El futuro virtual de la investigación sobre el cáncer | Gege Qian | TEDxSanDiegoSalon

La bióloga computacional Gege Qian explica cómo se usa la IA para construir modelos de células virtuales, copias digitales de células vivas. Estos modelos podrían permitir a los médicos probar opciones de tratamiento sobre una copia digital del tumor de un paciente. Qian describe cómo podrían cambiar el descubrimiento de fármacos y el tratamiento del cáncer. Según su biografía, su investigación muestra cómo las células cancerosas se reorganizan bajo quimioterapia.

• Modelos de células virtuales creados con IA
• Prueba de tratamientos en una copia digital del tumor
• Posible impacto en el descubrimiento de fármacos

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