To meet strict enterprise security and governance requirements, Snowflake's strategy is to "bring AI to the data." Through partnerships with cloud and model providers, inference is run inside the Snowflake security boundary, preventing sensitive data from being moved.

Industry partnerships are crucial for more than just funding. Collaborating with pharmaceutical companies provides translation-focused questions that guide the design of advanced cell models, ensuring they are predictive, scalable, and compatible with real-world development workflows.

When a billion-dollar drug trial fails, society learns nothing from the operational process. The detailed documentation of regulatory interactions, manufacturing, and trial design—the "lab notes" of clinical development—is locked away as a trade secret and effectively destroyed, preventing collective industry learning.

The FDA receives raw and cleaned datasets from sponsors, not just summary reports. Their internal teams conduct independent analyses, which can lead to findings or data presentations in the official drug label that differ from or expand upon what's in the published paper.

Enara Bio's discovery platform wasn't outsourced. It was built internally with integrated computational biology, mass spectrometry, and immunology teams. The CEO believes the most significant innovation and "magic" happens at the interface between these disciplines, a synergy only possible with close internal collaboration.

Despite processing 15 million clinical charts, Datycs doesn't use this data for model training. Their agreements explicitly respect that data belongs to the patient and the client—an ethical choice that prevents them from building large, aggregated language models from customer data.

The primary barrier to AI in drug discovery is the lack of large, high-quality training datasets. The emergence of federated learning platforms, which protect raw data while collectively training models, is a critical and undersung development for advancing the field.

When asked if they would investigate a safety concern for a specific drug at an external party's request, the FDA expressed reluctance. Such an analysis would raise questions of bias. Instead, they prefer to address these questions by pooling data from multiple drugs with a similar mechanism of action.

Bio is creating a formal system for biotech companies to report challenges with the FDA. Bio will synthesize this feedback monthly and present it directly to FDA leadership, creating a novel channel to elevate systemic issues and improve accountability.