Harsh Thakkar (00:02)
Russ, thank you for joining us. Really looking forward to this discussion. To start off with, I want to ask you...

You've had such a fascinating career. I was looking at your LinkedIn profile. I've seen all the companies you've started and, know, entrepreneur journey and what you're doing in the industry. How did you get attracted to the life sciences industry?

Russ Lebovitz (00:28)
Sure. You know, I started off in science and medicine.

So life sciences is really part of my blood. My original training was medical training and then a PhD in molecular biology. So I've always been fascinated with approaches based on molecules, interactions of molecules. Life sciences are perfect because they're complex. You have to drill down to individual molecules, but it's systems of molecules that make it work. And in my medical training, it was very much focused on pathology and diet.

So most of the things that I have done in the entrepreneurial area have been related to diagnostics. And so that's where we find ourselves today with Amprion.

Harsh Thakkar (01:19)
Yeah, and that's a good segue because I was also looking at Amprion's website. for people who are hearing Amprion for the first time, what's your 15, 20 second elevator pitch about what the company is?

Russ Lebovitz (01:37)
Sure, Amprion has a very unique approach to a small class of diseases that have a giant impact. And these are neurodegenerative diseases.

Alzheimer's, Parkinson's, ALS, PSP, and others. And it turns out we've known for about 30 or 40 years that these diseases are uniquely caused by normal proteins that misfold into an alternative shape that triggers a cascade of toxic events that eventually leads to cell death in the brain. And what we see as Alzheimer's, Parkinson's, or the other diseases. And Amprion has developed very unique

tools to look at misfolded proteins in the context of the normal form of the protein.

And so the important thing here is that in most biological fluids where you'd want to do testing, the misfolded proteins outside of the cell are present at very, very low concentrations. And the only way to detect them using Amprion's technology is to first amplify them a million fold and then use more traditional tools to detect them. Without the amplification, we're talking about detecting a disease based on one

to 10 molecules.

Harsh Thakkar (02:58)
So I'm going to go later as we go into the conversation about how the diagnostic test works and how it's different. But you mentioned that you've started, you came from a medicine background, that inspired your vision to get into the diagnostic side and that's how you entered the life sciences. But what was your vision in starting Amprion and

You know, how did your past experiences in the industry or in the medicine field, you know, help you to set up the vision for the company?

Russ Lebovitz (03:34)
Sure.

I've always been very interested again in novel molecule -based technologies for diagnosis. And when I met my co -founder at Amprion, Claudio Soto, at the University of Texas, he had developed what I considered to be a groundbreaking technology, which was the ability to rapidly amplify these misfolded proteins that were impossible to detect otherwise. Before Claudio

Harsh Thakkar (04:01)
Hmm.

Russ Lebovitz (04:05)
The only way to tell in the end if someone had one of these diseases was to look in their brain after they died. And he had the idea that even with very small amounts, you could amplify them a million fold or more while the patient was still alive and sometimes before they even have signs of disease. So it was revolutionary and it was worth going all in on.

Harsh Thakkar (04:31)
Yeah, I think, correct me if I'm wrong, but I think you're referring to what's on your website as the Samplify ASIN test, is that correct? Okay.

Russ Lebovitz (04:41)
Yes. Well, in this case, it is with there are a number of proteins that misfold.

a handful that we know of now, really five or six. The first one that was understood and where my co -founder did his work was a disease called Kreuzfeld -Jakob disease. It's fairly rare. It's better understood when it transmits from animals to people as mad cow disease. But it's really the index for all of these diseases. And so what Amprion has done is move from the pioneering work in CJD or Kreuzfeld -Jakob disease onto much more

Harsh Thakkar (04:49)
Mm -hmm.

Mmm.

Russ Lebovitz (05:19)
prevalent diseases, Alzheimer's, Parkinson's, ALS, and it turns out that all of these are similar in that misfolded proteins appear to be shared by all of them and it is the basic mechanism. Each of these diseases generally is caused and it progresses due to a handful of misfolded proteins. In some cases they're different, but in a lot of cases they overlap.

So Amprion first developed the test for a protein called synuclein, which is present in basically all cases of Parkinson's, all cases of Lewy body dementia, and probably 40 to 50 % of patients with Alzheimer's. And it changes the disease to a much more aggressive form.

