359 liang
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Kevin Folta: [00:00:00] Hi everybody. And welcome to this. Week's talking biotech podcast by collabora. Now, when we think about the immune system, we think of this finely tuned system that protects us from foreign invaders. This system of surveillance in the body that monitors for bacteria, fungi, viruses, other foreign protein products, other antigen.

Now the body has this capacity to Mount an immune response to learn. And remember that it saw a certain threat, a certain protein signature, these aspects of the immune system allow us to train it to maintain a durable response against a pathogen. So process like vaccination, right? So one of the most adaptable levels of immune response.

Are the antibodies. So these molecules that are produced to meet a new antigen threat or an, you know, also known as maybe [00:01:00] a foreign thing, the production of antibodies allows the body to target these new threats. And so what if your immune system could not just be trained to produce these antibodies?

But what if cells could be programmed with specific instructions to attack a problematic cell type, like those involved in cancer. And could those molecules, those antibodies that are produced be used to neutralize cancer and be used as therapeutics in a suite of different disease states. And on today's podcast, we're speaking with Dr.

Leon Schweitzer, she's the founder and CEO of high fi bio up in Cambridge, Massachusetts. So welcome to the podcast, Dr. Schweizer. Hi, 

Liang Schweizer: Kevin. Thanks for having me here. 

Kevin Folta: This is really exciting because it's something that I admittedly know very little about. I've learned about immunology. I've learned about immunotherapies.

I'm [00:02:00] captivated by learning about them, but it's, it's so complex that it's something that I felt was really important for us to distill down for someone to understand kind of how it works in, in the. Simple sense, but then translate that into the front cutting edge and understand what's going on. So let's start out at the beginning.

What is this broad idea of immunotherapy? 

Liang Schweizer: Yeah, indeed. Our own immune system is quite complex. To this day, we cannot say we understand most of it, but one of the phenomena people Ernie young, already understand by moated immune system, you can treat disease. And the initial approach is looking at autoimmune diseases where you marginate immune systems, trying to, you know, overcome some of the illnesses people encountered.

The most interesting part recently draw [00:03:00] people more attention to immunotherapy is the fact that people find out we can ate our own immune system to fight cancer. So immunotherapy today in a lot of people's mind is talking about how to activate immune system to treat cancer that comes from the work Ernie young.

Actually, I personally got involved in. Back at BMS times where we looking at a drug called map and the brand name is UVO that target a checkpointing inhibitor called CTA four. So we have at that time successfully proved the concept by modulating immune system by eliminate removing the function of.

Negative suppressive immune system, which we call checkpoint can activate T cells that against, you know, subsequently kill the tumor cells. So that was the. Basically [00:04:00] a start of a new era subsequently there are other checkpoint inhibitors like PD one and it's Nigen PD one. There are modernation center around.

So now afterwards Fast forward. Now there are many efforts sent around how to Moate immune system, not only for the adaptive systems like T cells, but also for inert systems. People start looking at NK cell therapies. So There's a lot of understanding associated with that subsequently and people start thinking about how to apply immunomodulations into diseases beyond autoimmune cancer possible in other disease as well.

We are thinking about possible for certain cardiovascular metabolic, even neuro degeneration. Efforts immune system can play a critical role. That's just looking forward. . 

Kevin Folta: Yeah. And I, I think I I've [00:05:00] seen a lot of this so far, especially with the neurodegenerative stuff we've covered here on the podcast, but let me go back just a little bit, because there's some concepts here I'd like to you clarify, when you say checkpoint, are you talking about cell cycle checkpoints?

Cause that's where we usually think about these or are you speaking about some sort of a immune system checkpoint? 

Liang Schweizer: Yeah. It's great. You clarifi that and Kevin, because indeed early days, especially in the cancer field. Yeah. We, we talk about sales cycle, checkpoints and others, but this is specifically in the immune service setting where we talk about checkpoints those, the pathways.

Involved in regulate immune responses. Normally it's where, you know, in the normal of physiological functions, those checkpoints are involved in, you know, self tolerance and to control immune system in a way that it wouldn't be overactive to a, you know, come [00:06:00] up with situations where attacking its own sale.

In situations where autoimmune diseases, some in a situation where the checkpoint gaining, you know, into deregulating. So people were experience some symptoms that, you know, where, where the immune system start, you know, dealing with its own cells. So those are the type of System in place that has been already, you know well unstowed over the years and now we are in immuno-oncology.

Leverage those scientific understandings, trying to activate instead of inhibit as in autoimmune diseases to, to activate immune systems. So you remove the negative regulation of the checkpoint. 

Kevin Folta: Okay. Now that makes a lot of sense to me. So in the immune system, when you have a hyperactive immune system, such as like lupus, rheumatoid arthritis maybe Crohn's disease, whatever you are [00:07:00] seeing, this kind of enhanced.

Or a lack of gating, a lack of a checkpoint that kind of constrains what the immune system does. And it starts to go after self. Whereas in the case of cancer, It that same checkpoint is constrained and doesn't go after self when we would like it to go after self. So what you are talking about is how do you treat, how do you train an immune system to actually go after self when it crosses the line in the cancer?

Liang Schweizer: Yeah. In the situation of cancer. That self with the quotation mark is referred to the cancer cells. you? You're still, you still not want to, you know, attack your own normal cells, but cancer cells has ways to invade immune surveillance. So in that situation, you know, the checkpoint inhibitor no longer have the function to, to attack cancer cells where we wanted to remove that [00:08:00] negative immune suppression to activate the system.

According. 

Kevin Folta: I really appreciate your clarification there. It helps me understand this a lot, but could you help me also understand, you know, I have an immune system, it works pretty good. So why do we need to come up with something that can discern cancer from other normal self cells? Why, why doesn't our body automatically go after cancer 

Liang Schweizer: in.

Actually, I, I would imagine a lot of us, normally our immune system was good enough. the great rate of some you know, cancer like cells, which other cells out of the normal control. One of the hallmark of cancer cells is continuously ation and. we do normally have our immune system to keep those cells in check.

But as we developing some individuals have compromised immune cells, some cancer cells, [00:09:00] also on top of it to figure out ways to escape our normal. Immune surveillance. So be in that situation, you have to use therapies to Moate immune systems to recognize those escaped cancer cell, if you will. And in the meantime, you know, for, for people who might be not have enough cancer, I mean, immune power to fight cancer cells.

Wanting to boost their immune system further to be able to fight cancer cells. 

Kevin Folta: No. Very good. And you said something there that I'd also like to clarify with the average listener is you said boost the immune system. So this means a very specific targeting to changing the way a certain cell identifies its target, not the go to the gas station.

And someone sells you a, a drink for $4 that says it'll boost your immune system. you're talking about what you don't wanna do, boosting your immune system. Isn't a good idea. [00:10:00] Ask anyone with lupus. But the idea being selectively, changing the function of specific cell types to identify their targets or, or potential targets a little better.

Liang Schweizer: Yes. So, so when you are talking about, you know, different modulations and one of the important aspect to treat a disease is to figure out in that specific disease setting where immune dysregulation. Happens. Right. Whether it's exhausted T cells no longer can fight can cancer cells or where situations where I, and like you mentioned, the gas station, where we, we, we have too many breaks there where immune cells cannot be activated due to too many breaks.

So checkpoint inhibitor often we see this as the breaks is. Preventing your immune system to fight the cancer. So [00:11:00] we using, you know, checkpoint inhibitor to remove the breaks. So it lets it go. But in the meantime, another way is you could also adding gas to stimulate immune cells to make them go forward too.

So, so that's actually one of the. Two approaches people in the field has been trying really to, to figure out. So you know, for, in each individual diseases and individual patients, even where you immune balance needs to be achieved to restore your immune activity you, you need to figure out what's the disease context 

Kevin Folta: first.

Oh, very good. And I love your analogy. I think it's spot on you have the gas and the brakes and how do we energize the appropriate parts of the immune system to take action while keeping the brakes on where it doesn't overcommit. And, and so how do we, how have immune therapies or immunotherapies? Cause we've heard about this for a little while [00:12:00] now.

