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EP 64
Foundation Models in Biomedicine and Drug Discovery
The episode explores the evolution of foundation models in biomedicine and drug discovery, from rigid task-specific models to massive polymath models that learn the fundamental grammar of biology. It discusses the tension between open source and private models, and the rise of agentic AI that can reason and orchestrate virtual labs. The episode also touches on the challenges of simulating complex biological systems and the potential future of clinical trials.
foundation modelsbiomedicinedrug discoveryagentic AIopen sourceprivate modelsclinical trials
Key Concepts
Foundation Models
- Pre-trained on massive unlabeled data sets
- Capable of multi-step reasoning
- Can simulate life itself
- Learn the fundamental grammar of biology
Agentic AI
- Enables the creation of virtual patient labs
- Can reason and orchestrate virtual labs
- Has the potential to accelerate drug discovery
Open Source vs Private Models
- Open source models are massive and generalized
- Private models are smaller and hyper-efficient
- Private models are preferred by pharma due to security and logistics concerns
Simulating Complex Biological Systems
- The complexity of biological systems is vast and challenging to simulate
- The accessible chemical space for potential drug-like molecules is estimated to be 10 to the power of 60
- The number of possible gene-to-gene interactions in a single human cell is over 200 million
Clinical Trials and Virtual Patient Labs
- The future of clinical trials may be impacted by the development of perfect agentic virtual patient labs
- Virtual patient labs have the potential to reduce the need for physical testing
- However, the models are not yet capable of replacing physical reality
Episode Summary
- check_circleFoundation models are revolutionizing biomedicine and drug discovery by learning the fundamental grammar of biology
- check_circleThese models are pre-trained on massive unlabeled data sets and can be fine-tuned for specific tasks
- check_circleThe models are capable of multi-step reasoning and can simulate life itself
- check_circleThe field is experiencing a 250% annual growth rate in the publication of biomedical foundation models
- check_circleThe models are being used to simulate cellular structure, protein folding, and disease states
- check_circleThe use of foundation models has the potential to accelerate drug discovery and reduce the need for physical testing
- check_circleHowever, the models are not yet capable of replacing physical reality and must be tethered to real physical wet lab validation
- check_circleThe rise of agentic AI is enabling the creation of virtual patient labs that can simulate human biological responses to molecules
- check_circleThe future of clinical trials may be impacted by the development of perfect agentic virtual patient labs
Full Transcript
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