OncoImmunity receives €2.2 million to roll out its machine-learning platform to enable the development of personalized cancer immunotherapies.
The bioinformatics company OncoImmunity has been awarded the prestigious EU SME Instrument funding. The company’s flagship product, the ImmuneProfiler™, is a unique machine learning solution that has made inroads into solving the neoantigen prediction challenge. OncoImmunity enables their partners to solve the “needle in the haystack” challenge of identifying the right cocktail of neoantigens for each individual patient, and design a vaccine or cell therapy uniquely tailored to their specific tumor.
The machine learning company is based in both Oslo Norway and Cambridge Massachusetts in the USA, and this funding will advance further its capability to tailor the ImmuneProfiler™ for specific vaccine platforms, facilitating the design of safer and more efficacious personalised cancer vaccines.
“This project matches our ambition to position OncoImmunity as the leading supplier of neoantigen identification software in the personalized cancer vaccine market,” says Dr. Richard Stratford, Chief Executive Officer and Co-founder of OncoImmunity.
– The ImmuneProfiler™ is already a powerful antigen presentation prediction tool, with demonstrated utility in predicting antigens that are presented and visible to a patient’s T cells. With these funds OncoImmunity will further advance its generic platform to learn the precise constellation of potential neoantigens that are immunogenic in different vaccine delivery systems, says Dr. Trevor Clancy, Chief Scientific Officer and Co-founder of OncoImmunity.
OncoImmunity is a machine-learning company offering a proprietary technology to address the key knowledge gaps in the prediction of bone fide immunogenic neoantigens for personalized cancer immunotherapy. OncoImmunity’s software facilitates effective patient selection for cancer immunotherapy, and identifies optimal neoantigen targets for truly personalized cancer vaccines & cell therapies in a clinically actionable time-frame.