Switzerland, AI and Liquid Biopsies

[00:00:00] Dear listeners, welcome to Faces of Digital Health, a podcast about digital health and

[00:00:06] how healthcare systems around the world adopt technology with me, Tjasa Zajc.

[00:00:14] Today we're diving into biotech and the potential of AI and predictive modeling to

[00:00:19] understand an individual's immune system function and predict treatment response.

[00:00:26] Genomics and AI models to help predict responses to cancer treatments are still in very early

[00:00:32] stages.

[00:00:33] We dream about precision medicine and getting every answer we can for ourselves when we

[00:00:37] get sick.

[00:00:38] But if we look at genomics, only about 20% of human coding genes are well studied.

[00:00:45] The rest 80%, which is about 16,000 genes along with the proteins they make, all

[00:00:52] this is still largely a mystery.

[00:00:55] So in this episode you will hear a little bit more about the field of immune oncology,

[00:01:01] understanding the correlation between tumor development and immune system response, trends

[00:01:07] in cancer detection and prevention, especially liquid biopsies, which are tests for detecting

[00:01:14] tumors in blood samples.

[00:01:17] I spoke with Brian Hashemi, executive chairman and CEO of Novigenics, a Swiss-based biotech

[00:01:24] using AI and RNA sequence analysis to capture the cancer immunity cycle during the multistage

[00:01:32] disease progression and response to therapy.

[00:01:36] Enjoy the show, and if you haven't yet, make sure to check out our newsletter, which

[00:01:40] you can find at fodh.substack.com.

[00:01:48] Now let's dive in today's discussion.

[00:01:53] Brian, hi and thank you for joining me on Phases of Digital Health to discuss healthcare

[00:02:11] innovation and biotech in Switzerland and also the advancements in liquid biopsy.

[00:02:19] Three out of four highest valued European companies are from Switzerland.

[00:02:25] This is also the country where Novigenics, the company that you are running, is based

[00:02:32] in.

[00:02:33] The two strong companies in Switzerland are Roche and Novartis, and generally speaking

[00:02:39] biotech in Switzerland is very strong.

[00:02:42] So I'm really wondering what does that mean to you, to your company?

[00:02:47] How did this impact the whole company development and everything that you do?

[00:02:54] Yeah, that's a very good question.

[00:02:57] I actually grew up and had my professional career in the United States, and at some

[00:03:01] point I was looking to see where in the world would make sense to establish myself

[00:03:06] in order to nurture innovation that will make an impact on healthcare.

[00:03:10] And this was maybe 15 years ago, and Switzerland really came across as the very

[00:03:16] upcoming innovative place in terms of early technology innovation and testing and

[00:03:21] adoption.

[00:03:23] And that has proven to be the case.

[00:03:24] 15 years later, I can attest to that.

[00:03:27] It is a very conservative country.

[00:03:28] As you can imagine, there's a lot of emphasis on quality, on risk mitigation.

[00:03:34] It's very risk-averse culturally as a society.

[00:03:38] However, it's at same time at the leading edge of innovation in science and

[00:03:42] technology.

[00:03:43] So a number of innovation parks, whether it's here at the Beopold where we're

[00:03:47] based or at the EPL or at Tazulik in Zurich, there's quite a lot of innovation

[00:03:52] also within the hospital settings and a lot of spin-outs, a lot of programs to

[00:03:57] help companies get their orientation into the world and to see how their

[00:04:02] innovation can make an impact and make a positive impact on healthcare.

[00:04:07] That's one side of it.

[00:04:08] The other side of it is a very good market to test products because it is

[00:04:12] quite demanding.

[00:04:14] And so often companies, whether from all over Europe or from the United

[00:04:18] States will often use Sutilin as a test market to bring their products

[00:04:22] initially because it is a good self-paying market, meaning that there's

[00:04:26] a high value paid for technology that will make a big impact.

[00:04:31] And people like to try new things that are the latest technologies as long

[00:04:35] as they meet certain quality and a certain level of terms of approvals.

[00:04:42] And it is a wonderful country to also test things.

[00:04:45] It's multicultural for different languages, and therefore it's proven

[00:04:50] to be a phenomenal landscape.

[00:04:52] Myself, I work in this space of understanding of the immune system

[00:04:56] role in adaptation, particularly in space like at NASA.

[00:05:00] And then when I came across this opportunity, it became clear that we

[00:05:04] can use immune cells to better understand what is happening in cancer

[00:05:08] patients, starting from early detection of cancer before people even

[00:05:13] have symptoms.

