The virtual future of cancer research | Gege Qian | TEDxSanDiegoSalon

Computational biologist Gege Qian discusses how AI is being used to build virtual cell models, digital copies of living cells that could let doctors test treatment options on a model of a patient's tumor. She explains how such models could change drug discovery and cancer treatment. According to the speaker bio, her research uses machine learning to show how cancer cells reorganize under chemotherapy, which may help explain relapse after treatment.

• Virtual cell models built with AI to represent living cells
• Testing treatment options on a digital copy of a tumor
• How cell models could change drug discovery and disease treatment
• Why cancer cells may reorganize under chemotherapy and relapse

What if, before choosing your cancer treatment, your doctor could test every option — not on you, but on a digital copy of your tumor living inside a computer? That's the promise of the virtual cell. Computational biologist Gege Qian explains how AI is learning to model living cells, what the future of the virtual cell could hold, and why it could change how we discover drugs and treat disease. #Cancer #DigitalTwin, #AI #technology #VirtualCell #UCSD #TEDxSanDiego #TEDx #moorescancercenter #ComputationalBiologist Gege Qian is a computational oncologist and PhD candidate at UC San Diego, where she builds AI systems that map the inner architecture of living cells. Her work — published in Nature and under review at Science — uses machine learning to construct virtual cell models that reveal how cancer cells reorganize under chemotherapy, helping explain why patients relapse after treatment. A first-generation college student, Gege earned dual degrees from UC San Diego before completing her master's at Harvard Medical School. She has also worked as a venture capital fellow evaluating AI biotech startups and led biotech entrepreneurship initiatives that brokered partnerships with Roche. She believes the most important frontier in medicine is not a new drug — it is a new way of seeing cells. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx