Parker Institute CEO: AI can speed drug discovery and help match patients to trials

Karen Knutson, chief executive officer of the Parker Institute for Cancer Immunotherapy, told the Assembly that AI is already changing cancer research and care. She said AI can synthesize complex datasets to accelerate drug discovery and highlighted three use cases: faster discovery, learning from every patient (including rare tumors), and improving clinical‑trial matching and operations. "AI is poised to shorten that time frame," she said when discussing the current 12‑ to 15‑year drug development window.

Knutson cited epidemiological figures to underline urgency: she said about "2,100,000 Americans will hear you have a new cancer this year, and 600,000 will die of their disease," adding roughly 200,000 of new diagnoses are in California. She also noted the high cost of oncology drug development ("exceeds $2,000,000,000") and said AI could improve efficiency across discovery and trial execution.

Why it matters: Knutson argued AI will not replace scientific judgment but can scale learning across heterogeneous patient data, especially for rare cancers where single‑center experience is limited. She urged more investment in translational steps—clinical testing and early signals that attract venture funding—rather than just discovery.

Next steps: Committee members and panelists discussed FDA readiness for platform and personalised therapeutic approvals; Knutson and others encouraged collaboration with regulators to modernize review pathways for platform‑based or personalized oncology interventions.