And so that is where we focus our attention on synuclein. So the test you're referring to now is actually a product in the market, the Samplify Asyn. But we are working on similar tests for other misfolded proteins. We expect to have an equally revolutionary impact on the diagnosis, accurate and early diagnosis of all the neurodegenerative diseases by bringing in other proteins as well.

Harsh Thakkar (06:07)
Hmm.

Yeah, I wanna go deep on how that works, but before I go there, what is the cause of the, you've talked about misfolded proteins, so what are some of the causes? Why do, and is it something in like genetics or what are some of the causes and is it worse in some versus not as, can you shed some light on that?

Russ Lebovitz (07:04)
Sure.

I mean, we're still learning about this. This is a brand new mechanism of disease that affects many, many people. But what we've learned are that there are, again, a small number of proteins in the brain. They're very abundant proteins that have this tendency that very rarely they can change from shape one into shape two. When they change into the alternative, what we'll call the misfolded shape, that becomes more stable and it over time,

it converts all the normal functional form of the protein into the misfolded form. You end up with a cell that basically has a loss of function for the original protein and a gain of function for the misfolded protein. And furthermore, that misfolded protein...

Harsh Thakkar (07:51)
Hmm.

Russ Lebovitz (07:54)
If it escapes from the cell and infects another cell, starts the whole process over. So at some point, misfolded proteins that escape from a cell now trigger a whole cascade that affects one cell, then two, then more, and you get to millions, sometimes hundreds of millions of cells it takes to have a symptom like that seen in Parkinson's or Alzheimer's.

Harsh Thakkar (08:00)
Hmm.

Russ Lebovitz (08:20)
So what causes it? It could be in some people we know it's genetic. In those people, it usually is very early onset. If you have a tendency for a protein to misfold more frequently, then often by age 35, you'll find whole families with Parkinson's or Alzheimer's symptoms. In other cases, it may be environmental. And we haven't yet identified exactly what those environmental toxins are. But some people believe

Harsh Thakkar (08:44)
Hmm.

Russ Lebovitz (08:50)
it may start in the gut or it may start in the nose with where we get exposed to environmental carcinogens or mutagens or active compounds. We're not sure what they are in the environment that's doing this. And then last, sometimes it's just stochastic. It's bad luck that protein has a small chance of misfolding and without even an external stimulus, you get in a single cell.

Harsh Thakkar (09:09)
Hmm.

Russ Lebovitz (09:18)
Proteins misfold and starts the same cascade.

Harsh Thakkar (09:22)
Yeah, I love how you are able to break down such a complex topic and explain it in a simple way. I love this. So I'm sure the audience or listeners will also appreciate that. So now that you've talked about how these proteins get misfolded and there's various reasons of how this happens and how it starts from one protein and spreads to the other different other parts.

Now I wanna ask you like, so how does the, how does this test, the ASIN test, Samplify S -Amplify test, how does that actually work in identifying these proteins?

Russ Lebovitz (10:06)
Yep. Great question. So the test takes advantage of the fact that the misfolded form of the protein becomes very stable and it actually can convert every normal protein of the same type that crashes into it into the misfolded. And so over time, what we do is in our assay, we will take a fluid that reflects what's going on in the brain.

The one closest to the brain is spinal fluid, CSF, cerebral spinal fluid. But we're working on other fluids as well. And if there is disease, we know that in the cerebral spinal fluid outside of the cells of the brain, but close, there are a very, very small number of these misfolded proteins released into the fluid. So what Amprion does is to take a sample, a biological sample from the patient, in this case,

or spinal fluid, mixes it with a million or 10 million fold excess of the normal protein, and then we just let them interact. And if there is one to five molecules of the misfolded, it will begin to convert the normal into the misfolded. However, we can accelerate this that every 20 to 30 minutes, when the misfolded protein, when the normal protein

is converted to misfolded, it actually stacks on top of it and you start to build a line of these. And if we break those in half every once in a while, it's actually the ends of those fibers or those lines where the misfolding is occurring.