What are some of the big success stories where immunotherapies have been successfully targeted to a specific cell? 

Liang Schweizer: Yeah. So, so one of the biggest breakthrough in cancer field is PD one and therapeutics. So that's in addition to CT, F four, I just mentioned earlier, PD one is another checkpoint inhibitor and Often, you know, it's it's, you could sync it.

It's a general break for multiple tumor types across multiple individual patients. So as a consequence, when you have PD one, anybody specifically that those are the therapy Developed that subsequently those multiple tumor types or multiple patients will respond to that inhibition release the break if you will.

So the. Outcome that's one of the biggest success is is a monotherapy of PD. One they're about [00:13:00] somewhere, you know, around 30% responses, average different kind of tumor types. Of course the in certain tumors responding could be even more. Some ness. So this is really totally changing the landscape for cancer treatment.

As you know, early days, you know, with chemo and targeted therapy there's limited successes and there's clearly AME medical needs. So immunotherapy coming out here provide a really another noble option for patients with terminal IIT, like cancer. That indeed, you know, was one of the. really exciting moments for us as draft developers in the 

Kevin Folta: field.

But this is the exciting part for me, is being able to not just modulate immune function, which is, which is very important, obviously, but being able to reprogram immune function. [00:14:00] And it seems like that's really a, a highlight of a lot of the immunotherapy programs that's that are going on, that your company has really.

Honed and really sped up. So before we get into your solution, let's talk a lot about, a little bit about the problem is what are some of those barriers to having efficient development of antibodies or other molecules that can help modulate this immunotherapy response? 

Liang Schweizer: Yeah. This is an excellent question, Kevin.

Clearly, you know after the success of PD one, there's a lot of effort trying to develop immune originators and sofa. Hasn't had some other groundbreaking outcome yet. That's also. Immune system is very fine tuned, well balanced system. So where you could imagine, you know, you release one break somewhere else might have corresponding responding changes.

So. [00:15:00] In order to understand the immune balance. We need to understand much better of all those important pathways players in the immune system. So this is one level of complexity, the biology itself. Then the second level of complexity is diseases. Like if we looking at cancer itself, Have certain cancer, we call hot tumor.

Certain cancer. We call cold tumor is because in the tumor micro environment, it's own immune context are very different. They are, the hot tumors are the ones who has immune cells surrounded and immune modulation would have much more effective versus code tumors where, you know, you, you probably have total on a minimum.

Immune system presence. So, so making modernation of those cold tumor difficult, and there, there were efforts in industry where [00:16:00] people tried to tank cold tumor into hot tumor by, you know, enhance immune filtration to tumor micro environment. But those are the efforts so far, you know, still in very much exploratory stage But personally, I'm confident we will with, you know, enhanced understanding of immunomodulation with enhanced understanding of disease.

Especially looking at individual cell level send around the disease context and You know, we, we will have much better tools or approaches to conquer disease. 

Kevin Folta: No, very good. And, and let's talk about that more on the other side of the break. We're speaking with Dr. Sweer, she's the founder and CEO of high five bio, and this is collaborative talking biotech podcast, and we'll be back in just a.

And now we're back on collaboratives talking biotech podcast. We're speaking with Dr. Leon [00:17:00] Schweitzer. She's a founder and CEO of high-fi bio and they're experts in modern immunotherapies. And this is a topic we've covered now for a number of years in a number of different forms and what is really a diverse field, but they're making some innovative.

Steps forward that we'll cover here in the second half of the podcast. So, Dr. Schweitzer, when you started the company, what were some of the major barriers to effective application of immunotherapies 

Liang Schweizer: immunotherapies still facing a lot of challenges due to complex biology, disease heterogeneity, and after PD, once launch There, there were, there has been limited successes in, you know, breakthrough immuno medicine.

So one of the things at high five bio is we try to understand immune context at the single cell level. So we think if we looking at a mixture of immune cells [00:18:00] or looking at diseases in a heterogeneous state, there are lack. Precision understanding of those biology that prevent you from better notion. So high five bio originally started with five scientific founders from different disciplines from physics to medicine, where they're thinking about using droplet setting, looking at single cells.

