Episode 53: Innovations in Personalized Cancer Care

Patient From Hell (00:03.274)
Hi everyone. This is Samira Daswani, the host of the podcast, The Patient From Hell. So today I actually have two guests with us who work for the same company. And I think are building something pretty remarkable in the cancer space. And with these two entrepreneurs who have done an enormous amount of work in this space, I am hoping that we can get into what it means to create innovation, create disruption.

in the cancer diagnostic space, in the cancer treatment space, with both Dennis and Cliff here. So with that, Dennis and Cliff, thank you for joining us. All right, so I'm going to have you guys do a little bit of background and storytelling. So maybe Cliff, we can start with you. One thing that I realized when I was looking at your bio, which in retrospect, I probably should have realized about a year ago, which I didn't, is that our undergrad and grad experiences are the same institutions.

Dennis Watson (00:40.47)
Thank you for having us.

Cliff Reid (00:40.618)
Our pleasure.

Patient From Hell (01:01.586)
So you do did undergrad at MIT and then graduate education at Stanford, which is the same as me. Very, very different departments in the two institutions. But as a MIT alum, I would love to understand what MIT was when you went to school, because that institution has changed so much even since I graduated. So maybe we can start there.

Cliff Reid (01:26.234)
Sure, and good to be here. When I was at MIT, and I shudder to say it was in the 70s, MIT was a technical school, pure and simple, and deeply technical. It's competitive schools where it's competed with students for, it's really Caltech, Georgia Tech, places like that. And then with the information revolution, and really under the leadership of Chuck Vest, who's president in the 90s, it began to change. And

And MIT took a really forward-thinking perspective that what they were training was not scientists and engineers. What they were training was leaders with backgrounds in science and engineering. And the fundamental interaction between the Institute and their students changed. And it was most clearly demonstrated by who they competed with students. And it changed from Caltech and Georgia Tech to Harvard, Stanford, Princeton, and Yale.

And to this day, that is how MIT benchmarks its success around attracting students among those five institutions. So when I was there, it was geek central. That's really what it was all about. And today, the students are unbelievably different. They're so broad. They have different interests. They travel internationally. They do all the stuff that MIT never encouraged my class to do. I will say, though, when I was a student there, the average SAT score, math and verbal, was 800, 800.

Dennis Watson (02:35.086)
Thank you.

Cliff Reid (02:51.614)
And today at MIT, things are very different. The average math and verbal score is 800, 800. So it remains one of the great academic institutions in the world, but it's looking for a lot more now in its students than just brilliant scientists and engineers, it's looking for leadership.

Patient From Hell (03:08.23)
So Cliff, the only thing that I will maybe contest you on that one is Geek Central. At least when I went to school, it was still Geek Central. I don't know if you guys had the nerd crossing signs. Do you know what I'm talking about?

Cliff Reid (03:22.19)
Yes.

Patient From Hell (03:23.602)
So that was still there. That was still held up with pride. And the only thing, the only thing that mattered at MIT was your IQ and what you built. That's it. Like I just remember the social hierarchy being very much driven by IQ. Grades, by the way, did not matter, at least when I went to school. I don't know if that was true for you. Yeah. Yeah, it just didn't matter. Like it was irrelevant what you scored in an exam. But what was relevant was what you built in your dorm at night.

Cliff Reid (03:33.301)
Yeah.

Cliff Reid (03:42.77)
Yeah, not much, yeah, no.

Patient From Hell (03:53.042)
How nerdy was it? So the nerd crossing and the geek centralness, at least for me, was very much what made MIT MIT.

Cliff Reid (04:02.738)
Yeah, and MIT has a long tradition of hacks, of pranks that the kids pull. And that is maintained as well. Although when I was there, we were allowed to do a lot of very dangerous hacking. It maybe wasn't such a good thing. And I think that's gotten a little bit channeled into more constructive activities in the stuff that we were doing.

Patient From Hell (04:25.527)
Okay, so you can drop that and not give me an example. What was a dangerous hack when you were there?

Cliff Reid (04:30.046)
You know, we hacked the Harvard Yale game at one point by putting explosives in the field and spelling out MIT in the field. And actually the Cambridge police caught us and the hack didn't come off. But those kinds of things are now frowned upon. At the time, Dean for Student Affairs was very supportive and thought it was a wonderful hack. Now you don't get to do that stuff anymore.

Patient From Hell (04:58.542)
Well, okay, in that sense, yes. I don't remember our hacks being quite as dramatic. Although we had in our year, you know the little army men from Toy Story? And then as for context, all these hacks, at least when I was in school, happened just before finals week, where all of the students are supposedly studying, but in actuality, there's this campus-wide hack being pulled off that all underground, no one's supposed to know about it, but everyone sorta kinda knows what's coming.

