12.8.21-DemoDay-Joesph-Azzarelli

JOE AZZARELLI: Joe Azzarelli, founder of Kinovi, and my connection at MIT is-- I graduated from the PhD program in 2016 in the chemistry department. And some of this technology has some origins there which we're really excited to take forward.

So we're focused on delivering a new suite of data analysis tools for early stage drug discovery teams. And as many of you may know, drug discovery is expensive. It's time consuming, and it's very risky. Even within the early stages of top tier pharma development programs, the probability of regulatory and technical success is typically less than 6%. And this really contributes to a lot of the overarching costs of getting a drug to market and getting it into patients' lives.

And so we think there's an opportunity there to transform that approach by bringing kinetics or kinetic binding information to much earlier in the screening paradigm. And what we've heard from many customers is the desire to do this but the inability to do it, because it's just unfeasible from a temporal perspective in terms of throughput.

I show here our comparison to cytiva, the Biacore 8K. That's the state of the art SPR tool that's used to collect kinetic binding information. And if you were to screen a $1 million compound library, which is a pretty typical size, it would take you greater than a year to get even a single shot screen. And that's something that we could complete in less than a month. So we think that's going to really change how people's approach [INAUDIBLE]

[INTERPOSING VOICES]

JOE AZZARELLI: So our solution is based on an underlying technology called conformational dynamics electrotransduction, or CODE for short. And what's important to note about that is that unlike many other techniques, it's not reliant on any sort of mass based measurement. And that allows us to interrogate kinetics on-- number one, on an electronic platform. So we can scale the volume of interactions that we screen to tens of thousands of interactions simultaneously. And that's the first part.

And the second important takeaway is that we reduce the need to have a weight based measurement, which allows us to interrogate really traditionally very difficult drugs to investigate, like GPCRs and other large transmembrane proteins. Additionally, it allows more complex information to be gathered. So instead of a simple kon or koff you can also get orthostatic and allosteric experiments and biased agonism experiments, all of which are important to the drug discovery today.

So how's our technology work or how is it used? Typically, it fits into a conventional funnel, but it optimizes that funnel. So ideally you're shortening your high throughput screening step, but you're also broadening the funnel, because you're able to screen more compounds and get much more interesting information along the way.

It also simplifies a lot of the experiments that people normally struggle to capture genetic binding data for. And that can really be useful in terms of providing key go or no go information, which then ultimately improves the probability of regulatory technical and regulatory success.

So where we're at right now is we're seeking partners across two different areas of interest. The first is pilot partners or clinical validation partners who would actually like to see this technology input into their existing portfolios, either as typical big pharma customer or CDMOs that are servicing other customers. The separate area that we're looking for partnerships in is in helping us scale up our production of key protein components that are utilized to manufacture our chips.

So with that, I'd love to discuss this opportunity further with anyone. My contact is joe@kinovi.com.

SPEAKER 1: Thank you, Joe. Great to hear. First question for you-- how do you tend to work with corporates? What are you looking for first?

JOE AZZARELLI: Yeah, certainly. So in terms of the biopharma partners, the simplest way to start is actually to have them perhaps identify a target that they're interested in right now or a target they've already validated. And they can actually send us compounds that they might already have the validation profile on.

We can send them the data back, and that's a really easy first step to validate our technology against a known set of compounds. And then once we've taken that step and establish that it does, in fact, work for their trial compounds, then we would go forward into a more conventional service model where it would be a fee per compound analyzed.

SPEAKER 1: Got it. And what are you mostly focused on right now developing, and what's the roadmap?

JOE AZZARELLI: Yep. So right now we're focused on expanding the number of targets that can fit into our platform. We have a really strong focus on GPCRs at the moment, although we do have interest in other transmembrane proteins, as well, and even non transmembrane proteins. And the roadmap is currently, as I mentioned, focused on a service model.

Our lab is actually based in Boston. But over the next year and a half or so, what we're actually seeking to do is identify basically their marketing requirements documentation that's utilized to advance towards bench top instruments that folks could utilize outside of Boston, for example, in their own facilities.