Lantern Pharma Inc. (NASDAQ:LTRN) Q3 2023 Earnings Call Transcript

David Margrave: Sure, sure. We have an aggregate of over 95 SG patents and pending patent applications. We have a strong patent position in each of our lead product candidate areas for LP-300. We have claims extending into at least 2032 for LP-184, we have claims extending into at least 20 41. And for 284, we have claims extending into at least 20 39. I think one very interesting thing we’ve seen with our RADR platform is that it’s also a great generator of new insights that you can then use to further expand your IP position. And we expect to continue that. So we are actively filing. As you saw, we described what we did in Q3. We will be actively filing and further building our IP position in coming quarters as well.

Panna Sharma: Thanks, David. Another question we have from Sean. Sean, thanks for your question. His question, what are your expectations around the pace of RADAR data accumulation in 2024 as you look beyond the 50 billion data points anticipated by end of 2023? That’s a really good question. It’s a very exciting question. Well, I think we’ll have a talk sometime in January or maybe early February, specifically around our RADR platform. But I think we’ll probably pass $50 billion in the next month or 2 easily. And we’re developing internal goals, but we’re thinking kind of a 3 to 4 increase for next year. So we’re looking at – we’ll probably easily get to $100 billion. So we’ll double that number, maybe get to $150 billion to $200 billion.

A lot of this is going to depend on what the quality of data sets are. We have a couple of initiatives internally. Again, we’ll talk about them later, around engineered data sets and extracting data from data that’s already available. Second, we’re also thinking about scraping, doing large-scale automated scraping from the right kind of quality publications. And we’re also looking at better and automated feeds from some of the existing more enlightened publications and systems that are doing machine-readable data format, machine-ready kind of data extractions look like through JSON files or other kind of configurations. So we have a number of things, I think we’re going to crush that $50 billion number next year, I think it could be a quarter at least 2 and maybe up to 4x that.

But yes, it’s a great question. And more importantly, it’s not just the data, it’s really the normalization and curation of the data and then, of course, the algorithms so you can make sense of all that data. Well, with that, I would like to thank everyone for participating. I know we had a lot of really good questions. And there being no further questions. We’d like to conclude today’s call. Thank you.

David Margrave: Thanks, everybody.