Cliff Reid (05:03.888)
Yeah.

Patient From Hell (05:27.422)
And a lot of people get involved in it. But one of the years that we had, the entire campus was covered in little tiny army men, the full campus. I have no idea how these people got access to so many little toy story army men. And there was a portrait of the president of MIT that was made from these little army men. So it's stuff like that just makes MIT nerd central. The only thing that has not changed.

Dennis Watson (05:49.09)
Ha.

Patient From Hell (05:55.786)
Uh, so with that, Dennis, I know we haven't put you into the conversation yet, but I would love for you to jump in here and talk to us about, when, when I look at the work you've done, Dennis, I am so incredibly amazed at how much you have helped move the field forward for oncology. So as way of background, if you don't mind talking to us about what you've done, how you got into it, why oncology, why do you stay in it? Uh, that would be awesome.

Dennis Watson (06:00.266)
Yeah.

Dennis Watson (06:24.382)
Yeah, no, happy to talk about that. So I was a bit of a nerd as well. I didn't go to MIT, but I always was just very deeply interested in the sciences. And I've joked with Cliff before. I think I took probably four physics classes in undergrad as electives just because I thought physics was fun. So I was a bit of a nerd in that way. And

Patient From Hell (06:28.298)
I'll see you at the end.

Dennis Watson (06:52.938)
You know, in my early days, I got into sales pretty quickly out of college and was dabbled with whether or not I was going to go to medical school. And, you know, in the end, I found an opportunity in medical sales and actually in vaccines in the really early days, selling vaccines and do pediatric care practices.

And that was really sort of my entrance into the medical sales industry. But I learned pretty quickly in that environment that I'm very process oriented. I'm very strategically driven. And I like to build things and create things and be creative. And, you know, in fact, I had a minor in fine arts and

in my undergrad. So I had sort of an unusual mix of a heavy science and, you know, the sort of creative artistic background. And so I started looking pretty early in my early medical sales career for opportunities to get into things that were newer, that were cutting edge, that impacted the patient community in a different way. And I always sort of in a lot of ways saw

the cancer environment and oncology as kind of the pinnacle of that. And, you know, right place at the right time. I, you know, I often tell my kids that success is a function of preparation and luck. You know, it's being prepared when that opportunity arises, right, and being able to grab it. And so the opportunity to join Myriad Genetics came up

in the really early days with that organization doing, you know, doing genetic testing and breast cancer and other types of cancer and the beginning of that organization in a lot of respects. And so I covered a couple of states. Most of the physicians I was talking to had never touched genetic testing. You know, I mean, I talked to patients today that are

Dennis Watson (09:14.274)
that are struggling with the concept of what's genetic versus genomic versus this versus that. And what's funny is 15 years ago, it was the commercial reps in the field that were really educating the oncologists on those differences because it was a very new science to them. And so it was a little bit of luck and being in the right place. And I got in with Myriad and had an opportunity in those early days to really introduce

that kind of testing to the care environment and you quickly realize the impact that could really have. And there's a very different experience in selling a commercial product to a customer, a physician, whomever, that is a new novel approach that has an impact on their care, that has an impact on how they manage their practices, et cetera, you know, versus

selling them the third version of something that they've been doing for a long time, right? It's just, it's a very different type of challenge.

Patient From Hell (10:19.838)
Can we actually dive into Myriad if you don't mind? And Cliff, I'd love to pull you into this too, because if I look at both of your backgrounds, the world of genomics, genetics, is something that both of you kind of entered, probably similar timing, if I'm not mistaken, but very different kind of entry points into it. But I'd love for you guys to talk about this, right? So let's, maybe let's start with a couple of definitions, if you don't mind. And Dennis, I'm just gonna tag on you because you...

Genetics versus genomics. Can you give us a quick, quick spiel and what's the difference? And if a patient is getting into it today, because there's also germline testing, somatic testing, there's a whole bunch of nuances that comes up very quickly, it becomes relevant. So if you don't mind just giving us a kind of one-on-one definitional foundation and then we can get into Myriad versus Complete Genomics.

Dennis Watson (11:11.986)
Yeah, so genetics, the way that I always sort of positioned it for patients especially is, if I hand you a book, the genetics of the book are the typed letters. It's the actual letters on the page. The genomics of the book is what those letters in combination into words and other things actually mean.

And so, you know, that's really kind of the difference. The genetics writes the story, but the genomics actually create the action. And, you know, and I think in the critical care environment that the patient is facing, that's an important sort of differentiation to build. Your inherent genetics can set the future of what your story is going to be. Or what it might be.

likely be, but the genomics is how those things really present themselves. It's a tumor's ability to enter the bloodstream and survive against the immune system. And it's these measurable things. And it's really this toolbox that a tumor either has or doesn't have. And genomics measures more of those, you know, measures more of those abilities

of the cancer. You know, the other big thing that tends to be common, and we do genetic testing on cancer cells of course as well. But you know, especially when I got started with Myriad in the early days, genetics was really about your, you know, born in mutations. Do you have a higher likelihood of this because of what you were born with, where genomics was more of a study of

the cancer cells themselves and what their opportunities and abilities to spread and et cetera, you know, looked like.