[00:05:14] So before they even know that they have cancer developing in their

[00:05:17] body, all the way through predicting now response to therapies,

[00:05:22] being able to understand the immune profile of an individual and

[00:05:26] contextualize that within the therapeutic landscape and the

[00:05:30] journey of the patient and being able to help drive therapy innovation in

[00:05:35] order to improve patient outcomes.

[00:05:37] So that has proven to be phenomenal landscape in order to bring

[00:05:41] products out, test products and develop products.

[00:05:45] It's interesting that you mentioned the fact that Switzerland is

[00:05:48] multilingual as an advantage.

[00:05:50] I would perceive it as more of a hurdle that you actually need to

[00:05:54] take care of three or four languages from the get go.

[00:05:58] You're absolutely, it's a hurdle.

[00:05:59] So if you get through and you succeed here, you're going to succeed anywhere.

[00:06:03] And I think that's where people look at it.

[00:06:05] If we can bring a product into Switzerland and make it work, we learn

[00:06:09] a lot very quickly and then becomes easier when you go elsewhere.

[00:06:13] So that is, but then you have a good self-pay market so you can actually

[00:06:17] get paid for the technologies that you bring to the market.

[00:06:20] Interesting angle.

[00:06:21] I know that the French startups or French entrepreneurs would say that

[00:06:25] if you succeed in France, you can succeed anywhere just because of

[00:06:29] the bureaucracy part.

[00:06:30] So I guess every market has its own specificities in terms of what

[00:06:35] difficulties you can take as a stepping stone and an advantage because

[00:06:40] you already had to go through something very difficult.

[00:06:44] Absolutely.

[00:06:45] If we dig a bit further in what you started explaining, and that is the

[00:06:52] role and the insight we can draw from the immune system to either

[00:06:58] detect and detect diseases, analyze responses to treatments.

[00:07:03] Let's talk a bit more about that.

[00:07:06] So how much do we actually know already and can measure effectively

[00:07:11] the impact basically of the immune system?

[00:07:14] Yeah.

[00:07:14] What's actually measurable and tangible that we can use for these purposes?

[00:07:19] Excellent.

[00:07:20] We've made a lot of progress in the 20 years since the

[00:07:23] completion of the Human Genome Project.

[00:07:26] A lot of the focus had been on, I would say over the last 10, 12, in the

[00:07:31] first 10, 15 years of it has been on the tumor itself, mutations and

[00:07:37] methylation and evolution of the tumor now being able to be captured

[00:07:42] initially was in the tumor itself, but not being able to be

[00:07:45] captured in liquid biopsy.

[00:07:47] So there are a number of, for example, FDA approved tests and

[00:07:50] technologies that are with liquid biopsy able to pick up small

[00:07:54] signals from the tumor that inform us of what's happening to the

[00:07:58] tumor and tumor evolution.

[00:08:00] As time has gone, the industry has learned more and more the

[00:08:03] importance role of the immune function.

[00:08:06] And I think after COVID everybody understands the important RNA, the

[00:08:10] importance of the immune function and how it can really impact

[00:08:13] health and health outcomes.

[00:08:15] And that has been also the case in the field of oncology.

[00:08:18] So the whole field of immuno-oncology is all about activating and

[00:08:22] driving the immune system towards killing the cancer.

[00:08:25] So you have this balance between the evolution of cancer, its ability to

[00:08:30] evade the immune system and immune escape, and the immune system trying

[00:08:36] to keep up with the tumor and the cancer and being able to overcome

[00:08:41] the changes that it makes to itself and to chase it and to take control

[00:08:45] of it.

[00:08:46] And this is a very intricate balance.

[00:08:49] And when the immune system is ahead, the cancer is under control or it's

[00:08:52] shrinking.

[00:08:53] When the cancer gets ahead, it can evade the immune system or even it

[00:08:58] can come back as a new form of disease because it's constantly evolving

[00:09:02] as a disease.

[00:09:03] Liquid biopsies become extremely important in giving us insight into

[00:09:07] what's happening because with tumor biopsy, you're limited to the

[00:09:10] tumor site and as the cancer is evolving different parts of the body,

[00:09:14] you want to have a systemic view of how it's evolving.

[00:09:19] And so liquid biopsies in tumor mutational burden or tumor mutations

[00:09:24] is very mature.

[00:09:26] And what we're doing today, which is quite a new frontier that's

[00:09:30] opening up is being able to through liquid biopsy be able to look at

[00:09:34] the RNA in blood and whole blood.