So if we allow it a very small line to become a long line, we break it in half, we allow each of those to become longer. Over time, we are increasing the number of misfolded proteins exponentially. And in 24 hours, we can go from one, which we started with, to 10 million or more. And it's only limited by the amount of normal protein that we throw in. And once we have

Harsh Thakkar (11:52)
I

Hmm.

Russ Lebovitz (12:22)
10 million copies, it's very easy to detect. When we start with one copy or five copies, it's basically too low for any existing technology to detect. So it's the combination of the misfolding and the amplification that makes what Amprion does so unique and important.

Harsh Thakkar (12:43)
Right and just to recap, are the conditions or diseases that this test can work on detecting?

Russ Lebovitz (12:52)
Sure, so with all misfolded proteins, that would cover what we call Alzheimer's, Parkinson's.

Harsh Thakkar (13:00)
Mm

Russ Lebovitz (13:01)
ALS, Lou Gehrig's disease is ALS, a disease called PSP, Progressive Supranuclear Palsy, multiple system atrophy. There are about 20 neurodegenerative diseases. Most of them start in people age 50 to 70 and get worse over time. And right now we have no real way to stop or reverse these changes. Although as an ecosystem, we're making a great deal of progress, a lot.

of the drug companies have drugs in the market or drugs in the pipeline, but it's diseases that we all know about, that we all have family members with, that we really haven't been able to understand until recently. And with Amprion's tools and other parts of the ecosystem with tools that complement, what we are doing is understanding that these are complex diseases, that they are

Harsh Thakkar (13:31)
Hmm.

Russ Lebovitz (14:00)
We need personalized medicine. Almost everyone's case has a different spectrum of misfolded proteins. And so what Amprion is able to do with the rest of the ecosystem is to quickly characterize each patient's disease molecularly. And therefore we believe we can target it to the best therapies and help develop the best therapies.

Harsh Thakkar (14:03)
Hmm.

Yeah, no, that's super impactful. And it just goes to show that, you know, the technology that you and your team have developed is, you know, has tremendous potential. You mentioned about 20 different types of conditions or diseases. So you also talked about ecosystem, which is kind of a good segue into the next question I had is how do patients or people who have these conditions, how do they get

the test that you described. Does the medical provider tell them, you probably need to take this test? What kind of qualification criteria do they have to go through before they get this test?

Russ Lebovitz (15:10)
Yeah, at present, are diagnostic tests. So for a diagnostic test, it is heavily regulated. So for someone, they see a doctor, a specialist, we break the neurodegenerative diseases generally into two classes, or the field breaks them down.

cognitive, where the main symptom is inability to think clearly and to remember things, or what we'll call movement disorders, where people may be thinking clearly, but they can't move in controlled ways the way they used to.

Harsh Thakkar (15:29)
Mm.

Russ Lebovitz (15:45)
Both of these classes are caused by similar misfolded proteins. They just happen to affect different parts of the brain, either parts related to thinking and association or parts related to movement. But when you see a specialist, so if you have...

Parkinson's disease or one suspects there might be Parkinson's or ALS, you would go to a movement disorder neurologist and they then would order the test. If it's cognitive and there are memory problems or thinking problems, one would go to a memory center and the physician there could order the test. So it is available anywhere to any physician and any patient in the United States and we're trying to expand that worldwide as well.

Harsh Thakkar (16:31)
And what does that take when you set to expand it worldwide? Is that like more regulatory approvals or, you know, yeah.

Russ Lebovitz (16:39)
It's regulatory approvals. And, you know, since we're collecting samples, it's much easier to ship those within one region. So when we do it in the United States, we can actually handle right now a lot of samples in the United States in our main clinical lab in San Diego.

Harsh Thakkar (16:49)
Right.

Russ Lebovitz (16:59)
but it's a little too far to handle Europe or Asia. there's a giant unmet demand in Europe. So we are addressing that now. There's a rapidly growing unmet demand in Asia. So we are moving as rapidly as possible to be able to address that. It's regulatory, it's infrastructure. It's not the technology. We actually have patents covering the amplification of these misfolded proteins worldwide. So we also have an obligation

Harsh Thakkar (17:03)
Right.

Russ Lebovitz (17:29)
to reach patients worldwide.