Patient From Hell (13:12.862)
Hmm. Go ahead, Cliff. You want to add something there? No? What about germline versus somatic?

Cliff Reid (13:17.258)
Nope, perfect.

Dennis Watson (13:23.094)
Yeah, so germline basically means this is something you were born with. Somatic is existing within the tumor. So we talk about BRCA. That's one that kind of everybody knows. The easiest way to describe the BRCA gene and the reason it was named BRCA is because it stands for the breast cancer gene. And the easiest way to describe that is that's really a spell checker.

A cell division occurs, that BRCA gene is sort of going along that sequence and it's checking to make sure that everything is spelled correctly and it will correct it or end it if it's not. Sometimes the spell checker is broken and that's when cancer can occur, right? That's something someone is born with. If you're born with a BRCA mutation, then your likelihood of developing cancer is higher because

you don't have a backup spell checker anymore. One of your spell checkers is already broken, right? Where somatic, on the other hand, is a mutation that occurs in the tumor. So it doesn't exist in every cell in your body, but it exists in the cells that exist in that tumor. And we talk a lot about EGFR mutations in lung cancer, for example. And so...

You know, you can't test any cell in a lung cancer patient's body and see whether or not they're EGFR positive. You can test their cancer cells to determine whether or not they're EGFR positive. And then that becomes now a target for the drugs to hit.

Patient From Hell (15:00.286)
Hmm. Thank you for that. I super appreciate that. So with that backdrop, I'd love to pull you Cliff into the conversation with you and at the space too. So how did you enter? Why did you enter? What made you sort of help build Complete Genomics?

Cliff Reid (15:19.786)
I'm sorry, say that again, I didn't hear you.

Patient From Hell (15:21.742)
Oh, what made you enter the space of genomics? Because you entered.

Cliff Reid (15:24.79)
Genomics itself. Well, you know, I'm a serial entrepreneur. I started my career in high tech and spent, you know, most of two decades doing business productivity software. And then, you know, met some amazing people at MIT. Whenever I'm starting a new company, I go back and walk the halls at MIT and find something cool and new to do. I always say, I made a wrong turn. I was going to the computer science department and I turned into biology by mistake. And I've always hated biology. I'm a physicist by training and a mathematician.

And the biologist, my view was they didn't really know much about what they were talking about. And I ran into DNA and DNA is the merge of biology and physics. DNA is digital of all things. It's like a computer. And so I fell in love with DNA and said, my goodness, everything I've learned over the first part of my career as a physicist and mathematician can now be applied to biology and can be applied to human health. And so in 2005, I started a DNA sequencing company called Complete Genomics,

to improve DNA sequencing. So the digital form of the human genome could be used in medicine, used in human health. And I've been doing that ever since.

Patient From Hell (16:36.378)
Um, okay. So I would love for you to talk a bit more about what Complete Genomics did, visa vie what Myriad did. It's actually, I think for people in the industry, it's very well understood. But from a patient perspective, it's actually really hard to differentiate the purposes of the two organizations when you're looking at it from outside in. So if you guys don't mind, maybe I know Dennis, you gave a little bit about Myriad, but if you don't mind, Cliff, maybe a little bit more about DNA sequencing.

2005, why was that important? And we're sitting here in 2023 today, very, very different landscape. So I'd love for you to talk a bit more about back in 2005, why is why is what Complete Genomics is going after relevant and important to that to the space.

Cliff Reid (17:24.798)
Yeah, and I'll let Dennis speak to the applications. Because the difference between what I was doing at the time, what Dennis was doing at the time, was the difference between measurement tools, which is what I was doing, DNA sequencing, and then the application of those measurement tools to problems in human health. So what is DNA sequencing? DNA sequencing is just like a microscope for looking inside a cell and making a measurement.

of the DNA in the cell. And it can either be in a germline cell, the cells you're born with, or it can be in a somatic cell, the cells that develop DNA mutations during the course of your life. But without being able to see those mutations, you can't do much. There were previous generations of DNA sequencing that were called gel electrophoresis, that were very slow and very expensive and pretty much impossible to look at the whole human genome. What Complete Genomics was founded to do, and its name actually reflected this, was to sequence the complete genome

to really understand the whole human genome and understand all of the changes in the human genome that could affect human health and cancer genes. Cells were one kind of change, but there are a lot of other changes in the human genome that affect human health outside of cancer. So I always say Complete Genomics was sort of like a big microscope. It was a company just for measuring the genes, but what you actually did with those measurements happened downstream, happened with the researchers and the great academic institutions,

and then the commercial companies that began to figure out how to use measurements of genes to provide products to patients that would improve their health. Dennis?

