Here's the FDA announcement: https://www.fda.gov/news-events/press-announcements/fda-announces-plan-phase-out-animal-testing-requirement-monoclonal-antibodies-

Here's the FDA announcement: https://www.fda.gov/news-events/press-announcements/fda-announces-plan-phase-out-animal-testing-requirement-monoclonal-antibodies-and-other-drugs https://www.fda.gov/news-events/press-announcements/fda-anno... Fact is, pharmas already pre-screen immune response in vitro using various stat and ML algorithms, a no-brainer that's been done for years. Organoids are useful to detect only the obvious toxicities in the most obvious tissues (liver, kidney, neural). Also a no-brainer that's been done for years mostly in animal studies. The acid test is what FDA criteria will change now in trusting nonclinical data and novel biomarker thresholds in novel criteria like simulations (much less AI black boxes). Attempts to address this also has been in development in the industry for decades, to invent new standards in a precompetitive space -- to be shared among drug developers so they can be freely employed by all. I don't see AI moving the needle, especially how inexplicable AI continues to be (as opposed to classical statistical ML methods, which CAN explain themselves). Caveat patiens.