Concr closes £1.22 million seed round to enhance biomarker discovery in oncology

Cambridge Enterprise portfolio company Concr announces close of seed round to enhance first-in-class, ML-enabled biomarker discovery in oncology

Concr, a techbio company with a statistical learning-powered biomarker prediction engine, has closed a £1.22 million seed round to enhance first-in-class, ML-enabled biomarker discovery in oncology. The funding will be used to enhance Concr’s scientific and product development and grow its portfolio of pharmaceutical partnerships.

Concr welcomed new investors SyndicateRoom and Jo Pisani from Cambridge Angels in a round co-led by Cambridge Enterprise, who invested alongside the existing investor R42 Group. This seed round follows a prior £500,000 funding in 2021, which saw Concr grow its core team and enter the market.

Founded by biomedical engineer Matt Foster, computational physicist Dr Matthew Griffiths and medical oncologist Dr Uzma Asghar, Concr uses established computational frameworks from astrophysics to interlink disparate and messy oncology data to allow scientists to confidently identify and develop biomarkers of drug response, with minimal data requirements.

These biomarker predictions de-risk pivotal clinical trials and improve patient outcomes through effective stratification. Concr’s technology is capable of generating meaningful and actionable biomarker predictions using 300x less pre-clinical and 7x less clinical data. The algorithms developed by Concr effectively model tumour complexity and predict causes of its evolution, there predicting better and accurate patient response leading to effective treatments and minimal side effects.

Matt Foster, Chief Executive Officer of Concr, commented on the raise: “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). We have demonstrated significant headway with our technology used across novel diagnostic modalities in preclinical study design to biomarker optimisation for late phase clinical trial design, and application in wide scale clinical cohort research. We are honoured to receive support to achieve this, from diverse sources of leading SME funding. With top university, grant and private sector funding across the UK, USA and Australia, we draw upon a truly global body of support. With this opportunity ahead of us, we welcome innovative teams from academia, biopharma and healthcare sectors to join our growing user base”.