Michael Freeman: Hi, Jennifer and team, thanks so much for taking my questions and congratulations on a big year, patent awards and productizing BioStrand – these are no small feat. So congratulations on all that big work.
Jennifer Bath: Thank you, Michael.
Michael Freeman: You’re very welcome. You’ve described so many capabilities of your various platforms. And I wonder, maybe as a simplifying exercise, could you describe maybe like what an ideal customer for IPA today looks like? And how – like how might that customer start and how might that customer be converted into some of sort of your – sort of highest value-add product offerings through IPA, that would be really helpful?
Jennifer Bath: Oh that’s an interesting question, Michael, because I look at each of those revenue pillars as kind of distinct opportunities that all have really unique benefits and all, I think, in their own way, contribute in a highly profitable way for BioStrand and IPA. So it’s a little difficult to choose one as an ideal client. But what we’re seeing, I think, quite rapid adoption in, is maybe a good example. Because I think that rapid adoption into that wet lab in silico combination is probably a little bit lower-hanging fruit and faster adoption for our clients because of the fact that they’re already using the wet lab capabilities. So, if they come in, they’re meeting with our sales team. They’re having this conversation with the scientific team at IPA.
As we’re exploring how to address and solve the problem they’ve brought forward, it’s a very natural conversation for us to bring in all of the in silico capabilities that we have now added that can be integrated directly into a wet lab program very seamlessly. But give them more insight, give them more diverse antibody candidates, give them more information about the safety and the potential efficacy of the actual antibodies that they’re analyzing. And even give them information about the possible negative effects of those drugs once they get into patients. And so, by adding all of these things into the wet lab, not only are we really increasing the size of those programs for those clients, but we’re introducing them into the in silico capabilities.
We’re showing them the power of what we’re able to do. So not only is it kind of easier access to those kinds where we’ve got them on the phone with the right people on our side, the right people on their side, but we’re going to give them a taste of what we’re capable of doing. And so, I think that’s probably quite a natural entry point for a number of our clients, because that communication is already happening, right? We’ve already got the key decision-maker in that company. And then from there – in this client right now that has the $640,000 in codes right now for BioStrand is a perfect example. That’s exactly how this happened and from that conversation with the same key decision makers. We were then invited to meet with them around the de novo in silico programs, of which now they are looking to launch three.
And now also, they have put us in contact with the person that was recently hired to manage 15 years of disparately – collected data that is sitting in silos at their company. So that’s kind of a perfect example of how this would cross-sell and upsell quite naturally through the initial conversation.
Michael Freeman: Brilliant, okay that’s super helpful, thanks so much. And last question from me. I wonder if you could comment on your cash needs during the next 12 to 18 months?
