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Big Pharma Fails 50% of the Time in Phase Three. AI Can Fix That | Vin Singh, BullFrog AI

49 min episode · 2 min read
·
Vin Singh

Episode

49 min

Read time

2 min

Topics

Relationships, Investing, Startups

AI-Generated Summary

Key Takeaways

  • Phase 3 Failure Economics: Big pharma fails 50% of Phase 3 clinical trials despite each drug requiring 10–15 years and $1–2 billion in development. A primary cause is selecting the wrong drug target early. AI-driven causal analysis that identifies root-cause genes — not downstream markers — can eliminate this foundational error before billions are committed.
  • Causal AI vs. Pattern AI: BulFrog's BF Leap generates 6 million causal models in 30 minutes, determining not just whether gene relationships exist but their magnitude and direction. This distinguishes root-cause genes from downstream effects — a critical distinction because drugs targeting downstream genes frequently fail mid-development when the true biological driver remains unaddressed.
  • Neuropsychiatric Target Discovery: Using exclusive postmortem brain data from the Lieber Institute's 5,000+ brain repository, BulFrog identified driver genes for major depressive disorder, bipolar disorder, and schizophrenia in months — work Lieber had pursued for over 15 years. These novel targets, sourced from a dataset unavailable anywhere publicly, are now being pitched to major pharmaceutical companies.
  • Data Readiness Gap: Over 60% of companies lack AI-ready data, making BF Prep a strategic entry point for BulFrog. The platform converts unstructured data — including handwritten clinical notes and PDFs — into clean, structured formats in hours or days rather than the months a human team would require, opening doors regardless of whether clients proceed to analytics.
  • Pharma Sales Cycle Reality: Deals with major pharmaceutical companies typically require 12–18 months of relationship-building, beginning with small pilot projects before progressing to multi-million dollar contracts. Companies seeking pharma partnerships should budget for extended sales cycles and prioritize delivering on pilot commitments, as more than 90% of existing AI-pharma deals are currently missing their stated milestones.

What It Covers

Vin Singh, founder and CEO of BulFrog AI (Nasdaq: BFRG), explains how his three-platform AI system — BF Prep, BF Leap, and BF Arenas — targets the 50% Phase 3 clinical trial failure rate in pharma by improving data quality, causal gene discovery, and drug target selection.

Key Questions Answered

  • Phase 3 Failure Economics: Big pharma fails 50% of Phase 3 clinical trials despite each drug requiring 10–15 years and $1–2 billion in development. A primary cause is selecting the wrong drug target early. AI-driven causal analysis that identifies root-cause genes — not downstream markers — can eliminate this foundational error before billions are committed.
  • Causal AI vs. Pattern AI: BulFrog's BF Leap generates 6 million causal models in 30 minutes, determining not just whether gene relationships exist but their magnitude and direction. This distinguishes root-cause genes from downstream effects — a critical distinction because drugs targeting downstream genes frequently fail mid-development when the true biological driver remains unaddressed.
  • Neuropsychiatric Target Discovery: Using exclusive postmortem brain data from the Lieber Institute's 5,000+ brain repository, BulFrog identified driver genes for major depressive disorder, bipolar disorder, and schizophrenia in months — work Lieber had pursued for over 15 years. These novel targets, sourced from a dataset unavailable anywhere publicly, are now being pitched to major pharmaceutical companies.
  • Data Readiness Gap: Over 60% of companies lack AI-ready data, making BF Prep a strategic entry point for BulFrog. The platform converts unstructured data — including handwritten clinical notes and PDFs — into clean, structured formats in hours or days rather than the months a human team would require, opening doors regardless of whether clients proceed to analytics.
  • Pharma Sales Cycle Reality: Deals with major pharmaceutical companies typically require 12–18 months of relationship-building, beginning with small pilot projects before progressing to multi-million dollar contracts. Companies seeking pharma partnerships should budget for extended sales cycles and prioritize delivering on pilot commitments, as more than 90% of existing AI-pharma deals are currently missing their stated milestones.

