00:00 Welcome in, Michael Murray with Benzinga, joined here by Vin Singh, the founder and
00:06 CEO of Bullfrog AI.
00:07 Vin, it's great to have you with us this morning.
00:09 How are you?
00:10 Great to be here, Michael.
00:11 Thank you.
00:12 Pleasure to have you and Bullfrog joining us.
00:13 Let's get started with a quick overview of your company.
00:16 What does Bullfrog AI do?
00:17 We're an AI-enabled drug development company.
00:21 Our mission is to revolutionize drug development.
00:24 We have a proprietary AI.
00:26 Actually, we have multiple platforms.
00:29 We do have one from the Johns Hopkins Applied Physics Lab.
00:32 Really, our focus is to reduce the time and cost and increase success rates in drug development.
00:39 Can you talk to us a little bit more about BFLEAP?
00:42 How exactly does that work?
00:44 So BFLEAP is our proprietary platform from the Johns Hopkins University Applied Physics
00:49 Lab.
00:50 We have worldwide exclusive license to this platform.
00:53 This platform has been successfully used in different sectors by Johns Hopkins APL.
01:00 Our focus is drug development.
01:02 It has an amazing ability to predict targets of interest, find patterns, relationships,
01:08 anomalies in large, complex datasets.
01:13 And when it comes to clinical data, real-world data, those are very large, complex datasets.
01:19 So it's an ideal tool to solve the problems that exist in the development of drugs.
01:26 Excellent.
01:27 And then what is missing in drug development that AI can provide on a more general basis?
01:31 Well, what's missing is there's a lot of data out there that's been collected over the years.
01:37 And it's surprising to learn that even today, big pharma spends 10 to 15 years and $1 to
01:43 $2 billion to develop a drug.
01:46 And in their final stage of clinical testing or phase three, they still fail about 50%
01:51 of the time.
01:52 So clearly there's something missing.
01:55 And what's missing is a tool that can effectively analyze that data and uncover insights and
02:03 help direct further development of these drugs, help better stratify patients so that we can
02:11 have more success in clinical trials.
02:14 Excellent.
02:15 And you announced a new preclinical study to evaluate the efficacy of BF-114 in obesity.
02:20 Can you talk to us about the drug specifically and how the study is going to be conducted
02:24 as we move forward?
02:25 Yeah, this is a really exciting opportunity for us.
02:29 And as you and your listeners may know, obesity is maybe the second hottest topic in the world
02:34 behind AI.
02:36 And there have been a lot of early stage, massive early stage deals done in the obesity
02:40 space by big pharma.
02:42 It is a very large market.
02:45 As we know, obesity is a huge problem in the US and other developed countries.
02:50 We think it's going to be about $70 billion market plus by the year 2030.
02:56 So we have a drug that we've licensed from George Washington University.
03:01 It's an siRNA drug.
03:05 And this drug is designed to target a particular gene.
03:10 And we think this will have an impact on obesity.
03:15 We have some preclinical data to support this hypothesis, not only for obesity, but certain
03:22 fibrotic liver diseases.
03:25 What we are going to do now is to kind of continue with that progression and conduct
03:32 an animal study, an animal study with Dr. Randy Sealy from the University of Michigan.
03:40 He's a global expert in preclinical animal studies, targeting obesity.
03:49 And he's well known and respected by big pharma.
03:53 So we have the best person in the world probably to conduct the study for us.
03:57 And the goal is to really determine the ability of this drug to lead to weight loss in an
04:07 obese animal model.
04:09 And also to help us better determine the mechanism of action.
04:15 Most obesity drugs are focused on appetite suppression.
04:21 This drug does not appear to have that mechanism of action.
04:25 It has something different and something very intriguing.
04:28 And we'll get the answers in about five months from now.
04:32 Got it.
04:33 Vin, the final question for you as we close, and thank you for all the context thus far.
04:36 As you look at the industry in general, where will AI be in 10 years in your estimation?
04:41 In 10 years, I think AI will be an integral part of the entire drug development process
04:49 for pharmaceutical companies going from discovery all the way to commercialization.
04:54 We're obviously playing a role in that entire continuum.
04:59 But I think it'll be something that's fully integrated and adopted by big pharma as well
05:05 as biotech.
05:06 They're a little bit slower to adopt these types of technologies, probably mostly related
05:12 to cost.
05:14 But I think in 10 years, you will definitely see that.
05:18 And the end result will be far more success, which will help more patients, which will
05:24 lead to more affordable drugs, less failures out there, and I think overall, healthier
05:31 society.
05:32 Wonderful.
05:33 Vin, it's been an absolute pleasure having you here today.
05:35 We appreciate you taking time out of your schedule, joining the Benzinca audience and
05:39 sharing more about what you're doing and the industry as a whole.
05:41 Vin Singh, founder and CEO of Bullfrog AI, thank you again for being with us.
05:45 Thank you.
05:46 Great to be here.
05:51 (upbeat music)
Comments