[00:09:37] So in one tube of blood, let's say two mils of blood, you have

[00:09:40] two million circulating immune cells.

[00:09:43] Imagine what you can learn from two million cells.

[00:09:46] If you can get into their operating system and read what parts of the

[00:09:50] operating system are up or down regulated and be able to do that

[00:09:54] repeatedly, whether it's before the cancer, during the cancer, or after

[00:09:59] first treatment, after cycle certain cycles of treatment.

[00:10:03] And all of that married to AI to be able to identify signals

[00:10:08] that are predictive.

[00:10:09] So not only being able to understand immune features that are contributing

[00:10:14] to heterogeneity of the disease, right?

[00:10:16] So every cancer patient is as unique as the tumor that is

[00:10:20] grown in the patient.

[00:10:22] And what we need to understand is that uniqueness and how that

[00:10:25] actually contributes to their therapeutic journey.

[00:10:29] Having an understanding of the heterogeneity of the immune function

[00:10:31] using liquid biopsy, as well as the heterogeneity or evolution of the

[00:10:36] tumor is really a new opportunity to leverage large data sets, very

[00:10:42] precise data sets that you can generate today and marry that with

[00:10:47] AI to be able to get insights that were not possible before.

[00:10:50] So we're quite excited about closing that loop of what the tumor's

[00:10:54] doing, but also what the host immune system is doing and be able to

[00:10:58] follow that with the patient and be able to create value within the

[00:11:01] healthcare system and the patient therapeutic journey.

[00:11:04] Yeah, it's a completely different paradigm now in precision therapies

[00:11:08] where you're not just trying to target the tumor necessarily, but

[00:11:11] trying to just find who are, where do the influences come from and

[00:11:17] basically indirectly impact the way that the tumor is going to react.

[00:11:22] When we talk about liquid biopsies, one of the big ideas is that

[00:11:30] sometime in the future, this could be a standard of care for screening

[00:11:35] so that it would replace colonoscopies, for example, but we're not quite there yet.

[00:11:41] So colonoscopy is still the standard of care for early detection of colon cancer.

[00:11:46] How would you kind of comment or describe where the field is at the moment?

[00:11:52] As you said, a lot of progress has been made.

[00:11:54] This is also not something completely new, but we still don't know a lot

[00:12:00] of things.

[00:12:02] Yeah, colon cancer screening particularly is extremely important.

[00:12:06] Not only because of the high prevalence rate and the high mortality

[00:12:09] rate of the disease, but also younger and younger people are developing

[00:12:13] the disease in the United States.

[00:12:15] They've actually lowered the screening age and you have a lot of people

[00:12:18] in their thirties and forties that are developing colon cancer.

[00:12:21] And all of a sudden, by the time you have symptoms, it is a bit late.

[00:12:25] So you're in stage three or sometimes stage four where the therapeutic

[00:12:29] response is very low.

[00:12:30] So it's very important to pick up the disease at very early stages, ideally

[00:12:35] at the precancerous lesion advanced adenoma where it can easily be removed

[00:12:39] by colonoscopy and you actually block entering into the disease.

[00:12:44] But to do that, there are only two ways to do it, either with the stool

[00:12:47] test or with the liquid biopsy test.

[00:12:49] Stool tests have been around quite a long time, whether it's FIT or the

[00:12:53] most advanced stool test in the world is the Coligard by Exact

[00:12:56] Sciences in the United States.

[00:12:58] They already have the second version FDA approved, but the problem there

[00:13:02] is the compliance.

[00:13:03] So you have no compliance to colonoscopy and you have low compliance

[00:13:06] to the stool test, which has to be done every two years.

[00:13:10] And therefore most people are actually not screened.

[00:13:13] Most people in the world are not screened.

[00:13:14] The United States is trying to work hard to catch up, but it's with a

[00:13:18] lot of campaign and marketing and really pushing the stool test or

[00:13:22] colonoscopy into the big visibility and forcing people to do that.

[00:13:28] But ideal world is where you go and do your annual checkup, where you

[00:13:32] check your cholesterol.

[00:13:33] The doctor checks the box.

[00:13:35] You have a blood draw alongside the other blood tubes that are being

[00:13:38] drawn anyways, and you're screened for colonoscopy.

[00:13:42] Colonoscopy is a phenomenal tool for diagnosing the disease, staging

[00:13:47] the disease or even removing polyps where you block the disease from

[00:13:51] going forward, but it's actually not the preferred tool for screening

[00:13:56] because screening is actually, colonoscopy is also not without a

[00:14:01] risk of perforation or risk of adverse events.

