Vice President, Research and Data Science
Developed a platform for a CLIA-validated/CAP-accredited commercial product (GPS Cancer) that translates somatic alterations from patient sequencing data into a clinical report that provides physicians with actionable findings. Finally, my algorithms are the core technology of the FDA-approved Tumor-Normal mutation profiling test called Omics Core, which features the first FDA-approved measure of a tumor's "true" tumor mutation burden (TMB) based on whole exome sequencing data. I have designed, developed, and overseen the development of analytical frameworks for analyzing genomic and transcriptomic data, including: estimates of Tumor Mutation Burden, ranking or filtering somatic mutations based on measures of their biological effect, estimating purity & ploidy of the tumor sample, identifying cases of sample contamination or sample mismatches, inferring patient population, and detecting fusion sequences from raw sequencing data. The GPS Cancer product and its related technologies have successfully returned results to thousands of patients across the country, numerous academic collaborations, and provided analytical support to clinical trials.