Speaker Profile

CEO, bioSyntagma

Mr. Richardson’s company is focused on preventing trial-and-error cancer treatments by using predictive analytics to recommend treatment regimens that avoid drug resistance. His team has developed technology for mapping tumors that creates spatial (in-situ) and multi-omic data to form comprehensive, network-level understanding of tumors. Richardson’s team started development of the technology in 2016 and has since optimized its use for clinical patient samples and demonstrated novel screening methods in breast cancer patients with industry partners. Mr. Richardson and his team have received multiple awards and recognitions for their work, including the Flinn Foundation’s Bioscience Entrepreneurship Award, an Arizona Bioscience Award for Rapid Commercialization, Best Oncology-Focused Precision Medicine Company, and named one of Arizona’s Top 12 to Watch in Business for 2019. They have also won several National Science Foundation and National Cancer Institute grants to continue development of their technology.

Clinical Dx Showcase:

Data-driven biotech company addressing cancer drug resistance through novel tissue analysis and predictive analytics.

Tackling Drug Resistance: Spatial Mapping And AI
Drug resistance and patient stratification are critical obstacles to personalized medicine. bioSyntagma presents a platform for mapping patient tumors (spatial + multi-omic) paired with Artificial Intelligence for interpreting system-level environmental biomarkers to predict response and recommend combination treatments.

 Session Abstract – PMWC 2020 Silicon Valley

The PMWC 2020 Data Applications in Clinical Diagnostics Showcase will provide a 15-minute time slot for selected organizations, including commercial companies, clinical testing labs, and medical research institutions, to present their latest advancements, insights, applications, and technologies to an audience of clinicians, leading investigators, academic institutions, pharma and biotech, investors, and potential clients. We will learn about new technologies and findings that promise expedited, cost-effective, and accurate clinical diagnosis for early disease detection, treatment decisions, and disease prevention.