So they initially their approach is looking at single B cells looking at. Immune cells like B cells, bodies, whether that anybody is effective against specific imaging. So when I started the therapeutic aspect for this company, average the single cell platform where we start saying, if we could find anybody from the single B against certain immune targets and looking at, at the single cell level, we can find a beta.

That way. And [00:19:00] subsequently now five years later we have identified successfully eight clinical candidate, including a recent pandemic. COVID 19. When the outbreak comes, we, we were thinking about. The best effective way is go to the patients, identify the, anybody, the patients SSCT patients generates, where we can also produce those, anybody in a bulk order to help people that have immune deficiency or, or people, you know, can take the vaccine.

Figure out ways to against cancer. So, so that was one of the ways using our technology. Within six months, we started looking at COVID 19. If, you know, the, the patients still see their common lesson recovery from their own immune system, we could identify anybody's clinical candidates do in and D finding within six months, we move rapidly on that front.[00:20:00] 

So this is one of the power and differentiating point of high five bio, where we can use a world needing single cell technology identify quickly anybody's therapeutics for patients for immunomodulation port we have looking at anybodys that can marginate immune system fighting cancer or autoimmune diseases.

So, This is one way to co you know, address the challenges people are facing. The other part of the challenge current industry is facing is as you develop therapy, demotion immune system, you already know not every patient will respond to your drug, but there's no effective way to. Identify which patient population were responding to a drug.

So once again, we apply single cell approach, which we using the concept called drug intelligence. Science means you look at the scientific context using your drugs [00:21:00] mechanism of action to figure out what are the intelligence behind patient selection strategy. So we. Biomarker from single cell approaches to identify subpopulations where we'll be responding to a particular drug of your own development.

So in that sense we, we trying to, you know, bring breakthrough approach that could be potentially changed the industry practice. 

Kevin Folta: no, I like this a lot, but let's talk about a couple concepts that you introduced there. When you talk about this idea of single cell based approaches, is this because now most solid tumors, and if you're looking at things like, you know you know, non-blood types, cancers glioblastoma is a good example.

Other ones, these are rapidly evolving cancers where the cells inside the mass are changing. With [00:22:00] each division. And so you have a kind of heterogeneity or a, I should say genetic differences that are present within each cell of that, or well, different populations of cells within a solid tumor. And so is this why it's so important to be able to have single cell resolution to design therapies?

Liang Schweizer: This is one part of it. Clearly as you highlight it, Cancer is a very heterogeneous disease and not only, you know, different patients can have different specific types, even within the same patient. Looking at a specific tumor, they could be heterogeneity of different cells, have different genetic alterations.

So that's also one of the power of immune therapy. With immune activation, you could try to eliminate cancer cells even. Diverse genetic background. So but on the other hand the immune system, so, you know, surrounding the [00:23:00] tumors that we try to activate attacking the tumors also can be very heterogeneous.

So, so every tumors. Micro environment and each individual's immune system. And the way how we interact with the tumor could be very different. So we think only at the single cell level, you can get the accurate picture otherwise you. Go with average approach in some situation might, could, you know, provide you some notion, but in a lot of situations where you don't address this heterogeneity you, what missing the desired therapeutic outcome because of that?

Kevin Folta: Well, and you mentioned this concept of biomarkers, what is a biomarker in the context of an immunotherapy applic? 

Liang Schweizer: Yeah. So as we, you know, trying to figure out which [00:24:00] subpopulation could respond to your drug of development one of the aspects is to try to figure out a ways to stratify the patient and biomarker is associated.

Your approach is stratify patient for early days. And for immunotherapy, when we start already understand even, you know, one of the most effective immunotherapy PD one cannot have every patient respond to that drug. People start looking for ways to separate. Patients. And so, so people start looking at, for example tumor mutation burden or PDL one it's Nigen expression that that's very straightforward.

