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My Personal Therapeutics and Pentavere Receive EUREKA Funding to Support AI-based Personalized Cancer Treatment Plans

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Product News

My Personal Therapeutics and Pentavere Receive EUREKA Funding to Support AI-based Personalized Cancer Treatment Plans

My Personal Therapeutics, a London-based medtech/digital therapeutics company and Pentavere Research Group, a Canadian-based Artificial Intelligence and data insight company have announced their successful EUREKA Collaborative R&D: AI and Quantum Technologies Competition award for project titled "Utilisation of AI to develop Personalised Treatment Plans for cancer".

Funding totaling £792,000 is co-funded by the UK’s innovation agency, Innovate UK, and Canada’s National Research Council’s Industrial Research Assistant Program, as part of their Collaborate R&D program. These funds will be used by Pentavere Research Group and My Personal Therapeutics to access Genomics England’s whole genome sequencing lung cancer data set and selectively generate drosophila avatars for high-throughput drug screening. The resulting tumor genomic profile and corresponding drug treatment recommendation data will feed into our AI Personal Discovery Process predictive model. Potentially, some of the funding can support personalized treatment recommendations for lung cancer patients in the UK.

"This Eureka award will partly fund this ground-breaking collaboration between My Personal Therapeutics, Pentavere and Genomics England towards the development of our rapid personalised cancer therapeutics offering – AI PDP" shared My Personal Therapeutics’ CEO Laura Towart.

My Personal Therapeutics is a London based medtech/digital therapeutics company offering personalized cancer therapeutics utilizing technology developed at Mt Sinai Medical Center. The Personal Discovery Process technology leverages Big Data curated from electronic health records, and genomics to build personalized fruit fly “avatars” that model individual patients at an unprecedented level of complexity. Using robotics, thousands of drugs are screened in combinations to identify drug cocktails designed to target the tumor while preserving the patient’s quality of life. Nearly all combinations incorporate non-cancer drugs, which can make them less toxic and more affordable. The goal is integrating AI/predictive modeling to enable rapid personalized treatment recommendations.

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