They say you should never judge a book by its cover, but can you judge a cell by its shape? On this episode, host Lauren Richardson is joined by Maddison Masaeli (CEO and cofounder of Deepcell), and a16z general partner Vijay Pande (whose lab at Stanford focused on the development of novel computational methods for simulating biology), to discuss what we can learn by characterizing a cell's shape — also known as its morphology. We've long appreciated that morphology can be used to discriminate cells, for example, cancer cells look very different than the surrounding tissue and can be spotted in a biopsy, and the various classes of immune cells all have distinct appearances. But characterization of cell shape — and what it can tell us about the underlying biology of those cells and the health of the organism that they came from — has been stuck in the low-tech, manual, qualitative era. To unlock the potential of cell morphology, Maddison and her colleagues are leveraging the power of artificial intelligence to assess and learn from cell images to create a quantitative, scaleable technology. The conversation covers the untapped potential of studying cells and their shape, how Maddison and her team at Deepcell are building an AI with seemingly limitless applications, and where this technology could take us.