Notable Moment

BulFrog's pancreatic cancer analysis identified a patient subgroup whose mean overall survival increased nearly threefold — from roughly two months to six months — by pinpointing a precise biomarker profile within existing trial data, demonstrating that buried precision medicine signals can be extracted from datasets already collected.

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Episode Transcript

The point of this is to increase likelihood that a clinical trial will succeed. Considering it takes ten to fifteen years and 1 to $2,000,000,000 to develop a drug, it's quite shocking that big pharma fails fifty percent of the time in phase three. Are you concerned about competition from Big Pharma who may be developing We discovered the biological drivers of those diseases. We believe we've discovered the genes that drive depression, bipolar, and schizophrenia from a one of a kind dataset that does not exist anywhere in the world. It seems that you would be an acquisition target by Zing pharma. Let's see if we can get one of these drug discovery AI deals done or target discovery deals done. Introduce yourself to listeners, how you got the Bullfrog. Craig, thanks for having me today. Great to be here. So, you know, my name is Vin Singh. I'm the chairman, founder, and CEO of Bullfrog AI. We are a publicly traded company under the symbol BFRG on Nasdaq. So, obviously, there are certain things I won't be able to say or questions I might not be able to answer, but looking forward to it. So, a little bit about me. I have almost thirty years of industry experience, life sciences, biotech. I'm a biomedical engineer by training. I'm a three time founder of investor backed companies. Two of them have gone public. The first company I cofounded is a company called MaxCyte, symbol is MX CT, as a cell therapy systems company. When they went public on Nasdaq several years ago, there I think the market cap was around 1,500,000,000. Obviously, biotech's been beaten down pretty hard, over that period of time. After that, I founded a company called Next Healthcare, which was at the time the world's first adult skin cell and stem cell banking company for regenerative medicine applications. And that company is still operating and doing some different things today. And then about eight years ago, I I founded Bullfrog. And, the reason I founded the company was I I was, you know, very surprised by the high failure rates in late stage clinical development. And, you know, considering it takes ten to fifteen years and 1 to $2,000,000,000 to develop a drug, it's, quite shocking that big pharma fails fifty percent of the time in phase three. It doesn't it didn't make sense to me. And I also realized if I could make a difference, there's a lot of people that will benefit from drugs that maybe otherwise wouldn't. And I think, the trickle down effect would be, you know, drugs would be more affordable in general, if you have more success. Right? Because somebody's paying for all those failures. Right? And it's unfortunately, it's the health care system that's paying for it. So, you know, I started the company and that the the original focus was why don't we try to rescue failed drugs because there's like a ocean of them out there. …

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Keep Reading

Books, tools, and gear mentioned in this episode

SignalCast may earn commission on purchases via these links.

Tools

  • BF PrepBy guest

    by BulFrog AI

    The platform converts unstructured data — including handwritten clinical notes and PDFs — into clean, structured formats in hours or days rather than the months a human team would require
  • BF LeapBy guest

    by BulFrog AI

    BulFrog's BF Leap generates 6 million causal models in 30 minutes, determining not just whether gene relationships exist but their magnitude and direction
  • BF ArenasBy guest

    by BulFrog AI

    his three-platform AI system — BF Prep, BF Leap, and BF Arenas — targets the 50% Phase 3 clinical trial failure rate in pharma

company

  • BulFrog AIBy guest
    Vin Singh, founder and CEO of BulFrog AI (Nasdaq: BFRG), explains how his three-platform AI system — BF Prep, BF Leap, and BF Arenas — targets the 50% Phase 3 clinical trial failure rate in pharma
  • Using exclusive postmortem brain data from the Lieber Institute's 5,000+ brain repository, BulFrog identified driver genes for major depressive disorder, bipolar disorder, and schizophrenia in months

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