Harsh Thakkar (17:32)
Yeah, and I, you know, every day, every time I talk to a guest on this podcast, it's, you know, I always learned so much. And today you just taught me that there's, you know, two different kinds, like the cognitive and the movement disorder. And I actually know two people in my family, you know, who've had one of these conditions. And I was thinking about them when you were talking to me, because one of them has the cognitive type and the other one has the movement type.

And I never understood that, but after you just explained it, I had like a flashback of, know, them in my mind. So thank you for that.

Russ Lebovitz (18:10)
I'm glad that this conversation helps you, because you helped so many people by having this podcast.

Harsh Thakkar (18:16)
Right, thank you. I wanna switch gears and talk to you about some other trends in the industry. As you are, I know we've talked a ton about Amprion. Outside of your world of Amprion and the stuff that you're doing, what do you think about the potential of technologies like AI in the imaging space or helping understand how the human brain works?

to get to identify these kinds of diseases faster.

Russ Lebovitz (18:47)
Yeah, another great question. so first that you we've already acknowledged that one can look when one wants to understand changes that are in molecules that cause those changes. There are several tools we have. One is fluid biomarkers where we can identify down to great detail the molecules themselves. Others would be involved in molecular imaging where we can not only see the molecules, but see where in the brain they're affecting.

So all of these work together and I'm so proud to have worked in imaging as well as fluid biomarkers and even looking at tissue itself. These are all tools that are complimentary. But your question about how something like AI can help, it has...

incredible potential for looking through very, very large amounts of data. So I'd say we're already at the point with AI in image analysis, where a computer program can do a better job than even the best trained person in looking at an image and making a diagnosis. And that's because the computer can combine the lifetime images seen by a hundred or a thousand or

or a million doctors, and then the next diagnosis is based on all of that information. So what AI does is allow us to combine so much more data than even one person can see in a lifetime. And that would include what we do with fluid biomarkers, imaging biomarkers, tissue biomarkers, and AI has the potential to combine all of those. So knowing something that someone who looks at tissue knows, someone who looks in the

Harsh Thakkar (20:09)
Mmm.

Russ Lebovitz (20:36)
fluid nose and someone who looks at images, you can combine all of those together now to get the experience of 100 ,000 doctors all around the world and do it in a few seconds. So I'm looking forward to that ability to combine more and more data and get better and better diagnoses, which will undoubtedly lead to better and better treatments.

Harsh Thakkar (21:03)
Yeah, that's interesting. do you think as, so I agree with everything you said about the potential of AI, but do you think that the healthcare professionals and the doctors and the surgeons, do you anticipate there being some sort of a learning curve or maybe some sort of a change in how they approach? Because maybe when they were trained,

or when they went to school to learn medicine, maybe 20, 30, 40 years ago, AI wasn't where it is today, right? So for those providers, what challenges do you think they might have in embracing AI, if you will?

Russ Lebovitz (21:46)
Sure, so first as you said, look, there are people who are very good at this, but they have been doing it for 30 and 40 years. Sometimes it's hard to understand that someone can devise a computer program that captures all of your expertise. But my experience is that the doctors who take care of these patients are very dedicated. They want the best tools and it's both, it's a partnership between the doctors who need the tools and the software

Harsh Thakkar (21:54)
Mm.

Russ Lebovitz (22:17)
who need to make the interface for the doctors as simple as possible so they have access to all of this information and you know we're beyond the point where they have to write programs and scripts themselves it's all visually guided but the user experience and user interface is critical so

The beauty of this AI in life sciences, it requires so many different expertise coming together to make it look simple. But as it looks simple, then everyone will adopt it.

Harsh Thakkar (22:51)
Right, yeah. mean, just being in the industry, I've seen sort of maybe the overlap or the amount of areas in the healthcare and life sciences space where technology has had an impact. Just thinking about how it was 20 years ago, now we're seeing so many. Every time I go to a doctor's office or I go to visit somebody,

who was in a hospital having a surgery, I'm always seeing like new types of equipment, like fancy analytics and charts. And so you can already see that it's progressing really fast.