You could imagine, you know, if a patient, they, they have the receptor and the Nigen also high expression versus no way expressing. They might responding to the drug differently to me. So. Type of approaches where you could [00:25:00] start looking at, you know, a genes expression in PD, one situation you're looking at PDL one expression, or you could looking at a mixture like tumor mutation burden is a mixture of readouts.

As long as you figure out ways, Distinguish one patient versus the other. We call those approaches. The, the molecular signature you're looking at as a biomarker. So right now often, you know, when people looking for biomarker, they get a tumor sample, they do a Bo bulk analysis, which means, you know, the tumor and it's in ramen is heterogeneous, but you get a signal from the average of those different cells.

And we think, you know, that the concept of jock intelligence science is we think the average of those signals will mask a lot of true Biomark. Identification. So if you can separate them, although in that [00:26:00] situation, you could imagine each patient samples, you're not looking at one readout, you're looking at thousands readout.

The amount of information is gonna be. Constantly enhanced tremendously. So that's where we actually start, you know having a group data scientist to using machine learning, to, to try to dissect the complexity of the single cell data. Try to figure out what are the cell markers you know, differentiating from the cells that.

Does not respond to the drug or responding to the drug. So, so from that perspective you know, the single cell analysis bring as much higher risk notion to the. Drug response readout. And that's also one of the things associated with, with our company name high high-fi bio is high fidelity biology.

We wanted to really [00:27:00] reflect the choose of the disease setting and figure out. The patients that who might be responding to, to the drugs or not. 

Kevin Folta: When you talk about this idea of single cell profiling, and I really wanna make sure that I understand this for and, and communicate this for the listener is that by looking at a single cell, you are able to to identify discreet.

Potential therapies or antibodies that would work in that single cell environment and would be effective against that cell. Whereas that single cell as part of a mass of cells are part of a population of cells. That signal that that really describes its best vulnerability is lost because it's drowned out in the signal of all of the other cells.

So is, is that really what we're looking at is that this single cell approach allows you to develop therapies based upon that one, signature that, [00:28:00] and, and, and then go with it that may otherwise be lost. 

Liang Schweizer: Yeah. I think that, you know aspect of figure out a small population that could be a driving force where you could get the drug marginate, then they can amplify.

So you could imagine, you know, a patient initially they have a subpopulation of cells that without drug treatment. They were not having enough power to be in high tumor activity. And if you look at the patient, you wouldn't even be able to see those cells because they are just gonna be drawn in the signature.

But what, because you, they were gonna be just averaged out. You, you don't have a readout for that. And when you look at individual cells, you start seeing. Although it could be a subpopulation, but they can rapidly gain the [00:29:00] power through activation proliferation, especially such as exhaustive CD, eight positive cells where, you know, upon our drug treatment, there are certain patients have that.

TCE chronotypes where can they rapidly grow and activate to fight tumor so you can identify those subpopulation out and you, you can predict which patient may or may not respond 

Kevin Folta: to that. I, yeah, I think that's really, my next question is that if you identify in a single cell, a type of vulnerability or, or a place where you could design the drug target, that's in one.

In one cell in one solid tumor, for instance, or one population of cells in a solid tumor, right. Are there common mutations that we see pop up again and again that are shared between individuals that once you identify that biomarker, then you can apply that same drug to multiple people. [00:30:00] 

Liang Schweizer: Exactly Kevin, you brought up a really super important point is why every individual.

Is different. They're certain underlying mechanisms they're consistent. That's where our immune systems are building certain basic fundamentals we could share among each other. So what we are trying to figure out is what are the shared most common mechanisms among us to maximize the benefit versus, you know, itch individual is different.

You don't want to target specific. each individuals, which, you know, I, I cannot say it's totally ineffective, but it will be less effective. Compared with, if you understand underlying journal mechanisms where you could develop drug 

Kevin Folta: to more. No, very good. That really helps a lot. So if we talk about pipeline, what are some of [00:31:00] the drugs that are being developed right now for which specific cancers and how far along are.

Liang Schweizer: Thank you for asking, because we are very excited to, you know, share with everyone that we have. Currently two clinical candidate in phase one study. One is targeting TFR two. One is targeting ups 40. So as I mentioned, there are two type of mechanism. Whether you release the brake or hit the gas so far, those two, you could view as the molecules that hit the gas.

