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AI and LLMs are rapidly shifting how we work, and science is no different. 🧬 The conversation around drug discovery is particularly intriguing - and urgent. With drug development costs of $2.6B and a 90% failure rate, pharma needs AI more than ever. But is AI living up to its promise? 🧵
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Big Pharma is going all-in on AI partnerships: OpenAI building with Moderna, Sanofi, Lilly, & more AstraZeneca partnering with BenevolentAI Aitiabio building digital twins with Roche, Merck & more Yet these siloed approaches might be missing the bigger picture - the potential of decentralized, collaborative science.
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Let's start with what AI can do for drug discovery. 💊 1. Identify patterns in vast datasets 3. Predict drug-target interactions 4. Prioritize promising lead compounds 5. Design efficient clinical trials 6. Identify new uses for existing drugs And that's just the beginning
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A ton of questions are still on the table. ❓Who ultimately owns and benefits from the IP? ❓How do we fund diverse approaches? ❓Won't we need more access to data? ❓Will the industry become more collaborative or siloed? That's what DeSci is for 🧬
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