Dennis Watson (19:01.258)
Yeah, and that's where the application piece comes in. So, you know, and again starting with Myriad I moved on to a company called Agendia after my time there and spent about a decade with that organization, led their commercial team for about five years, but you know in both environments it was about applying first genetics with Myriad and later genomics with Agendia and how that

applied in the clinical care environment. So, you know, with the genetic testing, if a patient has a specific mutation, their likelihood of something to happen changes. And so the physicians that are managing those patients can manage them differently. Now, actually, since I've left, there are actually some drugs that have been developed for those patients as well. But in the early days, it was really more about managing risk, doing things like prophylactic mastectomies.

Patient From Hell (19:50.942)
Hmm.

Dennis Watson (19:55.982)
The mom gets diagnosed with ovarian cancer and the awareness of the daughter changes in a pretty significant way. And in fact, to take a small sidebar, Samira you asked about what sort of got me into this space and what has kept me here. And it's been the ability to impact those patients in that

kind of a way. My mother-in-law unfortunately passed away from ovarian cancer at a pretty young age. I watched how that affected my wife and her little sister and that conversation with her gynecologic oncologist about BRCA testing at the time, which little to his chagrin I knew pretty well. And you know we had an intense conversation.

But it was still relatively new, and a lot of the doctors were coming around to it. But, you know, those applications of how you can use a diagnostic assay to change a patient's care in a really significant way is where genetics and genomics have made significant impact. And on a broader scale, diagnostics. You know, historically, diagnostics were really about,

diagnosing an upfront problem. Once you've been diagnosed with X disease, everything else becomes about the drugs and the surgeries and the radiation and all of this. But the last two decades have dramatically changed what tests can do to impact how, where, when, and why a specific disease should be treated. And it's been a lot of fun to be on the forefront of that.

Patient From Hell (21:50.37)
Thank you for sharing that because that actually, you helped me set up the next pivot I was going to go into, which is the role of a test to drive clinical decisions. Right? Because what you all are describing is, and to your point, a decade, 15 years ago, the genetic tests that patients were doing was really about managing risk. It was about prognosis, right? Like what's going to happen in my future? What is likely to happen in my future? And therefore, what can I do today to manage that risk?

it to a financial portfolio where you have in a portfolio, you essentially decide what your risk profile is and then you're making decisions to balance out your equity versus bonds versus etc. Right? You're looking at your 401k, hopefully, or your retirement funds and you're managing your risk. In healthcare, I actually don't think patients are taught to think of risk in quite the same way.

But these tests are providing you input to help you understand personal risk, family risk, because the mutations are talking about, it's not just about me as a patient, it's me as a patient and my family, because there are consequences sometimes. So I say all of that as a precursor to kind of where we are today, which is these tests are not just driving risk, but they are truly, in a lot of cases, helping you decide which treatment plan is most appropriate.

And the treatment plan can be a specific drug, specific type of chemotherapy, whether or not radiation is helpful or not helpful, whether or not which type of surgery, to your point, Dennis, is most beneficial to me now and in the future. So I'd love for you to talk a bit more about what is this test landscape looking like today in terms of driving true, true clinical decisions.

Cliff Reid (23:41.41)
Let me give you kind of the history of that from the Complete Genomics perspective and then moving into the Travera perspective, which is where Dennis and I are now. So when I founded Complete Genomic in 2005, it was right on the heels of Gleevec being FDA approved. And Gleevec is a drug for CML, for chronic viral load leukemia. And Gleevec is curative of leukemia. It's one of the most important and powerful...

cancer drugs in existence. And it is based purely on the DNA mutation. It's called the Philadelphia mutation of the patient. So when we started Complete Genome, we were like, wow, they found this mutation and they were able to build this drug Gleevec using these kind of terrible old slow bad DNA sequencing tools. And once we provide the research community, the drug development community with great, high quality, very fast, very inexpensive DNA sequencing tools, we're gonna have a Gleevec for every cancer.

Patient From Hell (24:36.659)
Yes.

Cliff Reid (24:36.878)
Gleevec for every cancer. That was the mantra of DNA sequencing in 2005. Well, it didn't happen. And it turned out that it's much more complicated than we thought. We always thought of cancer as a disease of the genome because it arises from DNA mutations. But it turns out it's just knowing the DNA won't get you to the answer. You need to know a lot more than the DNA, and in particular, you need to know a lot about proteins. And so we fast forward from

you know, 2005 to 2023, you know, 18 years later, the total number of cancer patients that actually benefit from genomic sequencing their cancer and then matching them to a drug, it's about 10%, which is incredibly disappointing compared to where we were in 2005, thinking we were gonna get, you know, pushing 100%. And for the 10%, it's fantastic. When DNA sequencing and genomic medicine works, it's absolutely terrific.

