PFI-RP: Precision diagnostics for personalized cancer care: development of new drugs and selection of treatment

The broader impact/commercial potential of this Partnerships for Innovation – Research Partnerships (PFI-RP) project is to benefit cancer patients by using AN innovative artificial intelligence (AI) technology to select optimal treatment options tailored to each individual patient with the goal of prolonging patient life. Despite emerging new therapies, cancer remains the second leading cause of death in the United States. Clinical tools to select optimal treatment options suitable for individual cancer patients are currently lacking. To meet these unmet clinical needs, this project will employ an established cutting-edge AI/big data technology to determine the best treatments and therapeutic options for individual patients to improve cancer outcomes. Upon successful completion of the development of this technology, the solution will reduce healthcare costs by avoiding initial treatment failures. This project will also foster transdisciplinary graduate research and educate future leaders in innovation and entrepreneurship. This work, if success, will result in industrial investments and workforce development in Appalachia, reducing health disparities in West Virginia, which has high cancer incidence and mortality rates. The proposed project is based on leading-edge AI technology with competitive advantages in computational efficiency, scalability, and accuracy over existing other methods for developing diagnostic gene tests and new drugs. Using the proposed technology, new prototype gene assays can be developed and patented for diagnosis, prognosis, and prediction of therapeutic benefits in breast, ovarian, colon, and lung cancer patients. These gene assays will have the ability to identify individuals who are at high-risk for tumor recurrence and metastasis and select the drug treatments that will benefit the patients the most. The proposed AI pipeline will initially focus on the discovery of new drug options for treating lung cancer but can be expanded to other types of cancers. This project has three goals: 1) to establish the connection with multiple innovation networks/hubs, enhancing academia-industry collaboration, 2) to accelerate market-oriented development of prototype products, and 3) to develop a novel multidisciplinary graduate training program across computer science, oncology, biomedical research, and entrepreneurship. To overcome the technical hurdles in commercialization, this project will leverage multi-modal patient data using several precision medicine companies' manufacturing platforms to 1) validate the prototype gene assays for optimal treatment selection and better cancer outcomes, and 2) establish an AI-based technology for comprehensively discovering new drugs and/or repositioning Food and Drug Administration (FDA)-approved drugs for cancer patients with failed prior therapy. This project is jointly funded by Partnerships for Innovation Program and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.