metabolizer of this. This may not be the right medication or at the right dose.

[29:00] That is, through space and time and different clinicians, a problem that we need to solve. And that's why, again, getting away from this sort of one test at one point in time system that we have now to figuring out how to organize the information, deliver the insights, and get fairly paid for this continuum of

[29:20] of data persistence and reanalysis. So how do we build that system? How do we take that, and let's assume that we have the given of the empowered consumer who is granting that approval, because that's key. But how do we build that? What sort of systems do we need? Obviously, computer-assisted knowledge, AI, anything like that in terms of training.

[29:40] meaning, and also some sort of coordinated aspect among these providers to be able to make that history clear. Right. And I'm assuming we're not allowing for a magic wand to reboot the whole system. Yes. Okay. Yes. Okay. In that case, I think the fits and starts that you see around the country,

[30:00] tend to get at that tend to be the integrated delivery networks, whether it be a geisinger, a Kaiser, whatever, where they're the payer, the provider. If you're living in central PA for your whole life and you get all of your health care from a geisinger, they might do a terrific job of being able to do exactly what you just said. But in today's world where we bounce around, we want to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to get to the point where we're going to be able to be the point where we're going to be able to be the point where we're going to be able to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're going to be the point where we're

[30:20] want choices, we want to figure out any given doctor we want to go to at any time and we are more mobile, it's just harder to make all of that come together unless you are truly empowered enough to want to drive that yourself. But unfortunately, everyone in this room is sophisticated and probably would have that motivation. The average American probably

[30:40] or the average person probably is not in a position to do that. Is anyone building that though? Is anyone building that kind of system that allows us to integrate the history of those, you know, the history of the biological diseases? I would have asked Amy Abernathy that at the end of yesterday because if any one of you

[31:00] Anybody has the IT and the money to do it? It's probably Google. Very up, yeah. Yeah. And every one of us uses them every day. But I think we're a long time from that truly perfect system that you're describing because there are just so many difficult, interconnected pieces that have to come together. Yeah. Where do you see...

[31:20] Where do you see the next step in your industry? Where do you see you going in terms of, not the sort of modest little incremental step, which I know all of this is built on incremental steps, which is important and we shouldn't dismiss that. I have a tendency of dismissing that for the big leaps. But where do you see the next leap?

[31:40] I'll say not just because we're sitting at the personalized medicine conference, but because it's probably the right thing of going again from this sort of one doctor, one patient, one lab test right now situation to looking at an individual patient longitudinally over time for all of their conditions to then one thing we're having

[32:00] conversations with health plans around is what if we take, you know, Dr. Leaf and all of your patients and we sort of profile you in terms of what are your test ordering habits. For a particular test, what's the likelihood that it's going to be abnormal, meaning your pre-test probability and diagnostic acumen was pretty

[32:20] good, you were thinking of the right things in the differential diagnosis of what to order for a given patient. Could we use that to not say you're a good doctor or a bad doctor necessarily, but maybe how complex and how could we risk adjust your patients if we're going to get into a value-based care contract? How could we maybe give you some better provider education?

[32:40] around how to deal with the onslaught of new information, new tests, new opportunities for you to take care of with any given patient every year. How do we deliver that in a way through some clinical decision support mechanism so that you can make better decisions for your patients? And then how can we look over-populatively?

[33:00] relations and learn more. So we're not just suggesting for any given condition that every patient, to take the common example, every woman who turns 50 should get a mammogram this year. That's terrific. And it's easy to implement because it's so simple to say. But it could be that in a future where a lot

[33:20] more risk-stratified than just that. Because doctors don't want to practice cookbook medicine in reality, they want to be able to refine and stratify the risk of their patient's panel and then have more personalized interventions for them, which is going to start with better diagnostics up front and then have

[33:40] an ever-increasing tool belt of more specific medications and other procedures that they can do once they get a better diagnosis. Is there any coordinated effort to work with, say, Apple Watch and Fitbits and other kind of diagnostic wearable devices, things like that? Is there any coordination between any of the tests that you've been doing?

[34:00] do. We and many others have those conversations all the time and there are all sorts of different programs sometimes on behalf of employers or with health plans in particular to put some of those different pieces of data together on behalf of any given population. I'm not aware of sort of a coordinated national effort or

[34:20] state level effort to bring those different disparate players together. But a lot of them are happening organically in the industry. You have such a global perspective. I mean, you've seen this from the insurance side part of your career, obviously as one of the largest providers in the diagnostic space.

[34:40] You've had lots of different views from various career points on your resume. Where do you see the areas where we're not hearing each other? You know, that one side is saying something to the other. And you've heard it from both sides. I can see both sides. But like, God, I wish that was you.

[35:00] they could just hear each other. Yeah. A couple of areas would be, one, again, back to this idea that physicians are trying so hard, they wake up every day wanting to do the right thing and practice really high-quality health care. But they just can't possibly keep up with the data coming at them, and they don't have enough time to actually

[35:20] Think about an individual patient in front of them, do extra research. I mean, we talked about the difference between doctors and lawyers as an example, where you'll pay a lawyer to spend 100 or 1,000 hours researching one provision of one contract before they put it in front of you to sign.