It just doesn't work enough of the time. And that was really the direct motivation for me to leave Complete Genomics and found Travera because it's those other 90% of the patients that we're going after now.

Patient From Hell (25:46.602)
Hmm. Can we go down that route? You opened the Travera bucket, so let's go into that. And let's maybe go back to, I think you said something earlier, which is a lot of your decisions in life are made by walking down the halls of MIT. So just for the people who have not had the experience of being on MIT's campus, there's something called the Infinite Corridor. And it's quite literally this corridor that just keeps going. And as you walk down this corridor on either side,

Dennis Watson (26:00.578)
Hmm

Patient From Hell (26:16.298)
there are different departments that show up. And for what it's worth, the departments have names, but no one on the campus calls it by name, it's by number. So it really is, you know, I was course 20, and if you're on campus, and if you're talking to someone who's not from MIT undergrad specifically, people look at you as you're kind of, I don't know, a little off because...

the entire conversation can happen in a sequence of numbers. What course are you, course 20, where are you heading, building, five, one, two, three, whatever, something insane. I ask this because you're walking down this, I had this image of you, Cliff, walking down this infinite corridor and then somehow finding Scott Manalis' lab, which is at the very other end, or at least I think it's still there, very, it's like you walk through the infinite corridor and then you have to end up in the Koch building and then...

you end up in Dr. Manalis' lab. And how did you stumble across Scott Manalis? Because I think that story is foundational, right?

Cliff Reid (27:19.49)
Well, yeah, I'm very engaged with MIT. As an alum, I participate in some of the alumni activities in a pretty significant way. And one of my participations is that I sit on the visiting committee of the Department of Biological Engineering at MIT. And the visiting committee is like the board of directors. And so I get to see everything cool that happens in biology at MIT. And that's a great thing.

That assignment came to me because I worked with the original founder of the Department of Biological Engineering, who was actually on my advisory board at Complete Genomics for a decade. His name is Doug Laufenberger, instrumental in creating the biological engineering powerhouse that MIT is today. So from my administrative position at MIT, I got to see everything going on all sides of the corridor in biology. The Koch Institute, which is where Scott Manalis' lab is, is actually beyond the infinite corridor.

But when I saw Scott's work, it's sort of like the light goes off because the challenge in doing therapy guidance for cancer patients is that not all patients have mutations. In fact, only about a quarter of cancer patients have any mutation that's at all related to the drugs in the industry. So we had to find something that wasn't mutation-based. And Scott Manalis had invented a new measurement tool. Once I say, what is DNA sequencing? It's a measurement tool.

got an invention, a new non-DNA based measurement tool that I thought could be applied to those other patients, all of those cancer patients that didn't have a mutation that could guide them to a therapy. And so that became the basis of Travera and that's what we're doing today.

Patient From Hell (28:51.764)
Mm-hmm.

Patient From Hell (29:00.162)
So here's a funny part of the story for the listeners out there. One of my undergrad research rotations was in Scott and Alice's lab on the very tool that Cliff is talking about. In the Koch building, so yes, it is not, the way I think about it is you have to end the infinite corridor, walk through, well, not in the winter, it's a grassy patch and end up in the Koch building. Or you go down the undergrad.

Cliff Reid (29:08.042)
Yeah, that's strange.

Patient From Hell (29:28.474)
underground little hallway structure, which is warmer, but also can be somewhat depressing, depending on how you look at it, and then end up in the Koch building. So I say all this as a prelude to, I would, I mean, I, of course, I'm familiar with the instrument you're talking about, Cliff, but at a high level, what does Scott's instrument do? Why is it?

Cliff Reid (29:49.726)
Yeah, so Scott Manalis and his lab team, all of them now work at Travera by the way, invented an instrument for weighing a single cell. That's all it does. It weighs single cells, but it weighs them with extraordinary accuracy, about 100 times better than any other instrument can weigh a single cell. And to kind of put it in context, this instrument can detect the change of the diameter of a single cell

of about five nanometers. And if you recall, the wavelength of visible light is about 500 nanometers. So this is like a hundredth, the hundredth of the wavelength of visible light. You'll never ever see this with a light microscope, just based on the laws of physics. But it's a very clever technology, and I won't drag you through the physics of it now, but it's a very reliable measurement of the weight of a single cell. And so...

just a basic measurement tool. And in the inimitable style of MIT, it was invented not for cancer, it was invented because it's cool to invent new measurement tools, right? And so they did all sorts of great cell biology with it, having nothing to do with cancer. And then fortunately, Scott had this great collaboration running with the Dana-Farber Cancer Institute. And they sort of asked and answered the question, gee, if we were to take a cancer drug and apply it to a live cancer cell in the lab, would the weight change?

