Digital twin model predicts the right chemotherapy response

U.K. researchers have repurposed algorithms that astrophysicists employ to discover black holes to create a digital twin model that can accurately predict treatment responses for different chemotherapy drug classes in people with cancer. The technology, called FarrSight®- Twin, could “help health professionals to match individuals to the right chemotherapy drug,” said Uzma Asghar, PhD, co-founder and chief scientific officer at Concr and a consultant medical oncologist, currently working at The Royal Marsden NHS Foundation Trust, London. “This increases the probability of response to the drug and, as we have shown, improves survival in a retrospective analysis.” Speaking at the 36th EORTC-NCIAACR Symposium on Molecular Targets and Cancer Therapeutics in Barcelona, Spain, Asghar explained that a digital twin is a virtual replicate of an individual and their cancer.

It is created from biological data from thousands of patients with cancer who have been treated in different ways and considers information about the patient, their demographic profile, the type of cancer that they have, including molecular data on their tumor, and any potential drug they may be exposed to.