SolverGen is a 2019 Pitch for Purpose impact startup Finalist

Hi everyone, my name is Jane and I'm a molecular biologist with over 15 years of experience in the life science industry. I've had the opportunity to work both in academia and biotech and spend most of my career doing cancer research and developing cancer diagnostics. Cancer is a huge problem worldwide and right now we're treating cancer patients largely with a one-size-fits-all approach that doesn't account for their individual uniqueness. And at Sovrogen, we want to bring personalized medicine for cancer patients, allowing them to be treated with medicine that's tailored based on their individual biology. This is going to improve treatment success and reduce unnecessary treatment and improve care. And we have an opportunity— amount of genome data. This is the blueprint of our DNA and raw material that contains insights that can help us to design I'm sorry, but—

It looks like the presentation—

Just stop.

Yeah, why don't we start that again?

Just keep talking. Just keep talking.

Okay. And we have an opportunity because we have all this genome data available, but it is very difficult to mine genome data insights, and most biomedical research scientists will tell you that they don't have the know-how or the resources to do it. And currently available solutions are mostly siloed and on a platform unfit to be used in a clinical setting. At Sovereign, we are changing the current paradigm of how genome data insights are discovered and translated by being a software platform that takes you from discovery to translation on a single platform to really expedite the process. And you biomedical research scientists to take genome data and correlate it with clinical information and using machine learning technology to figure out the best drugs that's going to be responded by the patient based on his or her genetic fingerprint. And that will help the clinicians design the best and most optimal treatment regime for the patient, whether it is standard therapy or standard therapy plus/minus other types of drugs. Our software platform compared to the current solutions is much easier to use, it's more powerful analytically, it's more accessible, and last but not least, we are designed with clinical use just cases in mind, complying with regulations such as HIPAA and PPEDA. And it could be as simple as logging in, uploading that data from the patient, and perform the design analysis pipelines, which can show us all the unique biological features of the patient that can tell us the best drugs to use for him or her. We're in a $65 billion industry that's growing at around 11% every year, and we're spending about $1 billion now on genome data analysis for cancer research and application. We'll have two different revenue streams. For scientists who want to use our platform to mine insights, we'll be charging them a monthly subscription fee. And once that insight is developed and validated and ready to move to be used in a clinical setting, we'll then be charging the hospitals on a per-sample or patient basis. Within 3 months, we have already gained the collaboration support from champion scientists to work with us and also seed funding to help us move forward to the next phase of our development. Product development. We're in a really unique position being a hybrid platform that crosses its use from the research space into the clinical space, and we're backed by a team of experts that come from science, business, and technology. And right now we're just looking for additional resources and funding to help us to execute the full vision of the platform. And thank you very much for listening to me, and sorry for the sideways.

Alright, well, thank you. You know, look, we can't always get our heads straight, so to speak. So judges, welcome to the screen. Do you have questions and/or feedback? Maybe we can start with some questions. Christine or Noah?

Yeah, so a couple of initial questions. One is Who's on the team right now that's actually working on it full-time, or if it's just you, kind of understanding where you are in that process, you know, who's the next person that you really need to hire?

We— I am working on this full-time. I'm also working with a software development company as well as other software developer contractors who are helping the MVP development. And we are in the process of signing formal agreements with the collaboration scientists that I've just mentioned. And I have personal network with many, many different actually researchers within this field that are willing and in the process of basically discussing what type of role they might play in the team. Right.

Who is it that you're— what's the most painful lack? Like, you know, when you're starting a company, like, oh, I wish I had this person. Like, who's that person you really need to hire full-time first? Is it research? Is it a software person? Is it a marketing?

So the current, the current, I want to say there are different, there are difficulties in, in all, in different aspects. But I want to say the most immediate gap that we have right now are really just that group of technology people who can develop the product.

So they can build that app. Yes. And then where— and then my other question was about data sources and, you know, how you're thinking about data sources. You know, is there— not being in the cancer space or the genomic space, you know, is there a critical mass of data that you need to acquire? Sort of how does that work? Or is it piece by piece based on types of cancer?

The sources of data can come from several different ways. One of the largest Source is actually from these global alliances that have formed to actually accumulate a wealth of these tumor data. For example, probably the most well-known is the one that was funded by the NCI, the National Cancer Institute, the Tumor Genome Atlas program that have a collection of, I believe, something like 22,000 tumor samples tumor plus normal parastampel data available for researchers to access and to mine. Another similar initiation is called the International Genome Cancer Consortium. They are aiming to provide another 25,000+ tumor samples. And there are several other types, these type of large initiations around the world trying to accumulate it, accumulate data and allow it to be accessed by the research community to mine.

Noah, it says e-tech. Sorry, the other sources that we got a lot of questions coming in the chat.

Yeah.

Okay.

So I just want to be sensitive to get the judge questions and then the chat questions and all in it. Christine, do you have any other quick questions?

I'll give— I'll throw the ball to Noah.

Noah, yeah. How do you plan to differentiate from Foundation or NantHealth, you know, that are already offering products in this arena?

Our vision is, our vision is to actually provide a more open source platform. So allowing researchers to take, to analyze data that come from a varieties of different types of technology as well as researchers who are at different stages of their development. So somebody who is at a very beginning stage where only they have a— but want to leverage our platform's clinical utility aspects of it to actually do the technology transfer, the insight to move into the clinical space. So in that sense, we are trying to meet needs from different stages as well as being a more open platform.

Will you contribute your data back to the community somehow? Do you plan to share outcomes data back?

Do you mean by the data who— the data is being brought to be analyzed on our platform from our users?

Yeah, I guess, will there be a way for doctors to contribute outcomes information back to the platform to share with others in an open manner?