Dennis Watson (30:49.678)
Thank you.

Cliff Reid (31:09.566)
And the reason I asked this question is because we all know that dead cells, cancer cells or any cells, actually, but dead cells weigh about half of what live cells weigh. They lose a lot of stuff in the process of dying. So but the question was, hey, if we have this super sensitive measurement tool now, can we apply a cancer drug to a cancer cell and make a measurement within a day within 24 hours,

to determine if this cell is beginning to die in response to the drug. And MIT and Dana Farber ran like 10 years of research on that project. And it turned out to have an extraordinary answer to that question. And the answer was, that appears to work not only for every cancer. It also appears to work for just about every cancer drug. So this is a measurement that can detect whether or not a cancer drug is going to kill a patient's

patients' cancer cells, independent of the mutations in the cell, independent of the proteomics of the cell, independent of anything. Because one thing that all cancer drugs share, they have all different complicated mechanisms of killing cells, but one thing they all share, they kill cells. And a cell can't die without changing its weight. So this ends up being sort of a universal biomarker.

Patient From Hell (32:34.302)
Yes.

Cliff Reid (32:34.466)
a method of detecting whether or not a cancer drug is gonna kill a cancer cell from all drugs and all cancers. And that's the basis of Travera.

Patient From Hell (32:45.162)
Okay, so now let's go, Dennis, I'm gonna pull you into this and I wanna go back to something you said about Myriad Genetics back in the early 2000s, which is the sales and commercial teams of companies are teaching clinicians about new innovations.

And a lot of times, the sales and commercial teams are tasked with education. Because a lot of times, you have innovations like MIT, not MIT, like Travera coming out of institutions like MIT, that are so cutting edge and so far, far ahead of clinical practice today, that there is a lag period between what's happening at a Travera, what patients and clinicians have access to today,

Dennis Watson (33:18.83)
Mm-hmm.

Dennis Watson (33:28.974)
Thank you.

Patient From Hell (33:33.946)
and how someone might be able to take advantage of the new innovations, right? So if you don't mind talking a little bit about, and I'm gonna specifically say this, clinical workflow for Travera, and why in the world clinicians are, well, I think you're allowed to change your clinical workforce. I think you should talk about that a little bit.

Dennis Watson (33:53.386)
Yeah, yeah, no. So what's interesting on a little bit of a broader scale, Samira, is that the way that I have found success in diagnostics in the last 15 years or so and the organizations that I've been with have found success is we get really deeply focused on the process and the process integration. You have to establish the utility

of the product, but then you have to integrate it into that process, into that workflow, into that clinical care environment, and you have to do it in a way that it is as seamless and as smooth as possible because these doctors are busy. And these doctors are so busy, in fact, that these, you know, the front line sort of sales

organizations of these different companies, whether it's a startup or an established product, they're often one of the more valuable tools that the doctors have to stay abreast of the things that are going on. There are so many innovations and so many new drugs and new studies and all of these different things coming out all the time that your average community

based oncologist who is seeing 30 patients a day with 25 different disease types. And that's not even to begin the discussion of how different management of a newly diagnosed early stage breast cancer patient is compared to a patient with late stage leukemia. I mean, these are completely different diseases. And

and are treated and managed and all of that differently. And so it's really challenging. I mean, it's impossible really for any one physician to keep up on all of those different things. And so that becomes a lot of the role of the sales team and the commercial side of the companies is to keep the physicians aware of these things that are sort of happening and changing. And so, you know, the value that

Dennis Watson (36:14.762)
that Travera specifically has brought and the opportunity for us to really change what's happening in the care environment today sort of goes back to what options are available to clinicians. And the main thing that the doctors are doing in treating especially advanced stage cancer is trying to decide what drug am I going to use in this patient

that's going to have the highest likelihood of killing the cancer cells that are in their body, right? And that question becomes exponentially more challenging with every additional line of therapy. And when you look at the average tumor type in the guidelines and you get past maybe second line treatment

Patient From Hell (36:48.098)
Mm-hmm.

Dennis Watson (37:11.526)
options, you end up in many cases with a list of 20 or 30 drugs that are oftentimes listed alphabetically. Because these are other drugs that we know work for this disease. They're not the best drugs that work for this disease because those are the first ones you tried. And which of these 25 or 30 drugs you should try next is a bit of an educated guess.

Patient From Hell (37:27.911)
Yes.

