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Impact AI
Trailer
Bonus
Episode 121
Season 1
Foundation Model Series: Empowering Drug Discovery with Rick Schneider from Helical
AI is transforming drug discovery by making biological data more accessible and actionable, bridging the gap between complex sequencing data and real-world therapeutic breakthroughs. As Rick Schneider puts it, it's all about leveraging powerful models to “build use cases that matter and bring value.”
In this episode of Impact AI, we hear from the CEO and Co-founder of Helical to find out how bio-foundation models are transforming pharmaceutical research. Rick shares how Helical’s AI platform enables drug discovery by leveraging biological sequencing data without requiring companies to build their own models from scratch. He also reveals the challenges of working with high-dimensional biological data, the power of model specialization for specific therapeutic areas, and the growing role of open-source AI in healthcare innovation.
Whether you're in biotech, AI, or simply curious about the future of medicine, this episode offers invaluable insights into how AI is shaping the next generation of drug discovery. Tune in today!
In this episode of Impact AI, we hear from the CEO and Co-founder of Helical to find out how bio-foundation models are transforming pharmaceutical research. Rick shares how Helical’s AI platform enables drug discovery by leveraging biological sequencing data without requiring companies to build their own models from scratch. He also reveals the challenges of working with high-dimensional biological data, the power of model specialization for specific therapeutic areas, and the growing role of open-source AI in healthcare innovation.
Whether you're in biotech, AI, or simply curious about the future of medicine, this episode offers invaluable insights into how AI is shaping the next generation of drug discovery. Tune in today!
Key Points:
- Introducing Rick, his engineering background, and Helical’s mission.
- The challenges of leveraging biological foundation models for drug discovery.
- Understanding biological sequencing data and its complexities.
- Key technical challenges: messy datasets, long-range dependencies, and model architecture.
- How Helix, Helical’s mRNA foundation model, competes with industry leaders.
- Three key factors in building biological foundation models: data, compute, and talent
- The shift from narrow AI to general-purpose AI in pharma.
- Benchmarking and evaluating foundation models for different use cases.
- Commercializing Helical’s platform through partnerships with pharma companies.
- Insight into the role of open-source AI in advancing biological research.
- The future of biological foundation models: scaling up for greater impact.
- Rick’s vision for Helical as the backbone of in silico pharma labs.
Quotes:
“The question is, how do I leverage [powerful biological foundation models] and – build use cases that matter and bring value? Helical is building a therapeutic area, an agnostic AI platform that is empowering single-cell RNA and DNA bio foundation models for drug discovery.” — Rick Schneider
“In bio, you can still innovate on the architecture side and not simply [with] the scale of the models. It's not simply by throwing more compute at the models that you get to the very best outcomes.” — Rick Schneider
“Be okay with being different in your approach and accept [that you will] be contrarian to certain things.” — Rick Schneider
Links:
Resources for Computer Vision Teams:
LinkedIn – Connect with Heather.
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