That is certainly something that we will consider doing. But first and foremost, we want to be just a net powerful analytical platform for people to really take from the early stage discovery and have a vehicle to move their knowledge into a clinical setting.

Okay, we got a lot of questions coming from the chat. Noah, I'll throw some in and then I'll give you guys opportunities to, to come up with others. Philip was asking, does— and try and keep like super short answers because I got a lot of these questions. Does SolverGen facilitate the initial genomic mapping?

No, we did not.

So you're taking data from other sources. Craig was asking, what is your technology built on? IBM Watson, question mark.

We're going to use the latest cloud tech, whatever is the fastest and the most flexible to deal with, for example, moving forward, combination of on-premise and hybrid cloud environments.

Right. So I think the IBM Watson question might imply like, are you using also any sort of off-the-shelf AI?

We will be developing our own. And also we will have a standardized— we'll have an in-house made AI system to analyze data, but we'll also allow researchers to come and bring on board, integrate their own developed algorithms and models.

Okay. BM, acronym for something, asked, how do you— how did you or how have you come up with your pricing model?

This is actually the pricing model is, is comes from surveys done from the very users that we're trying to target. So these are clinician research scientists who are right now doing this type of work using their, the current solutions available and what they're comfortable with paying. And the model for the pricing model for the hospital charge is actually research done by comparing some of the currently available offers. Offerings on similar type S of platforms used in the clinical setting. Okay.

Right. So you have, you mentioned a couple different kinds of customers, right? In that answer, which is a good segue into Mark's question, which is, who is your customer? Those seeking treatment, clinical trial organizations, pharmaceutical companies. You just mentioned hospitals and researchers, but if you could be more specific for Mark, that would be great.

So there will be two major, there will be two different categories of users. The first category are really the biomedical researchers that fall within the clinical and translational research. And they can come from academia, they can come from industry setting, either a biotech or pharma. And they will be, those are the people who will be paying a monthly subscription fee for using our platform to mine insights. Now, once those insights are mined and go through all the validation, studies that is required to be accepted and considered to be used in a clinical practice and move forward into the hospital setting, for example, as a clinical test, that's when those are the other, that's the second type of users that we have. And those are, that's the pricing model for those users will be on a per sample or per patient basis. So to—

Okay, we gotta go, we gotta go faster though because we got a lot more questions. I want, And I'll just call it in a minute, but I'm— what are you facing compliance issues in the US or you're just focusing on Canada at first? Was another question.

We'll be targeting, we'll be targeting both. We're targeting the North America market first because that's all that, that market from North America occupies almost 50% of the entire market. So we'll be dealing with, we'll be complying with HIPAA and PPDA, which is the Canadian version of HIPAA.

Okay. Wilson was asking, how do you guarantee any accuracy with the analysis? How do you deal with the potential of wrong diagnosis?

Well, for a test to be used in a clinical setting, they have to obviously pass rigorous tests. One of the three— the three major criteria is actually clinical validity, clinical utility, and clinical reproducibility. Reproducibility. So regardless of the platform that researchers use, they will have to pass those 3 tests, and those are determined by peer review, publication, and other type of regulatory.

So you're just a tool facilitating, you're not necessarily—

But our tool— Yes, but our tool will help at least 2 of the 3 aspects, which is the reproducibility and utility.

All right, before I go on to any other quick questions from the audience, and there are a lot, I want to turn it back to either Christine or Noah. So you got some questions peppered out. Do you have anything else you want to add, Christine or Noah?

Yeah, the one thing that— actually, this is from the chat. I'm going to pull from the chat. So thanks, Khalid. Someone had mentioned veterinary applications, and that's often interesting just because then you can get some field use without having the regulatory issues. Is that something that you guys have looked at?

This is an interesting question. This platform obviously is not unique to just human or cancer. It is a general— it can be applied in a variety of different situations. So while we primarily will be focusing on cancer in humans right now, which I think has a real big demand and needs right now, but this is certainly another application this platform can have.

Yeah, I was wondering, you just Trying to understand a little bit from your description of how the product will roll out. Is it— will you be able to treat patients from, you know, from early on, or do you need to sort of go through an acceptance phase before you're able to treat patients? When used for treatment.

So you mean once it's developed, is it able to treat the patient, use it on a patient right away?

I guess, do you have a validation phase of the technology that you need to sort of pass through before you can position it, you know, go take it to market for patient treatment?

And usually how it works is that it will probably be used at a few example sites, a few major sites to roll out. And then once that, once there's been more success seen from that, it can be rolled out to more different sites in general.

Yeah, let me clarify. I think primarily Primarily its use is going to be, and correct me if I'm wrong, by the researchers doing the analysis of the problems, coming up with clinical analysis, and then once that research is done, a few stages down the line, it may materialize into something that would be a clinical trial. Is that accurate in terms of its placement in the—

There are several ways to push a test into the— to be used in a hospital setting. The one way is, as you have described, once the test is designed, it will be tested in a clinical trial. If proven successful, then moves into clinic. There, however, there's another accepted path to that as well. If the researchers discover their develop their test based on basic 2 or 3 Phase 3 trials, for example, that itself is also enough evidence to move forward to clinical space. So there are a couple of different ways to go about it.

And what's your traction so far in terms of the actual product? How much of that has been built out? What milestones have you already hit? And, you know, how long is it going to be before you hit those next milestones that let you kind of get it into people's in people's hands?

We, we are building out the first couple of phases of our MVP. Within 6 months, we should have something that will be usable for some basic features that the researchers can already test out.

Yeah.

So it's like pre-seed, seed stage.

Yeah.

Um, all right guys, we have a ton of questions in the chat. Let's do this. And I wanna start bringing on our next one.