Developing successful cancer treatments remains challenging, with high failure rates. Cosmology may hold the answer.
Founded by a biomedical engineer, a computational physicist and a medical oncologist, Concr uses established computational frameworks from astrophysics to enable learning between disparate and messy oncology data to accurately model cancer biology.
This allows scientists to predict therapeutic response for individual patients, simulate clinical trials and generate biomarker hypotheses, thereby de-risking drug development and improving patient outcomes.
In July 2024, the first patients were recruited into Concr’s observational trial of their FarrSight®-Twin technology for outcome prediction in breast cancer.
“Our mission is to give more confidence to patients, clinicians, and drug developers in understanding whether and how their treatment will be effective to help each individual receive treatment that works best for them.”
AI-powered astrophysics meets oncology
Oncology therapeutic development continues to face high failure rates, causing substantial R&D costs with limited improvements to patient benefit and survival. However, there is a spark of hope in the distance, and cosmology may hold the answer.
“The uncertainty of knowing whether a treatment will be effective for a cancer patient is one of the cruellest and most damaging aspects of the disease. Concr was founded to directly address that problem. Our cutting-edge technology integrates oncology research and clinical data to simulate cancer biology, enabling precise therapeutic predictions with minimal diagnostic input.”
Dr Matthew Griffiths
Founded by Matthew Foster, Dr Matthew Griffiths and Dr Uzma Asghar, Concr is transforming cancer drug development and care with AI-powered predictive modelling. By adapting astrophysics methodologies, they’ve built FarrSight®-Twin, the first Bayesian AI model for individualised treatment response prediction.
This cutting-edge technology integrates fragmented oncology research and clinical data to accurately simulate cancer biology, enabling precise therapeutic predictions with minimal diagnostic input. Extensively validated pre-clinically and in clinical trials, their platform is used by drug developers for clinical trial simulation, biomarker discovery and therapeutic response prediction to reduce risk and improve patient outcomes.
In 2023, our Ventures team co-led a £1.94 million seed round alongside existing investor R42 Group, as well as welcoming new investors – Oncology Ventures, SyndicateRoom, Debiopharm and Jo Pisani from Cambridge Angels. Since then, Concr promoted Dr Irina Babina to CEO, and has pre-published a paper validating its novel approach across cancer types and treatment complexities.
“Our vision is to ensure precision oncology reaches the widest population, and that the widest population reaches precision oncology. This requires us to efficiently integrate diverse data modalities (solve data), to identify predictive biomarkers of treatment response (enabling precision diagnostics), that are generalisable to the widest patient cohorts (for all).”
Matthew Foster
From cell models to cohorts of patients, Concr provides the most advanced digital twins in oncology to enable more effective and data-driven development of cancer therapeutics.
Image Credits: Concr
