Tanishq Mathew Abraham, Ph.D.

I don't think AI can cure cancer until it has the right data to learn from. Right now, that data mostly doesn't exist. I believe Precigenetics can change that. Most large biological datasets used to train AI "virtual cell" models show cells at a single moment, usually because the measurement (ex: sequencing) destroys the cell. You get a "before" and an "after" treatment, but not the path in between. That path can matter a lot though. For example, tumor cells adapt to drugs over hours and days, and resistance often emerges in exactly the window a snapshot misses. Precigenetics addresses this challenge by measuring the dynamic response of cells to drugs and other perturbations. They can measure morphological and biochemical changes inside living cells, without labels or killing the cell. The second problem is that most of this kind of data comes from 2D cell lines or animal models, which often don't represent how human tissue will respond. That's one reason so many drugs that look promising in preclinical studies fail in human trials. Precigenetics is extending its platform to human organoids, 3D tissue models that more closely resemble real human biology. Put those together and you get exactly the kind of data that is needed to train the next generation of AI virtual cells to solve cancer (and other diseases!). Parmita is a formidable founder and she is now looking for investors to support her mission. If you are an angel investor, I highly recommend reaching out! Full disclosure: I am an advisor for, and hold equity in Precigenetics.