[00:14:05] And also most people, they really don't want to do it and therefore

[00:14:09] it doesn't get done.

[00:14:10] So the opportunity there definitely is liquid biopsy.

[00:14:14] And we have had the first in class, best in class blood test

[00:14:17] for color cancer screening on the Swiss market since 2014.

[00:14:22] And now we are seeing second generation products coming out.

[00:14:25] We are building our own second generation product.

[00:14:27] Most other tests in the market are looking at the DNA, which is limiting

[00:14:33] because the earlier you go into the disease state, the less of a tumor

[00:14:38] load you have, the less of a signal you have and the performance of

[00:14:41] the test fall, whether you look at the color guard, if they try and do

[00:14:45] it in blood or whether you look at garden's blood tests or whether you

[00:14:49] look at other people who have developed a blood test, the performance

[00:14:53] for advanced aeronoma is very low.

[00:14:55] So the opportunity here for us is to leverage the immune system, which

[00:14:58] is of course, the first defense of the body against abnormalities and

[00:15:02] picking up weak signals in the immune cells that are responding to the

[00:15:06] cancer and completing the picture by multiplexing that signal with

[00:15:10] the tumor signal.

[00:15:12] And that is extremely promising.

[00:15:14] We're very excited about that.

[00:15:15] And we continue pushing the boundary of that in being able to complete

[00:15:19] that picture and be able to have high performing blood tests that

[00:15:22] change that standard of care for screening applications.

[00:15:25] Of course, say if you're positive for those tests, then you're going to

[00:15:28] go into colonoscopy more for therapeutic colonoscopy rather than

[00:15:32] screening colonoscopy.

[00:15:34] If there is, if you have a positive test, of course, you wouldn't

[00:15:37] mind going to colonoscopy, but normally healthy individuals that

[00:15:41] don't have the symptoms are not preferring to do that.

[00:15:45] Your specific tool or liquid biopsy that you offer in the colorectal

[00:15:52] cancer space is already on the market.

[00:15:54] It's been used by clinicians.

[00:15:57] What kind of patients did usually get it?

[00:16:00] So how do clinicians decide to actually test patients with this test?

[00:16:08] And where do you see the biggest challenges?

[00:16:10] I don't know, is it trust from the clinicians?

[00:16:13] How are you approaching these questions?

[00:16:16] That's a very good question.

[00:16:17] The ease of use is extremely important.

[00:16:22] What we have seen on the Swiss market with the protest that we have on

[00:16:25] the Swiss market for quite some years now, it is for people who are the

[00:16:29] age where they should be screened.

[00:16:32] Who do not want to do colonoscopy and who do not want to do a stool test.

[00:16:36] So that's really how the product currently is positioned.

[00:16:39] Therefore, and what really inspires us is we do get individuals.

[00:16:43] I go to 50th birthday party of a friend of mine and I said,

[00:16:48] why aren't you working on this test?

[00:16:50] I did that test.

[00:16:51] It was positive and thank God because I went to colonoscopy and they found

[00:16:54] the early stages of cancer and they removed it.

[00:16:56] So we get these real cases, which really inspires us to really push,

[00:17:00] continue pushing the boundaries.

[00:17:02] The limitation that we have in the current test is that you have to

[00:17:04] isolate the immune cells from the blood of the patient and make the

[00:17:08] measurements that we need and that requires that you have to process

[00:17:12] a sample within two hours.

[00:17:14] And that's a big limitation.

[00:17:15] We're able to do it in Switzerland, in a small market area that we're

[00:17:18] in. Over 6,000 people have paid out of their pocket to do this test.

[00:17:23] It's very convenient. Me myself, that's the test that I do.

[00:17:26] That's my test of choice that I do.

[00:17:29] But to really get market adoption around the world and global adoption,

[00:17:33] you really need to simplify that pre-analytic.

[00:17:35] And that is really what we're working on today on the next generation test.

[00:17:39] We published some results last year at ASCOGI in San Francisco

[00:17:44] and in ESMO in Madrid.

[00:17:47] And we're seeing extremely good performances in whole blood,

[00:17:51] stabilized whole blood RNA.

[00:17:53] And that is really what we're pushing towards is bringing out a solution that

[00:17:57] is very easy to implement in routine medical practice where you just draw

[00:18:01] the blood, it can sit on the table for a couple of days and you can still

[00:18:04] process it and batch it and ship it.

[00:18:07] When that happens, I think it will really be transformational in terms of

[00:18:11] screening and being able to pick cancer early and where you have a high

[00:18:15] therapeutic response. Not only it's much,

[00:18:18] much better for the individual and the patient,

[00:18:21] not only will save a lot of lives,

[00:18:22] but also it's much better for the healthcare system because you avoid all

[00:18:26] of the costs associated with treating a cancer patient with often

[00:18:31] not very good outcomes by picking up very early and intersecting.

[00:18:36] There are still some reservations around liquid biopsy

[00:18:41] and its broader use.

[00:18:43] And I want to really pick your brain around that.

[00:18:47] For example, last year, the NHS tested the

[00:18:51] Galleri test, which is a blood test for more than 50

[00:18:56] forms of cancer. This was just a test.

[00:18:59] So it was a study and basically the results show that

[00:19:04] two thirds of the included patients were correctly

[00:19:10] revealed. So the test correctly revealed two thirds of cancers among those in the

[00:19:14] study. So when you think about it from the other perspective,

[00:19:17] that means that basically one third or 30% of patients weren't correctly

[00:19:22] diagnosed, which seems quite a high numbers.

[00:19:25] There's this notion that we want to have

[00:19:28] 100% accuracy with these tests.

[00:19:32] So how do you see these challenges?

[00:19:35] Yeah, absolutely.

[00:19:36] So I think we have to peel that out in different layers.

[00:19:40] So first of all, there are a couple of approaches for multi-cancer tests,

[00:19:45] and those have proven to have this difficulty.

[00:19:47] As you mentioned, you cannot send one third of the population on a

[00:19:51] goose chase around trying to figure out what's wrong with them

[00:19:54] because of the false positive rate of the test.

[00:19:57] And that is a challenge with a couple of tests that some of them,

[00:20:00] one of them has even approved for marketing.

[00:20:03] So the healthcare system struggled with that.

[00:20:05] The patients struggle with that.

[00:20:06] And it's absolutely very important that the performances of the tests are up

[00:20:10] where they need to be, which is better than 90%.

[00:20:12] So 90% over 90% specific.

[00:20:16] So there it is a technology evolution question.

[00:20:19] And you can remember the first TVs before went to the next generation,

[00:20:23] before it became flat screen, before it became portable.

[00:20:27] So of course, it is an evolution of the technology landscape.

[00:20:30] And as we go through that technology evolution, we are getting there.

[00:20:33] Definitely there are significant leaps being made in terms of

[00:20:37] the advancement of the performance of these tests.

[00:20:39] But if you look at single cancer tests, such as the colox that

[00:20:43] we have in the Swiss market, we have a specificity of 92%

[00:20:47] at sensitivity of about 80%.

[00:20:49] So we're pushing those boundaries along.

[00:20:51] The beauty of colorectal cancer is that false positive are just

[00:20:55] simply taking you to standard care.

[00:20:57] So you're doing nothing more than just doing the colonoscopy

[00:21:00] that you were recommended to do.

[00:21:02] If you have a false positive.

[00:21:04] And so we really focus on reducing false negatives and making sure

[00:21:07] we capture every cancer patient.

[00:21:09] Um, so there I think there's a huge opportunity.

[00:21:13] We see a lot of improvement in performance of the test with the

[00:21:16] SCDNA and we see a lot of improvement opportunities within the

[00:21:20] immune function and multiplexing those things together where we believe

[00:21:24] that is going to be a reality.

[00:21:26] From a physician point of view, I think they're really interested to know that

[00:21:29] the test is well proven and typically, for example, if you look at a fit test

[00:21:34] it's been around for two decades.

[00:21:36] And so it's become even the performance of a fit test are not very good.

[00:21:41] Nevertheless, they have become relatively accepted.

[00:21:44] Liquid balances are very new.

[00:21:46] So we're talking about, we launched our product in 2014, 2015 timeframe.

[00:21:51] Of course it takes a decade or two for people to become familiar with it.

[00:21:55] To see the test results and to start getting mass adoption.

[00:21:59] Like I said, in the very small market that we are, we've sold over

[00:22:03] 6,000 tests without really doing any sales and marketing.

[00:22:06] We don't have a sales and marketing team.

[00:22:08] Why?

[00:22:09] Because like I said, the pre-analytic complexity of the test is just being

[00:22:12] adopted naturally by the market by physicians who see the importance

[00:22:16] of screening of individuals that are not doing colonoscopy or not

[00:22:20] doing the stool test or individuals who actually educate their physician

[00:22:24] on the importance of it and that they would like to do this liquid

[00:22:26] biopsy test and pay out of the box.

[00:22:28] The next year or so tests will get mass adoption because the pre-analytic

[00:22:33] complexity is being removed and therefore you can be anywhere in the world

[00:22:37] and have a simple blood test to be able to screen for colon cancer.

[00:22:40] If we move away from colon cancer screening for a while, your solution

[00:22:47] is also addressing basically clinical trials and drug development.

[00:22:52] So can you talk a little bit about how exactly are you helping

[00:22:56] reduce the drug development timelines?

[00:23:00] Yeah, that's a very good question.

[00:23:02] Turns out actually to predict response of a patient to a therapeutic

[00:23:07] modality, a lot of it does have to do with the immune function.

[00:23:11] So initially that was discovered in the tumor microenvironment where

[00:23:15] you look at the penetration, for example, of the immune cells in the tumor

[00:23:19] or the proximity and the organization of immune cells within the tumor

[00:23:23] microenvironment.

[00:23:24] What we've learned over the years, and that's not well documented, is

[00:23:27] that those signals actually do come and make themselves in blood.

[00:23:31] And that opens up a huge opportunity where you can actually sample

[00:23:36] immune cells in the blood to learn about what is happening between the

[00:23:40] interaction of the host immune system to the tumor.

[00:23:44] And there, what we have shown now is that you are able to predict who's

[00:23:49] going to respond to particular immunotherapy.

[00:23:51] For example, in bladder cancer patients treated with the

[00:23:53] Antipedi 1, which is an immunotherapy, you get anywhere between

[00:23:57] 20, 30, 40% response maximum.

[00:24:00] Now, what about those who are not responding?

[00:24:02] They're still getting the drug for months and months.

[00:24:05] And at the end they're not responding, which is a terrible

[00:24:08] service to the patient.

[00:24:09] Meaning that they're dealing with a lot of toxicities.

[00:24:12] They're dealing with a lot of impact on quality of life and not going to

[00:24:16] other treatment modalities because they think that I have to finish this.

[00:24:21] What we've been able to demonstrate is that we are able to vectorize

[00:24:24] the patients by looking at once they get the treatment, how the immune

[00:24:27] system of the patient is responding and developing predictive algorithms

[00:24:32] that can show whether this person is going to respond six months from now

[00:24:36] or not.

[00:24:37] And this sort of new world of being able to use leverage AI and

[00:24:41] predictive modeling is completely disruptive in terms of being able to

[00:24:46] show to a physician or to a patient what your immune system is actually doing.

[00:24:51] Being able to get into the operating system of the immune function of the

[00:24:55] patient and extract knowledge about what's going on there.

[00:24:58] So there, if you think of the individuals that are not responding,

[00:25:02] you can ask the question why?

[00:25:03] What is the mechanism of resistance?

[00:25:05] Are there immune features that are predictive of resistance?

[00:25:08] And are there ways to target those mechanisms of resistance to overcome

[00:25:13] that resistance in those spaces?

[00:25:15] So that brings us into combination therapies and where we're able to

[00:25:18] identify drug targets within the patient population.

[00:25:22] Traditional drug development starts with animal models, lines,

[00:25:27] hypothesis driven discovery, and going into an attrition model where

[00:25:31] finally they can come to a first in man, the clinical trial phase one,

[00:25:35] where you've spent years and years, typically 10 years by the time you get

[00:25:40] there, eight to 10 years.

[00:25:41] And we can actually shrink that timeline significantly, shape off about five to

[00:25:46] six years off of that by actually developing the targets within the patient

[00:25:50] population by having a blood sample from the patients that are not responding

[00:25:55] and asking the question, what do we do to overcome this resistance?

[00:25:58] So that's where we are today.

[00:26:00] We have novel drug targets we've discovered both in CRC as well as

[00:26:04] in bladder cancer patients within immunotherapy.

[00:26:07] And we're very excited about the opportunity to improve the therapeutic

[00:26:11] modalities, particularly within combination therapies to accelerate

[00:26:15] development of new therapeutic modalities for better patient outcomes.

[00:26:21] It would be a dream come true that if you get sick, that you would just

[00:26:26] do a few tests and doctors would be able to just prescribe exactly what you

[00:26:32] need. But unfortunately we are far from that.

[00:26:37] Even when you look at genomics, there's only about 20% of human coding

[00:26:43] genes that are well studied.

