Toward Building a Cancer Patient Digital Twin
What if we could build personalized digital twins that can identify anomalous health events that lead to cancer, suggest lifestyle changes to avoid high-risk states, and, when needed, instigate early diagnostic steps? what if the clinician and the cancer patient could jointly explore personalized risks, benefits and side effects and choose the best treatment plan using the patient's digital twin? These and other questions were explored in an intense 5-day Idea Lab organized by the National Cancer Institute , the Department of Energy and the Frederick National Labs for Cancer Research . Imagine this scenario On the day a person hears of his/her cancer diagnosis, a digital twin of the patient is instantiated by the clinical team. Over time, multi-modal, individualized data from genetic, environment and social factors are fed to the digital twin to create an accurate representation of the current state of the cancer patient. Clinicians then use High performance computing to simu