Because over the time we find out checkpoint inhibitor has been effective. People start saying why we. Develop immune agonist S immune response. That should be more effective than just release the break. So they. They have been quite a few efforts sent around that. So far the clinical outcomes is not very [00:32:00] effective as you could imagine.

Kevin sometimes people hit the guest too much. The, the therapy become toxic, right? They're too much side effects for the patient to tolerate. And there sometimes people don't hit the guess. The court doesn't go forward with it. So to understand the label of immune activation is super important and we can monitor that also effectively.

If we apply our single cell technology, we can given up drugs understand at the immune, you know, cells at the single cell level where. What level of activation we should be. And whether, you know, it might be possible bring general toxicity. So, so we have gained the learning from previous effort as well as now applying our own unique di S approach.

So we. Hoping will be one of the first in the world [00:33:00] who develop immune agonists 

Kevin Folta: for oh, very good. Just to kind of put it in average language, what kinds of disorders would these be most effective against? 

Liang Schweizer: Right. So, so in data you are asking what type of tumors. So actually we. When two indications where we have already applied our drug intelligence science approach, looking at single cell immune context, we find out if you are looking at all solid tumors right now, we, we are focused on solid tumor.

Only a subset of solid tumor with TFR two ox 40 modulation makes sense. So we, we selected indications based on our single cell immune profiling. So we are not going to all comers for all solid tumors. So that already. The first step enhance our, like the hood of success, but even wheezing, the tumor types, we see [00:34:00] the mechanisms applies.

We also realize there are certain individuals may not be, you know, effect responsive towards our drug treatment. So we went ahead applied the biomarker machine learning approach. We identifi. The common immune modulation mechanisms where certain patients, certain biomarkers can be predictive for responses versus you know, non-responsive population.

So, so we are now. In our phase one trials, we continually connecting those patient samples to do immune profiling, to validate our biomarker hypothesis from preclinical research. And we hope once we can ING the phase one study, when we go to phase two, we can select to the right patient population. We can design smaller trials with better response rate.

That could also changing the whole clinical trial design 

Kevin Folta: [00:35:00] and practice. Have you had successful trials and animal models or are these difficult to translate because they have something to do with the immune system. 

Liang Schweizer: So indeed it's always, you know, the struck between connecting preclinical data and the clinical data, the translation that has been a challenge in the field.

One of the aspects of animal models is certain times certain immune systems does not even, you know, corresponding to, to human tightly. So what we have been doing is to figure out, got Mo models that. Possible need translatable in a clinical setting by, you know, explore different possibilities. And on top of it, what we have been practiced consistently is in the preclinical setting model, we do X vivo experiment.

That means we obtain patient samples not treating the [00:36:00] patient. With the drug yet, because that is before we apply for I N D in the preclinical setting where you get patient samples, you culture them X Viv in a Petri dish where you treat them with the drugs and you can do single cell profiling that way.

So from that perspective, The translation in, you know, our analysis. And we are hoping to be more relevant than animal model even. And of course, with the caveat, those are not actual human patients. You're treating. You know, in a, in legal setting, it's in a dish. 

Kevin Folta: Yeah. And then we understand the limitations of all of that and that that's perfectly fine.

I guess the big thing I always like to think about is we kind of conclude discussion of new technology is what does the time horizon look like? And are there other companies that are applying, competing approaches? 

Liang Schweizer: I have seen other companies [00:37:00] and with more and more interest towards single cell approach because, you know, as I highlighted out Ernie on and the bulk analysis has its own limitation and sometimes could be, even be misleading.

So They are because corresponding to that, they are technology company, just developing single cell technologies for, for people from industry and academic to use. But I must say this is still at the beginning. And so far, very few people really put into the single cell practice at the clinical setting as we are doing.

So The other challenge is. mass amount of data, people gaining. How do you dealing with the data and come up with conclusions from that? So we have been investing that over the last few years. And so our data intelligence team has been able to connecting [00:38:00] single cell data from different tumor types.