Dennis Watson (37:42.214)
It's an educated guess because if the patient has one of those mutations we were talking about earlier, then you can use that information to better target which of these drugs you might look at. But the reality is, as Cliff spoke to, genetics and genomics have only gotten us so far. And there's very few differences today for a patient with

late stage advanced disease who's looking at a third line of therapy, then there was 10 years ago or 15 years ago or 20 years ago. And so those patients really are, they're playing a bit of a guessing game. And it's wearing on the patient when you try a drug and it doesn't work. Not only is it wearing on them

physically, I right? I mean these drugs are not easy to take as you as you know from personal experience, but it you know, it breaks your body down it weakens you it weakens your immune system, it you know it weakens sort of everything about you. But it also it also is taxing emotionally and it gets harder and harder to keep trying the next thing and the next thing and the next thing and so the way that we're really

trying to use this tool that Cliff just described to impact care in a significant way is help physicians and patients take that list of, here's 20 drugs we haven't tried. Which of these drugs elicited the best response in this patient's actual cells? And maybe we're gonna try to start with that drug rather than.

guessing which of these 20 drugs are going to come next.

Patient From Hell (39:33.342)
There was something that I remember because we met at ASCOL and I can't remember which of you told me this, but you'll use the phrase resource of last resort.

And I'd love for you to talk a little bit about that in the context of the case study we're talking about, right? So patient is third line therapy, exploring essentially, and correct me if I'm wrong, but often off-label drugs, because at third line, you've basically exhausted a lot of the options that may be on label. So you may be exploring off-label medications. And can you talk a bit about that in the context of resources of last resort?

Dennis Watson (40:12.234)
Yeah, you know, it's when a patient gets to a place where you're looking for an extension of your life, you're looking for, you know, you start talking in days or weeks rather than years, you know, you start talking about your quality of life and you start, you know, you get to the place where these kinds of things become increasingly the focus

of your attention, this is a resource in that environment that can help you make a better next decision. Rather than trying a drug and seeing whether or not it's going to work for three or four or five or six weeks and getting that other scan and then getting that emotional hit and getting that physical hit, let's rule out the drugs that don't seem to work.

And so that is the place where this resource becomes incredibly valuable. And, and they're, you know, long-term, as we continue to build what we're doing in our data, there there's going to be earlier applications of this test and earlier stage disease, but this is where we are right now and it's incredibly valuable for the patients that are dealing with it and, you know, it's important to, to speak to that as well, because we're an incredibly deeply patient focused organization.

And we've done that with intentionality and we're going to continue to do that. And one of the things that led us to doing that is, you know, in important context for those that don't know, we've already talked about the sales reps going in and educating the physicians and keeping them up to speed on data, et cetera. Most of these organizations, the pharmaceutical companies, the diagnostics, the devices, whomever, they're really focused on a physician targeted model for promoting their products.

Educate the doctor, get the doctor to identify the right patients, et cetera. And that's the right model in the vast majority of scenarios. And it will be the right model for us. And we're doing, it is the right model for us. We're doing a lot of that. But we're also going to these patients that are in that place that they're looking for a resource of last resort And, you know, and these patients started to find us.

Dennis Watson (42:39.09)
And so we made a really intentional effort to then begin looking for them. And much of the education that we're doing as an organization is direct to those patients to let them know that this tool is here. It's developing, it's early, you know, but we're doing it through a lot of different great programs to get people's hands on it. And it's been an incredibly compelling way to do it because no one understands the value of deciding which of these next 20 drugs

best give me a shot, then the patient who's going through it.

Patient From Hell (43:16.854)
I mean, I definitely agree with that. And I think you know that about me. I mean, the whole premise behind everything we do is sort of similar in intentionality, right? Which is, I think in today's day and age, we're in a world where healthcare was not designed for the patient. It just was not. It wasn't, it was designed for the pharmaceutical companies, insurance companies, clinicians, hospital systems, and all for the right reasons.

But I do think we're sitting at a precipice where the patient of the future, at least I hope, is someone who has to not just have resource of last resort, but tools across the sort of spectrum of disease that enable that patient to make better decisions that are more in line with going back to kind of where we started, what their preferences are, how they want to live their life. What is their tolerance for risk?

How do they want to balance quality of life versus time remaining? And I do firmly believe that what you guys are doing sort of sits in that bucket of tools that patients need for the future. Um, and with that, I'm going to ask you guys one wrap up question, which is, it's all good. Uh, which is if you guys look out 10 years from today, outside of just Travera and you're painting a vision of the future,

Dennis Watson (44:25.9)
Oh yeah, sorry.

Patient From Hell (44:37.414)
What does that look like? Because both of you have seen this sort of beautiful evolution of diagnostics, of tests, of treatments through your many, many decades of work. So if you look out into the future, where are you seeing all of this go?