[00:26:44] So 80% are largely still a mystery.

[00:26:49] And I wonder where are we with that when it comes to the immune system?

[00:26:54] So how much do we already know?

[00:26:58] How much do we still don't know?

[00:27:00] Absolutely.

[00:27:01] I think we have come far in terms of the tumor microenvironment with liquid

[00:27:06] biopsy. The beauty of liquid biopsy is that it can, the data aggregation

[00:27:11] can go very quick.

[00:27:12] You just have to get into clinical trials.

[00:27:14] So today we have a new program we're establishing with the NIH, which has

[00:27:19] 3,500 blood samples from patients that have gone through immunotherapy

[00:27:24] at five time points per patient.

[00:27:26] And this sort of data aggregation and scaling is what is absolutely needed

[00:27:30] in order to get visibility into the unity of immune function of a human being

[00:27:35] and its response to therapy.

[00:27:37] With a screening environment, we already aggregating quite a lot of data.

[00:27:40] We're accelerating that within the therapeutic environment.

[00:27:43] We are also starting to accelerate aggregating that.

[00:27:47] Fortunately there are clinical trials that have already collected these

[00:27:51] samples and buy back them, phase three clinical trials that have been

[00:27:53] completed. So it's just a matter of analyzing and onboarding those

[00:27:57] samples on a platform in order to really get a much deeper visibility and

[00:28:02] better prediction modeling as time goes on.

[00:28:05] So I would say we're really at the cusp of that inflection point where the

[00:28:09] technology has proven itself, where the cost of doing this sort of work has

[00:28:13] come down to a point where it becomes feasible to do the kind of work that

[00:28:18] we're doing per blood sample used to cost initially 10,000 per blood

[00:28:22] sample. That came down to about a thousand.

[00:28:26] It came down to about 600 when we moved our whole platform there.

[00:28:29] And now we can do it with around four to five hundred and that cost pressure

[00:28:33] is constantly coming down.

[00:28:34] So as a cost pressure is coming down, bringing the cost down, you can

[00:28:39] imagine a day I don't think it's going to be very far from the future

[00:28:43] where we get a visibility into the tumor state of the patient using a

[00:28:47] liquid biopsy at the same time getting visibility on the immune response

[00:28:52] and immune state of the patient and contextualizing that within the peer

[00:28:57] group of the patients.

[00:28:57] So your bladder cancer patient with your peer group of bladder cancer

[00:29:01] patients, your bladder cancer patient with a peer group of cancer patients

[00:29:05] in general and contextual this thing is that within the healthy population

[00:29:10] and that is going to what is going to be driving visibility into the

[00:29:14] heterogeneity of the disease, heterogeneity of the immune function

[00:29:17] and tailor and therapies for the individuals.

[00:29:20] I don't believe that we are very far from that.

[00:29:22] We have all the tools and the technologies at play.

[00:29:25] We're getting aggregation of the data.

[00:29:27] Different platforms are scaling now in terms of capacity, both in terms

[00:29:31] of data generation, as well as importantly, data analysis.

[00:29:36] We're able to set up virtual servers overnight, parallel virtual servers.

[00:29:41] This was not possible historically.

[00:29:43] Now, for the first time in the cloud, we're able to compute

[00:29:47] significant amounts of data that was not imaginable just a few years ago.

[00:29:52] And all of that is contributing and accelerating.

[00:29:54] So it's really it is it's an exponential learning curve.

[00:29:58] It is not a linear learning curve.

[00:30:01] And we're really on that exponential part of the curve.

[00:30:03] So that is what keeps us very excited as we work into different populations.

[00:30:09] What are some of the next steps that you wish to see

[00:30:12] in the development of the field?

[00:30:14] You mentioned that basically we have a lot of opportunities

[00:30:17] because of the technologies and because of the computing power

[00:30:19] and everything that can do.

[00:30:21] But still when patients get treated, if they're not a part of a clinical trial

[00:30:26] and therefore a specific research, when they just get treated,

[00:30:30] they just get treated based on all the existing knowledge.

[00:30:35] You don't use the patient to try to get all the information

[00:30:39] and data about that patient to then derive new findings about

[00:30:45] this type of patient.

[00:30:48] I don't know if that makes sense, but basically what I'm trying to say is that

[00:30:51] there's a lot of untapped opportunity in the real world data

[00:30:56] that we're not quite using and translating back into research just yet.

[00:31:01] So that's a very good question.

[00:31:02] So real world evidence generation is extremely important.