Russ Lebovitz (23:32)
Yeah, the big challenge with incorporating technology is to make what we do already or workflows more efficient, right? I'd say the first, the end of the 20th century, we had a tremendous number of breakthroughs, but what they did was to increase the cost of using them and increase the cost of healthcare tremendously. That was the phase one. In phase two, as we add software now that takes this knowledge and does it,

Harsh Thakkar (23:41)
Hmm.

Right.

Russ Lebovitz (24:02)
it more efficiently and in milliseconds, things that might take weeks otherwise, we can now begin to increase the efficiency while improving the overall.

We improve the efficiency by being better and doing it faster. And then if we can do it at lower cost, then we can reach everyone. One of the problems with the technology of healthcare for the last 30 years is that it is advanced, but it is expensive and we've only reached a subset of the people who need it. I believe that with the new breakthroughs in large data and AI, we'll be able to reach more people in a more affordable way.

Harsh Thakkar (24:42)
Yeah, agreed. And when you look at the field of neuro -generative diseases, we've talked about AI and how it has a huge impact. But outside of technology, what do you think are maybe some other challenges in that space that are making it difficult to bring new therapies or identify the cause of these diseases?

Russ Lebovitz (25:09)
Unfortunately, what we're learning is that these diseases are more complex than we thought. And it may be that we're going to need combined modalities. So multiple drugs plus some devices plus certain other behavioral care. But fortunately, we've already seen, you know, we can follow the example set in the last 30 years by cancer treatment. Cancer also is a molecular disease. We've decoded

Harsh Thakkar (25:15)
Hmm.

Russ Lebovitz (25:39)
what the problems are. And because of that, we've made great inroads in diagnostics. And we know that certain cancers need to be treated with multiple drugs. We know that people who have breast cancer, may be 10 types of breast cancer based on the molecules that cause it, and then you need different drugs for each type. So I think it's personalized medicine, understanding and neurodegenerative diseases. These are complex, just like cancer, and that we need

Harsh Thakkar (25:56)
Hmm.

Russ Lebovitz (26:09)
each patient to understand with their doctors which molecules are involved and then we can target each of those because I believe that one we can stop the progression of these diseases but much more importantly and we're starting to do this with cancer as well if tools like amperions which can detect these diseases very very early

It may be possible to have drugs that are not magical, but they just have to slow it down. And if you find someone who's 50 and has no symptoms, a drug that might not do much at 70 when they've already lost their ability to think or move might be very effective at 50. early, you know, I believe that early diagnosis enables early treatment and early cure, or at least prevention.

Harsh Thakkar (27:01)
Yeah.

And with, you know, another side, when in any field when we talk about technology and incorporating technology. Sorry, your video is frozen. I'm not sure if you're still able. okay. Yeah, no worries. Your video was frozen, so I wasn't sure if you were on, but okay. no worries. Yeah, so you were talking about.

Russ Lebovitz (27:17)
No, I'm okay. Let's just take a second. Okay.

Yeah, it happens. Sorry.

Harsh Thakkar (27:31)
you know, technology and how there's this tremendous potential. And that's really, you know, it's a really positive future that we all want for the patients and for the entire ecosystem. But if you want to switch, you know, on the other side and talk about risks and ethical implications, what are some things that we need to be cautious so that, you know, we're

sort of incorporating technology in the right way with the balance that is needed.

Russ Lebovitz (28:07)
Well, these are different questions for what I'll call sort of molecular approaches. So every drug has risks.

So we have to be sure that we are diagnosing people properly so that we are using the right drugs where you get the maximum benefit with the minimum number of side effects. So accurate diagnosis helps because if we've misdiagnosed someone, we expose them to a drug that's not likely to help them, but will have the same side effects. So there's one. The other is more on the computational side, right?

Harsh Thakkar (28:17)
Yeah.

Russ Lebovitz (28:47)
And we have to be very clear about our algorithms for the same reason. A misdiagnosis leads to a mistreatment and therefore we're increasing the risk. So I think we have to have our direct interventional tools, our drugs and our clinical trials need to really pinpoint the right patient population by accurate diagnosis. And then our

Harsh Thakkar (28:55)
Yeah.

Russ Lebovitz (29:14)
analytical tools also. I we have to hold both to a very very high standard.

