PRIME MEMBER EXCLUSIVE | 3 Months Free Trial
Auto-renews at INR 199/mo after 3 months. Cancel anytime. Offer ends 15 July, 2026.
#64. Foundation Models
Failed to add items
Add to cart failed.
Add to wishlist failed.
Remove from wishlist failed.
Follow podcast failed
Unfollow podcast failed
#64. Foundation Models
-
Narrated by:
-
Written by:
In this episode, we explore the surge of foundation models (FMs) within pharmaceutical research, noting that over 200 such models were published by early 2025. Unlike traditional task-specific AI, these versatile algorithms are pre-trained on massive datasets to identify broad biological patterns before being refined for specialized functions. We detail how FMs are currently applied to transcriptomics, protein structures, and pathology imaging to enhance the speed and efficiency of drug discovery. Despite hurdles like data scarcity and technical "hallucinations," the source envisions a future where automated workflows use these models to identify drug targets and design molecules. This transition suggests a shift toward a "lab-in-the-loop" paradigm, where AI predictions and experimental results continuously optimize one another. Ultimately, the text argues that FMs possess transformative potential to modernize the historically slow and expensive process of creating new medicines. Produced by Dr. Jake Chen.