Precision and Predictive Medicine
Big Data, Genomics, and Molecular Diagnosis
We are translating our research findings to precisely understand individual patients and use these data to make diagnostic, prognostic and therapeutic decisions.
We are translating our research findings to precisely understand individual patients and use these data to make diagnostic, prognostic and therapeutic decisions.
We apply computational medicine and artificial intelligence to develop predictive and precision medicine. For instance, we developed an artificial intelligence-based platform that can more easily classify esophageal biopsies. Using computer vision, the platform analyzes biopsy imagery to identify changes in tissue structure that are not seen under a microscope by the naked eye. Read more.
We have demonstrated broad effects of proton pump inhibitors on esophageal epithelium, including their ability to curtail transcriptomic processes involved in cellular proliferation and IL-13–induced responses, and they highlight the importance of ayrl hydrocarbon receptor (AHR) signaling in mediating these responses. Learn more.
Currently the diagnosis of EoE, and assessment of treatment response, involves invasive endoscopy and biopsy procurement and analysis and is not always accurate. Our lab is working on a more definitive molecular diagnostic test, which may also prove to be less invasive. This research involves developing a multigene panel of the genes involved in the “EoE signature” into an array format that can be run using clinical samples from patients. This array should also be able to tell us which patients will be responsive to specific treatments as well as predict disease severity and quality of life for these patients.