Harsh Thakkar (29:20)
Yeah, yeah. As someone who is so passionate and deeply involved in this space and everything you're doing at Amprion, I want to ask you for a prediction. If you're looking at this space in the next five or 10 years, is there some kind of a company that you think is gonna be formed in this space? Is there a new innovation that you might think is gonna happen? What breakthroughs?

or do you anticipate happening in this space?

Russ Lebovitz (29:53)
Well, I mean, those are big questions with a lot of answers. I don't know that there's one technology or one company. I can say that now that we have very accurate molecular diagnosis for these diseases, and I can say that, you know, in the last...

Harsh Thakkar (29:56)
Yeah.

Russ Lebovitz (30:10)
week or so, the FDA came out with a letter of support for Amprions technology, although there are others that are complementary, to say that these work well enough that they need to be used in future clinical trials and to make the clinical trials better to learn more about the disease. So I'd say on the diagnostic side, are a number of companies I think Amprion is on the forefront. I think on the drug development, I know that for Parkinson's,

There are probably 50 or 70 new drugs out there for Alzheimer's even more. And some of these, because there's only a handful of misfolded proteins, these very prevalent diseases will lead to the development of drugs that will also help patients with less prevalent diseases like ALS, where there may be 30 ,000 a year as opposed to maybe...

you know, several million a year for Alzheimer's and several hundred thousand a year for Parkinson's. So I think that one, every time we understand and develop a new drug, could be used across platforms. And so I think that's great. And then there are already a number of companies in the AI space trying to speed up and improve the quality of our drug development.

because time is really important. So by looking at all the data generated by Amprion and others, they may help us to come up with drug candidates and predict which ones will work best. Every year we save in development, one, saves a ton of money, and two, gets these to people faster.

So I'm very optimistic that all of these technologies working together are going to have a giant impact. That's why I talk about ecosystems, right? know, people working on drugs need to understand, people working on AI need to understand people who are working on diagnostics and digital therapies and digital diagnostics. The ecosystem is what's going to win here.

Harsh Thakkar (31:58)
Yeah.

Yeah.

Yeah, when I look at the conversation we've had so far, few things really the main takeaways at least for me are, for companies like Amprion who have this innovative technology to identify different, do these diagnostic tests for these different kinds of diseases, that's really an amazing thing for the industry and for the patients. And also,

AI there's a potential, huge potential, but at the same time, these diseases are not easy to understand. So even if we have vast amounts of data, we can come across a patient that, you know, pretty much has a completely something completely new that you've never seen, never heard of. And how do you tackle that? So, it's, it's, you know, a combination of, scientific expertise from all the, you know, healthcare providers.

plus technology like you mentioned the word ecosystem, that's exactly what needs to happen. And then you also made another interesting point, which is the newer therapies are not just a one shot, like, hey, here's a drug, go and do it. It's a combination of digital health, a physical drug or some kind of app, and all of these things are working together to sort of give that end patient experience.

or treat whatever it's trying to do. So that's a trend I've seen as well in the industry.

Russ Lebovitz (33:47)
Yeah, it's very exciting. You the brain is different than all other organs. know, all other organs, if there's a problem, you can go in with a knife and cut it out. You can't do that with the brain. So we have to use every arrow in our quiver to be able to hit what's going on in the brain. It's just, it's a very, very different set of challenges, but I feel like we're up to it.

Harsh Thakkar (34:13)
Yeah, kudos to you and your team. those, listen, this has been really amazing conversation. Thank you for coming here and sharing these insights. For those who want to learn about you or about Amprion, do you want to share where's the best way they can find you?

Russ Lebovitz (34:30)
Sure, best way is at our website. While the company's Amprion, we're Amprion Diagnostics. it's Amprion, A -P -R -I -O -N -D -X dot com. And you should find lots of information there. We go to every meeting. We're open to all sorts of ideas. We wanna have an impact, but Amprion DX is the place to go to learn about the company.

Harsh Thakkar (35:00)
All right. Thank you, Russ. And for the audience, if you want to hear more content and more episodes like this one from guests like Russ, be sure to hit the like and subscribe button and I'll see you in the next one. Thanks.

Russ Lebovitz (35:13)
Thanks, Harsh. I really appreciate it.