NEW YORK – Concr on Friday said it received a grant of nearly £800,000 ($1 million) from Innovate UK to support the use of its artificial intelligence platform FarrSight to profile tissue samples from patients with early triple-negative breast cancer.
London-based Concr, which describes itself as a techbio company, uses computational methods derived from the field of astrophysics to interlink oncology data from disparate sources and identify biomarkers of drug response. With the Innovate UK grant, Concr will conduct a 24-month long observational study, dubbed AI-VISION, in partnership with the Institute of Cancer Research, London; the Royal Marsden National Health Service Foundation Trust; and the Durham University Institute for Computational Cosmology. The goal of the study is to find and validate biomarkers of patients' response to treatment, including chemotherapy and immunotherapy.
"The aim of our project is to uncover new potential ways to treat triple-negative breast cancer more effectively, by combining data from a variety of different sources and analyzing it using AI," Navita Somaiah, a clinician scientist at the Institute of Cancer Research and an oncologist at the Royal Marsden, said in a statement. "We hope to uncover genomic characteristics that indicate sensitivity to immunotherapy and could guide us to selecting the patients most likely to benefit from these newer therapies."
Investigators will use Bayesian computational frameworks adopted from astrophysics to find associations between genomic profiling data from patient samples and clinical information. The Durham computational cosmology group will contribute statistical techniques developed for studying the universe.
The findings from AI-VISION will also "add to the growing body of evidence aimed at demonstrating the performance and safety of novel computational methods to deliver precision medicine for the benefit of patients," Concr added.
In 2021, Concr launched a similar project that was funded by a £1 million grant from Innovate UK, focused on developing a method of assessing and comparing the impact of genomic sequencing tissue and blood samples in patients with cancer of unknown primary across seven NHS sites.