[00:31:05] We haven't announced that yet, but we will soon be doing that.

[00:31:08] We have been chosen to be a member of the largest immunotherapy

[00:31:12] consortium in Europe.

[00:31:13] And so we're very excited and real world evidence generation to tap into

[00:31:17] is exactly as you say, routine, everyday,

[00:31:21] concord practice in order to identify opportunities to improve those outcomes.

[00:31:26] Having said that, the FDA has also become extremely interested

[00:31:30] in leveraging liquid biopsies as well as novel,

[00:31:34] bioinformatic and biomarker technology

[00:31:38] to optimize and build a much more modernized trial environment.

[00:31:43] There were just two calls that we applied to for the FDA,

[00:31:46] which are very large studies and large programs to leverage exactly that,

[00:31:51] to bring more precision insights into development of therapies.

[00:31:55] Because at the end of the day, that's what goes into the guidelines.

[00:31:58] It takes time to it is a very conservative field for good reasons

[00:32:02] where technologies have to be well tested, proven before

[00:32:05] the broadened routine practice, which can be frustrating

[00:32:08] because it can be a very slow process.

[00:32:11] But at the same time, once it does come out, it's well proven.

[00:32:15] It's a better and we will see more and more routine

[00:32:18] practice as health care systems around the world go more

[00:32:23] focused on health outcomes as a readout rather than what's just in the guidelines.

[00:32:30] There are very novel opportunities to actually leverage technologies

[00:32:34] to improve patient outcomes and reduce health care costs.

[00:32:37] And we see both the regulators and the payer systems

[00:32:40] extremely interested in Keene and getting that done.

[00:32:43] So again, as the cost of these technologies coming down,

[00:32:46] those opportunities expand rapidly because you can imagine

[00:32:50] if you have to spend several thousand dollars to analyze one blood sample,

[00:32:55] it makes a cost prohibitive.

[00:32:57] But as those cost structures are coming down,

[00:32:59] it's just exponentially accelerating those opportunities.

[00:33:03] So I'm actually extremely excited and optimistic about how

[00:33:07] both the regulators and the payer systems, as well as the research community,

[00:33:11] are very much keen on adopting new ways of looking at things

[00:33:15] and new ways of improving patient outcomes, which we see in our

[00:33:19] control and control data that we get.

[00:33:23] Just one last question before we wrap up.

[00:33:26] What's the biggest challenge that you have in the development

[00:33:30] of your solutions or scaling?

[00:33:33] We mentioned earlier that you're present on the Swiss market.

[00:33:36] I don't know to which extent you are looking beyond the Swiss

[00:33:40] borders in Europe and the US.

[00:33:42] So maybe a quick comment around that.

[00:33:46] Yeah, regulation is a key barrier

[00:33:50] to new novel technologies in health care for good reasons.

[00:33:54] In Europe, it's much more fragmented, so it becomes

[00:33:57] much more difficult to go country by country as whereas in the United States,

[00:34:01] you have one big homogeneous health care system.

[00:34:05] So we absolutely do have a bridge that we have built and we continue

[00:34:09] expanding into the United States while at the same time working

[00:34:14] with local research organizations, as well as government agencies

[00:34:18] that are funding and are health care system driven

[00:34:22] in order to bring our new solutions into the market.

[00:34:25] Those are pathways that we're pursuing every day with our

[00:34:29] both our clinical studies as well as our partnerships.

[00:34:32] And those partnerships are critical, right?

[00:34:34] You're not going to as a small company get rapid adoption

[00:34:38] if you decide to do it all by your own.

[00:34:39] And so we're very keen on that, both the partnership with biopharma partners

[00:34:43] that we have and we continue expanding, working with as well

[00:34:47] as large institutions such as the NIH and the Anderson and others.

[00:34:52] And then also in Europe, we work with

[00:34:55] C.D.K. Leuven and others in order to rapidly

[00:34:59] expand the reach of those organizations onto our platform

[00:35:03] and making it available.

[00:35:04] That's also the beauty of being able to look at the decentralized

[00:35:08] data generation, centralized data analytics, which has been

[00:35:12] the core strategy of the company.

[00:35:13] So now that we have more and more maturity, more and more

[00:35:16] a demonstration of capability of biomarkers, invalidated data sets

[00:35:20] that is extremely helpful in terms of now getting rapid adoption into the market.

[00:35:26] So for us, it's really about partnerships and about last month

[00:35:29] to the patient, which we're leveraging established channels

[00:35:32] and established partners into the market in order to accelerate.

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