SOURCE: Booz Allen HamiltonDESCRIPTION:
Booz Allen Hamilton is committed to doing its part to enhance Precision Medicine and promote the use of data science to effect positive change in the world. To that end, the firm has continued its longstanding relationship with Johns Hopkins University by partnering with Johns Hopkins’ Individualized Health Initiative (inHealth) in support of its inaugural Pilot Project Discovery Program.
Johns Hopkins conceived the inHealth Pilot Project Discovery Program to promote discoveries in biomedical and data science intended to improve health decisions and outcomes at more affordable costs. Faculty and staff at Johns Hopkins submitted 95 applications to the program, from which eight were selected for funding. Each of the awarded projects will receive up to $75,000 for a 15-month funding period. The programs offer approaches to tackle health challenges ranging from cancer and cardiovascular disease to dementia and depression.
Booz Allen Hamilton will fund and collaborate with Hopkins researchers from the Schools of Medicine, Public Health, and Engineering—where Booz Allen Senior Vice President Natalie Givans serves on the board—on the Decoding Tumor Heterogeneity by Bayesian Statistical Models project. The project’s goal is to better characterize the heterogeneity inherent in the tumors of cancer patients by using state-of-the-art sequencing technology and statistical modeling. The project team will use their markers of tumor heterogeneity to predict patient survival and responsiveness to treatment, further advancing the individualization of cancer care.
“Collaborating across multiple disciplines, from data science to biology and public health, is exactly what’s needed to launch—and land—our nation’s cancer ‘moonshot, said Booz Allen Senior Vice President Rob Silverman, who provides analytics to the firm’s public health clients. “I’m also personally proud to collaborate with Johns Hopkins, my alma mater, on this important program.”
KEYWORDS: Health, Booz Allen Hamilton, johns hopkins, inHealth, precision medicine, data science