[35:40] doctor is going to get seven minutes to decide what your cancer treatment is going to be. And there's a whole host of different things that go into that, and there's no magic bullet for that either because we're not going to be able to tenfold the number of physicians we have overnight and have them expect to make the same amount of income that they do right now.

[36:00] being a lawyer to a doctor. No, it's much better work on the healthcare side. You wake up and feel better about the work that you do every day. But given the regulatory and reimbursement challenges that we have, believe me, I use my law school education every single day. I'll bet. Yeah. All right, so we've got some time for some questions.

[36:20] about 10 minutes. So anybody who wants to have a question, please stand up to the mic. And then, oh, we've got Edward. Wait, is Ed allowed to ask a question? He runs the place. You're the lawyer, so you tell us.

[36:40] takeaways from this conference is science has never been more exciting. But as we heard from Dr. Yabara just a moment ago, there's a lot of uncertainty in the pharmaceutical industry which is challenging. We know in the diagnostic industry the uncertainty around the LDTs has been an albatross

[37:00] around the field for the two decades PMC has been in existence. And I wonder, Brian, if you could comment a little bit about how you see the future of LTT regulation or regulation generally in the diagnostic industry. Sure. Yep. Thank you, Ed. I mean, you know, nobody would question the idea

[37:20] We want to make sure and assure patient safety and accuracy and consistency of tests and other products on the market. I think part of the issue is laboratory developed tests are not a product that can be subject to sort of GMP practices. It's more of a service that has pre-analytic, analytic, post-analytic services lab scientists are constantly iterating on them.

[37:40] We lock something in because of the process. It is going to delay the ability to then do other iterations as we learn about new genetic mutations and other types of things. So it's going to slow down the process. We've already seen some of the startups that we invest in through our venture fund that we talk to all the time quite consistently.

[38:00] concerned, not necessarily immediately, but if implemented, their ability to actually have the time and capital to go through the process. And it's not just conjecture to say we think it's going to slow down innovation and process. All we need to do is look across the pond at the implementation of the IVDR regulations in the European Union, where we already know for sure.

[38:20] sure from some of our customers it has slowed down some clinical trials because assays that have to get CE marked are sort of in queue and bottlenecked from going through the process and we can anticipate a similar thing here. So we just want to make sure that it's rational, it's risk-based. We certainly would prefer it to be a legislative response like

[38:40] was in the valid act proposal from before. And so hopefully, as Scott Gottlieb said yesterday, hopefully we can winnow it down a little bit. Those of you in the audience and your organizations, you have until Monday to submit your comments to the notice of proposed rulemaking so that we can hopefully get to a little bit more.

[39:00] predictable and certain and streamlined, less administratively burdened process of making sure that we're doing really good science for the public. Frankly, I'm as concerned about some of the other regulatory issues as that. We still have the PAMA around our necks, and we've got to get clarity on that.

[39:20] It's become almost the same silliness as the SGR, the Sustainable Growth Rate, what used to be, you know, colloquially called the Doc Fix from years ago, of sort of waiting how much are they going to cut or reimbursement for lab tests next year. So we need some clarity on that and the SALSA Act would be a way to do that. But frankly, even the, I'll say the more insidious

[39:40] less public ways that are impacting the diagnostic industry are having a real negative impact on us. So for example, the NCCI edits are the national correct coding Institute. The CMS sometimes will make an a coding edit in the system to not cover diagnostic tests without going any due process.

[40:00] or the coverage process itself. So no notice and comment period. It'll just happen. And then all of the labs will start to get a certain code denied because of an edit that went into place without the foresight to plan for that and adjust our businesses. So and then just the regular coverage process itself is problematic. I mentioned earlier, the 6 max don't always

[40:20] have the same coverage decision or unit pricing, so that creates difficulty in the industry. So I think there are a lot of regulatory interventions, the FDA-LDT proposal being the most current one of just back to the theme that we heard a few times yesterday, clarity and predictability is going to allow us to invest more in the industry.

[40:40] the R&D to deliver more innovation that we know we all need and to then work better with our biopharma partners to deliver the therapies to the patients who deserve them down the road. Right. Well, that's wild. Please identify. Ed didn't identify himself, but we'll forgive him for that. Everybody knows Ed. Hi, I'm Betsy O'Donnell from the Dana-Farber Cancer Institute.

[41:00] So I wanted to first of all thank you for a very interesting discussion, both of you. But go back to your last comment where you're talking about the burden of physicians, so someone who is a practicing physician. It's very exciting to be here at the interface of industry and medicine. But you talked about something really important and that is really the scarcity of time for providers. And so when we think about these technologies and personalized medicine,

[41:20] and then we'll hear about MSED in just a few moments. Really a big focus, both an observation and a question for you is how do you bring in new complicated systems without increasing the burden, particularly on primary care, which is an overburdened industry as it is, and physicians don't have enough time. So anything you're developing or thinking about, I would argue

[41:40] that you have to, the first thing has to do is how is this making it easier for physicians so that you get uptake and particularly get uptake in the areas which most need it which are in communities and in practices that are either remote or underserved. Yeah, I couldn't agree more. That was terrific. Thank you for what you do at Dana-Farber and for that question. I'm going to brag for just a second. So I practiced for about a day.