So far. Now our single cell data covers eight. Cancer type and sex autoimmune type, and it's already over 7 million single cell transcript that we can put together and apply machine learning to figure out their identity and define sensitive versus resistant. Those are the work. it's just not anybody can jump in and start doing right away.

yeah. So it takes a lot of learning and pioneering and to figure out what's the best approach, but I'm confident when times goes on, there will be more and more. People 

Kevin Folta: interesting. Well, I, I, I laugh a little bit because when you say 7 million, transcriptomes, you know, I can think back to a time, not that long ago, where we were putting samples on atrics chips to interrogate 8,200 features and be able to, you know, so it two decades ago, [00:39:00] and to be able to think of now being able to, to have sequences from single cells representing 7 million.

Genotypes is amazing to me. And, and that's one thing that maybe we didn't talk about enough. That really is an important facet of your company's approach in, in why you had to have a team with physicists is this idea of the microfluidics that are involved. So when you're trying to separate single cells that have certain attributes, can you give me a little bit of a sense of what that is about?

Liang Schweizer: Yeah, I actually, you know, it's really fascinating when I first come across the single cell technology. Just from physics angle. We have the capability to generate droplet. At that time I heard about a thousand droplet per second. I, I already felt that was mind buckling, how fast to make my droplet.

And today we can make 5,000 to [00:40:00] 10,000 job led per. So , this is a progress we have made, you know, within the company. And we do have a group of engineers you know, experts of microfluid droplet, just thinking about a small droplet at the size of 40 pick eater, we have to be able to wrap a knife cell.

Inside that droplet. And we can track those activity of the single cell. They can secret the, anybody we can capture that anybody and sequence that cell to figure out what's the heavy chain night chain of that specific B-cells. And or if we are looking at T cells, we can look ATTC sequence looking at the Cy Chi is secreted because.

you know, no matter whether it's anybody secrets from BCL or cytokine from T-cell because of the droplet or the secretion is kept into such a tiny, small droplet, you can reach a high concentration that is detectable. So our. You know, [00:41:00] engineers not only can make the droplet wrapping the cells. We can detect the signal of activity of the cells.

Then we can subsequently sort it out that specific droplet and sequence that cell not only a specific genes, but the whole transcriptome. So, so. You know, when I think about the technology, how has been evolved? It's just amazing. When I was back at graduate school, we were involved in one of the first flow cytometry to this day 30 plus years later flow has been.

Whitely used, you know, in, in industry and academics. And I think singles another 30 years from now on will be 

Kevin Folta: Tru. Yeah. So just to clarify for the audience, you know, flow cytometry is just this process where you're able to move. Cells through a basically a narrow channel where you use a dye or some other kind of visual or fluorescent substance, to be able to learn things about the cell, whether it's maybe the content of [00:42:00] DNA or binding of a certain.

You know, two molecules together, a number of different things you can figure out, and then you can use this in cell sorting, move them to one side or the other. What we're discussing here is a microfluidics level. So where droplets that are, what did you say? 40 Pico liters. So Pico leaders, it's 10 to the minus 12 leaders.

Yeah. So think about that if so trillions of a liter, and then inside there you have a cell and then that cell is producing an antibody that is binding with its target and, or, or not. And so they can determine using their microfluidics platform, whether or not they have an antibody that's interacting with the target or not.

And so you get hits, you get non hits. And so the beauty of this is that it'll, it's all sorted. And then you can go ahead and look at all the hits and take those apart. Using bioinformatics, understand the, the DNA sequences that are the RNA or the [00:43:00] sequences that underlie. The production of those heavy chains and light chains to make these custom antibodies that are binding these custom targets.

Did I get that correct? 

Liang Schweizer: You summarize beautiful me. 

Kevin Folta: okay. I just wanted to make sure I got that right. Cause I, I think I understand this. I think it's so cool. And I, and it makes me think of things I do in my laboratory now at how I could do them on a different scale. And, and it really is very, very exciting.

