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The Future of Biology Is Generative: Inside Synthesize Bio’s RNA AI Model

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Manage episode 508239182 series 3563133
Content provided by Madrona Ventures. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Madrona Ventures or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode of Founded & Funded, Madrona Investor Joe Horsman sits down with Jeff Leek and Rob Bradley, co-founders of Synthesize Bio, a foundation model company for biology that’s unlocking experiments researchers could never run in the lab.

Jeff, chief data officer at the Fred Hutch Cancer Center, and Rob, the McIlwain Family endowed chair in data science, share:

•Why a startup the right fit for generative genomics •How generative genomics could reshape research, drug trials, and more •Why RNA is the right starting point for a generative AI model in biology •What this breakthrough means for the future of drug development •Why now is biology’s “ChatGPT moment” •What makes Synthesize a true foundation model for biology (not a point solution)

Whether you’re a founder, biotech innovator, or AI researcher, this is a must-listen conversation about the intersection of AI, biology, and the future of medicine.

Transcript:https://www.madrona.com/the-future-of-biology-is-generative-inside-synthesize-bios-rna-ai-model

Chapters: (2:00) – Why a Foundation Model for Biology? (5:00) – The Case for RNA (7:00) – Biology’s Large Language Model Analogy (9:00) – Solving Impossible Problems (11:00) – Validation & Testing (14:00) – Balancing Big Picture & Specific Biology (15:00) – Why a Company, Not Just a Lab (16:00) – Has Biology Had Its “ChatGPT Moment”? (19:00) – The Data Challenge (23:00) – Real-World Use Cases (26:00) – How Research Will Look in 10 Years (28:00) – Increasing the Odds of Discovery (29:00) – Clinical Trials & Precision Medicine (31:00) – Access & Next Steps

  continue reading

100 episodes

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iconShare
 
Manage episode 508239182 series 3563133
Content provided by Madrona Ventures. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Madrona Ventures or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode of Founded & Funded, Madrona Investor Joe Horsman sits down with Jeff Leek and Rob Bradley, co-founders of Synthesize Bio, a foundation model company for biology that’s unlocking experiments researchers could never run in the lab.

Jeff, chief data officer at the Fred Hutch Cancer Center, and Rob, the McIlwain Family endowed chair in data science, share:

•Why a startup the right fit for generative genomics •How generative genomics could reshape research, drug trials, and more •Why RNA is the right starting point for a generative AI model in biology •What this breakthrough means for the future of drug development •Why now is biology’s “ChatGPT moment” •What makes Synthesize a true foundation model for biology (not a point solution)

Whether you’re a founder, biotech innovator, or AI researcher, this is a must-listen conversation about the intersection of AI, biology, and the future of medicine.

Transcript:https://www.madrona.com/the-future-of-biology-is-generative-inside-synthesize-bios-rna-ai-model

Chapters: (2:00) – Why a Foundation Model for Biology? (5:00) – The Case for RNA (7:00) – Biology’s Large Language Model Analogy (9:00) – Solving Impossible Problems (11:00) – Validation & Testing (14:00) – Balancing Big Picture & Specific Biology (15:00) – Why a Company, Not Just a Lab (16:00) – Has Biology Had Its “ChatGPT Moment”? (19:00) – The Data Challenge (23:00) – Real-World Use Cases (26:00) – How Research Will Look in 10 Years (28:00) – Increasing the Odds of Discovery (29:00) – Clinical Trials & Precision Medicine (31:00) – Access & Next Steps

  continue reading

100 episodes

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