[42:00] decade at Duke, and a lot of you have heard the kind of it kind of gets almost sometimes silly in the media that primary care physicians would have to practice 27 hours a day in order to just implement the USPSTF preventive services guidelines. And that was a couple of friends in the department where I practiced at Duke who did the original work on that. And it's almost

[42:20] kind of become silly, but it proves your point. There's no possible way to actually get all of this done within the confines of the current system, instruction, reimbursement that we have right now. So I can't fix that for you, but one thing that I do promise that we're trying to do, even though we're constantly trying to, you know, we launch maybe a hundred

[42:40] new tests a year. We're trying to educate, we're trying to get the collateral out there to explain when to use test A versus test B and then what might be potentially helpful with it. We want it to be as much as possible in the workflow of the clinicians so you're not logging into other places, you know, having to do other types of things. That's difficult. We've got to.

[43:00] integrate with Epic and Cerner and the 600 other EMRs out there to try to present it in a simple way to be able to do that. But again, as Cliff mentioned earlier, bringing maybe historical lab values and automatically plotting them serially so you can quickly visually see the history of somebody's lab tests rather than flipping back.

[43:20] 500 pages through a paper chart or 80 tabs over inside Epic or Cerner to try to find a piece of information that you might be professionally liable for is going to be critical. I don't think there's any way we can expect humans to do that, and I think we've got to figure out how to not scare clinicians by AI and other

[43:40] digital tools that are maybe less than AI helping, collate a lot of that information, sift through all the noise to figure out what's going to be clinically relevant for whatever you're seeing them for their chief complaint today might be, and then serve it up in a way that's augmenting your clinical decision-making without frustrating and burning you out. That is easy for me to say an ungodly, hard, and

[44:00] and expensive to build, but we're going to have to do it. And again, maybe part B to my answer to Ed would be instead of making every lab go back and revalidate LDTs that we've had on our menu for 20 years, perhaps the limited FDA resources could be diverted to figuring out a rubric to.

[44:20] regulate and or give us guardrails in a framework for the algorithms to do some of these things that are gonna help you do your job more easily, and then build the clinical decision support and AI mechanisms to collate all of this disparate information together to help you make a better decision for your patient. Sounds great. Thank you.

[44:40] you. Hi, I'm Ital Rasmusan from Octave Bioscience. So first of all, thank you for this insightful future looking and I wanted to ask you about something you mentioned at the beginning about lab core and the multi-biome marker.

[45:00] for neurodegenerative diseases. So as you know, neurology, as we all think about neurology as the new oncology, how do you see the future of personalized medicine in neurodegenerative diseases, but also how LabCorp actually working on panels like this.

[45:20] What's the strategy from reimbursement, from adoption of providers overall? Oh, thank you. That's a very broad question. I'll try to just summarize it a little bit. I think you're exactly right. Epidemiologically, neurodegenerative disease is unbelievably important. We've made

[45:40] incredible advances in oncology and autoimmune diseases over the past couple of years, but there are tens or hundreds of millions of people around the world that we expect to be diagnosed with Alzheimer's disease and other neurodegenerative diseases over the next 10, 20, 30 years. It could bankrupt all of the health care systems of the world if we don't get on

[46:00] on top of it. There has been so much terrific innovation and research going into different pharmaceutical interventions to either slow down the progression of or treat. Alzheimer's disease is an easy one to pick on. There have been a lot that haven't made it, but luckily now we have a couple on the market that are. I think there are quite a few.

[46:20] others in the pipeline that are going to be very promising going forward. So I think we're doing both individual biomarkers and as I mentioned earlier, if we can show some correlation and concordance between plasma biomarkers or blood-based biomarkers and CSF-based biomarkers or PET scan imaging.

[46:40] of amyloid plaques, tau tangles, et cetera. That is gonna be very helpful for both identifying patients for the clinical trials to help us get better medications down the road, as well as treat them with the medications that do come on market. As we get more medications than as we learn a whole lot more about the concordance of the blood-based biomarkers, I'm hoping that we can get more medications.

[47:00] And we will eventually get to rather a yes, no, yes, I think you might have Alzheimer's disease or no, you probably don't, to a whole lot more subtyping to where it may be matched to the different medications. Maybe yours is more on the amyloid side, someone else is more on the phosphorylated tau side.

[47:20] and different medications might target those different subtypes and then it could progress from there. I think many, many years of research, we would love to partner with you on making sure that clinicians can get access to easy blood-based biomarkers to identify patients for clinical trials and then eventually for treatment with the right medications. Very promising.

[47:40] Thank you, Brian, for giving up the safety of the university life. That's right. Thank you, Clint. I appreciate it. Thank you, everyone. Thank you. Alright, so we have about a 30-minute break. We'll be back in half an hour.

[48:00] Thank you.