Liang Schweizer: And I wanted to just add one more level of interest here is we now learn not only putting one cell in the droplet, we can also put two cells in the droplet. So just imagine, you know, you can looking at a secreted. A, B cells created certain, anybody binds to a cell that have the expression of the Enogen, or, you know, if you see an immune cell attacking a tumor cell, you know, and [00:44:00] so, so there's a lot of possibility when you start can putting two or three cells into that job, let, to look at the biology and we can ate the jobless size according 

Kevin Folta: to oh, absolutely.

You just increase your through. And it's very exciting. Yeah. One of the other things I noticed from the website is just the global presence of the company. And is that something that really is just exploiting the diversity of talent that's out there or does it also have important implications for diversity in patience?

Liang Schweizer: Thanks Kevin for bring this up. Indeed we are small startup, but with the global presence one of the thing we think is as you point out, clearly there are diversity among patients. We wanted to see no call medical needs and why we are trying to understand certain common unin and scientific.

Mechanisms center around immune imagination. We clearly also would like to [00:45:00] understand the differences among different patient populations. One other aspect that I think it was super beneficial for us is to access scientific syncing at a global level. And. You know, would probably see from our website, we promote open innovation concept.

That means when we start develop innovative therapies, we not only do it on our own, we wanted to work with the top scientific leaders and, you know, clinical researchers global need to. Come up with innovative therapy and so far, you know, our presence in us Europe and China has been really enable us to start setting up multiple collaboration, scientific collaborations advisors at different continents.

And You know, last but not least, as you also mentioned the talent diverse pool of the talent, we, we could bringing people with different expertise [00:46:00] and different thoughts. And we talked about, you know, diversity brings. The innovation to the next level. And that's what we have been benefit is. Oh, 

Kevin Folta: very good.

I think one of the things that this podcast does for a lot of people is keeps them informed of the latest innovations and the companies that are producing them, but also maybe some of the products and some of their applications. And so if you had to get out the crystal ball and make a prediction going forward, what would you imagine might be the first big drug and what problem would it target?

Liang Schweizer: You know, I, I don't want to sound too boast. boasting on that one, but but I, you know, just Kevin, to your question of my prediction of the future breakthroughs, I do think immune modulation could be one of the next you know, breakthrough because we really have a lot of healing power within ourselves.

And the question is how to come up with the. [00:47:00] Approaches. And I think combining single cell and immuno donation, deep understanding of the knowledge and anticipating now with more and more, you know, power of machine learning, AI type of approach it will bring. The next breaks are serving for patients.

And, and that's what we try to practice 

Kevin Folta: at high power. No, very good. And you know, you are such a scientist and I adore that and I appreciate your conservative nature because I wear a scientist hat in a lab coat myself, and I never like to put the card ahead of the horse, but at the same time we have listeners who desperately.

Need a, a cart and a horse. And so this is why I bring that up. It just is maybe a way to get people hopeful that good solutions are coming from innovative approaches. So I guess the last question is if people wanted to learn more about high five bio, where could they find out more from either a website or possibly from social media?

Liang Schweizer: Indeed Kevin, you can find us [00:48:00] small details@wwwhifi.com. We are also have presence in LinkedIn, Twitter, Instagram, 

Kevin Folta: self Pfizer. Thank you very, very much for speaking with me today on the podcast. And I hope you can come back when you have some big breakthroughs. You'd love to talk. 

Liang Schweizer: I would love to thank you very much, Kevin, for your time.

It's such a pleasure. And once 

Kevin Folta: again, we hear about a big innovation and a new technique to solve an important problem. And to me again, it just brings the idea of hope. Through new technologies. And these are things that, you know, me as a, as a biotech aficionado and someone who studies the literature that even I don't know about.

And I'm learning about as we go and we're doing this together. So if this is what we're learning week to week, imagine what else is out there too. So awesome. That high five bio is in this space and creating these new solutions and hopefully being able to bring cures for the diseases that really are problematic to [00:49:00] us.

So, thank you very much for listening. Once again, tell a friend, write a review on the place you consume. Podcast media. This is the talking biotech podcast, and we'll talk to you again next week.