FarrSight-Twin was presented on October 24, 2024 at the 36th EORTC-NCI-AACR Symposium on Molecular Targets and Cancer Therapeutics in Barcelona, Spain.
According to the researchers, this approach could be used by cancer researchers to run virtual clinical trials before testing new treatments on patients. It could also be used alongside clinical trials with a digital twin for each patient taking part, which together could form a control group for any trial. It might also mean that patients could have different treatments tested on their digital twin to help select the most suitable treatment ahead of time.
The research was presented by Dr Uzma Asghar, co-founder and chief scientific officer at Concr and a consultant medical oncologist.
“Around the world, we spend billions of dollars on developing new cancer treatments. Some will turn out to be successful, but most will not,” she said in a statement. “We can use digital twins to represent individual patients, build clinical trial cohorts and compare treatments to see if they are likely to be successful before testing them out with real patients.”
Each digital twin is created from biological data from thousands of patients with cancer who have been treated in different ways. This information is combined to recreate the cancer of a real patient with molecular data on their tumour. This digital twin makes it possible to predict how a patient is likely to respond to a treatment.
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Dr Asghar and her colleagues used this approach to recreate published clinical trials with a digital twin representing each real patient who took part in the trial. Overall, the digital trials are said to have accurately predicted the outcome of the actual clinical trials in all simulated clinical studies. Further testing showed that where patients received the treatment predicted by FarrSight-Twin to be best, they had a 75 per cent response rate, compared to 53.5 per cent response where patients received a different treatment.
The trials they used in the study were in patients with breast, pancreatic or ovarian cancer. They were phase II or III trials that compared two different drug therapies, including anthracyclines, taxanes, platinum-based drugs, capecitabine and hormone treatments.
Dr Asghar said: “We are excited to apply this type of technology by simulating clinical trials across different tumour types to predict patients’ response to different chemotherapies and the results are encouraging.
“This technology means that researchers can simulate patient trials at a much earlier stage in drug development and they can re-run the simulation multiple times to test out different scenarios and maximise the likelihood of success. It is already being used to simulate patients to act as controls for comparing the effect of a new treatment with the existing standard of care.
“We are currently developing this technology so that it can predict treatment response for individual patients in the clinic and help doctors understand which chemotherapy will or will not be helpful, and this work is ongoing.”
Dr Asghar and her colleagues are testing the technology to see if it could help predict which available treatments will work best for patients with triple-negative breast cancer, in an observational collaborative trial between Concr, The Institute of Cancer Research, Durham University and the Royal Marsden Hospital.
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