Virtual cells could make it faster and easier to discover new drugs. They could also give insight into how cancer cells evade the immune system, or how an individual patient might respond to a given therapy. They might even help basic scientists come up with hypotheses about how cells work that can steer them toward what experiments to do with real cells. “The overall goal here,” Quake says, “is to try to turn cell biology from a field that’s 90% experimental and 10% computational to the other way around.”
Some scientists question how useful predictions made by AI will be, if the AI can’t provide an explanation for them. “The AI models, normally, are a black box,” says Erick Armingol, a systems biologist and post-doctoral researcher at the Wellcome Sanger Institute in the U.K. In other words, they give you an answer, but they can’t tell you why they gave you that answer.
