GE Healthcare and VUMC will retrospectively analyze and correlate the immunotherapy treatment response of thousands of VUMC cancer patients, with their anonymized demographic, genomic, tumor, cellular, proteomic and imaging data. They will then develop AI-powered apps that draw on this data to help physicians identify the most suitable treatment for each individual patient.
Simultaneously, GE Healthcare and VUMC will develop new positron-emission tomography (PET) imaging tracers, which together with the apps, will help physicians to stratify cancer patients for clinical trials. It currently takes an average of 12 years and costs almost $2B to bring a drug to market. In many cases, inappropriate patients are recruited to participate in immunotherapy trials, incurring unnecessary expense and slowing down approvals of new therapies. It is hoped that the PET tracers will ultimately also be used to monitor the efficacy of immunotherapies in everyday practice.
“Immunotherapy offers tremendous promise but given the current unpredictability of some patients’ reactions to treatments, it is also associated with increased morbidity and cost. This partnership provides the opportunity to leverage strengths of both of our organizations to further personalize cancer care by creating new tools that allow clinicians to more accurately predict how patients will respond to a specific therapy,” said Jeff Balser, MD, PhD, president and chief executive officer, Vanderbilt University Medical Center and Dean of the Vanderbilt University School of Medicine.
“GE Healthcare and Vanderbilt will combine their data science, genomic, imaging and cellular analysis capabilities to help improve clinical decision making. This partnership is a great example of the increasing convergence of the tools, technologies and data used by therapy innovators and healthcare providers,” said Kieran Murphy, president and chief executive officer, GE Healthcare.
GE Healthcare and the Vanderbilt-Ingram Cancer Center, a world-renowned stem cell transplant facility, will also collaborate on methods to improve productivity, efficiency and cost of stem cell transplant processing operations by automating processes, digitizing workflows, improving throughput and industrializing operations.