Slow Clinical Trials Break AI's Feedback Loop in Drug Development
clarejtbirch · x · 2026-09-06
Ruxandra Teslo argues that slow clinical trials, especially early-stage ones, don't just delay drug validation—they break the learning feedback loop that makes AI better at discovering cancer treatments. AI is immensely powerful but needs the right data, and the best data remains in-human; techniques like single-cell RNA sequencing on treated patients are key.
Kate Rouch amplified the piece, quoting "everyone tried their best, but the system is so convoluted and risk-averse," and warning that losing this real-world experimentation loop means losing leadership in both science and drug development.
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