Cliff Reid (44:55.154)
Yeah, a comment on that. I think there is a growing interest in really personalized oncology. Again, back in 2000, that term was thrown about, and then people realized that genomics couldn't personalize anything. All genomics can do is run clinical trials of people that share a mutation. And that's still population oncology. And now there's a real move afoot. There have been a series of companies that have tried and failed

to create really personalized therapy guidance or therapy selection systems. But there's a growing interest, I think, on three dimensions now, three different paths. One path is the Travera path, which uses this fancy measurement tool at MIT that weighs cells. The second path is the path from companies that are building organoids out of patients' tumors in hopes that they can create kind of a replica.

of the tumor in the laboratory, and then test lactic drugs against that tumor and pick the drug that works for the patient. And the third path is the rise of many imaging companies that use artificial intelligence and machine learning in some form to look at images of patient cells, patient cancer cells, and try to deduce from the images and a training set, a set of outcomes previously measured, based on the image, which drug is going to work best for the patient.

I think Travera's technology is a very strong one among the three. It remains to be seen if the others work. The organoid-based systems have been run for decades as cell line systems, and they've never worked very well because cancer cells change when you put them in the lab. And trying to grow up a replica of a patient's tumor turns out to be really difficult. But the research goes on, and we all hope that they succeed beautifully. It's just a really hard problem.

The AI systems are too new. We don't know if they could possibly work or not. There's certainly a lot of data and images of cancer cells that hasn't been fully mined. So there's optimism in that field. But there's no existence proof yet that it works at all. So the only technology that has some validation data behind it so far is ours. But we hope that there are going to be multiple modalities, multiple different measurement approaches for picking the right

Cliff Reid (47:16.854)
drug for the right patient at the right time, because that's the whole purpose of personalized oncology and it's a purpose that hasn't been fully achieved yet.

Dennis Watson (47:26.038)
Yeah, and I would add on a broader scale, as I said earlier, there's an opportunity to pull this kind of a technology earlier and earlier and sort of in the care continuum. The reality is, in breast cancer, for example, there's an increasingly strong move towards neoadjuvant therapy, which is...

Patient From Hell (47:26.11)
Thank you for joining us.

Dennis Watson (47:52.438)
you know, treating a patient with a chemotherapy or a targeted drug prior to their surgery to remove it. And the idea is you shrink the tumor, you know, you've got a better surgical outcome, et cetera. But there's also data that's beginning to show that when a patient has a full response to that therapy in that neoadjuvant environment, they actually have better long-term outcomes. And, you know, but.

We also have a world where there are new drugs coming out every day. And, you know, there are over 300 drugs in, you know, available within the NCCN guidelines that are FDA cleared across tumor types as, you know, we just stand now. And that number is growing all the time. And so how do we increase the likelihood that patient in this neoadjuvant environment, let's say, gets the right drug

the first time, that's going to elicit that really robust response that's going to give them better outcomes long term. And that is an application that I think tools like this will be able to bring. The other thing I think the diagnostics in general is going to continue to change and you know the approach that we've spoken to that we've taken and working with physicians, but also with patients

and with those patients in partnership with their physicians, is doctors are becoming more and more comfortable with their patients bringing them information. And we live in an age of information that everything's available online, and AI tools are helping patients to find these things even better. But well-informed patients that are

doing the reading, doing the research, doing the understanding, and they're taking things to their doctors and they're bringing it to their doctors with thoughtful, well-intentioned ideas about what they might be able to do to impact their own life. We're in a world where physicians, especially younger physicians that are coming out with this kind of experience, are becoming increasingly comfortable with that kind of a patient interaction.

Dennis Watson (50:14.786)
And outside of the cancer space, another world where that's happening a lot is within patients with autoimmune diseases. And my wife has dealt with some of that. And those patients tend to be very well informed. And they go to doctors that are pulling other topics in and other approaches in. And so I think that's the other place we're going to continue to see evolution

is with patients driving more of their own care, with the doctor there to be the expert and the critic to say, hey, I understand, but this is why we shouldn't take that approach. And I think we're gonna continue to see a great deal of that.

Patient From Hell (51:00.574)
Thank you for sharing that. I absolutely love, love both those answers because one was incredibly technical. And the other one was incredibly human centered. So I appreciate you guys sharing kind of that fairly compelling vision of the future. And, uh, I personally, uh, absolutely hope that the vision you guys are describing continues to play out and happen because as a patient, I can tell you that, uh,

I would love to see a world in which as a patient, I truly feel actually informed. Because today it's a mishmash. You end up doing things and you're like, ah, I don't know, this is right or wrong. Like, maybe. It is an educated guess. And if we have a world in which the educated guess goes more and more towards a deterministic answer, I do think that is a world that I would love to see come true.

So with that, Cliff and Dennis, thank you for taking time and joining us today and sharing your incredible experiences and what you guys are building.

Cliff Reid (52:08.694)
You bet. Thank you for having us, Samira. It's been great.

Dennis Watson (52:10.894)
Thanks very much.