Speaker Profile

CEO, Oncobox

Andrew Garazha is a Co-Founder and CEO of Oncobox, a cancer research company developing next-generation tests for companion diagnostics. Oncobox team has developed a proprietary AI platform that utilizes RNAseq to measure gene expression patterns and predict drug response for targeted and immunotherapy drugs. The most recent clinical trial has shown that Oncobox method can double the response rate to therapy even for advanced cancer patients. Andrew has worked in both academia and industry with an emphasis on molecular genetics and bioinformatics. His work has resulted in multiple peer-reviewed publications, incl. PNAS, Nature Leukemia, Seminars in Oncology and the successful launch of several products. Andrew has graduated from the Moscow Institute of Physics and Technology (Master’s and Ph.D. programs), studied and worked at the California Institute of Technology.

Clinical Dx Showcase:

Oncobox is a cancer diagnostics company with true clinical data and unique algorithms. Backed by a multidisciplinary team, 30 publications in 2 years and Y Combinator recognition.

AI-Guided Development Of Novel Companion Diagnostics
Employing gene expression data intensified by AI allows designing affordable and powerful all-in-one test (incl. TMB, infiltration, IHC, and targets activation), applicable for drug selection or signature for a specific drug. Oncobox clinical trial (n=238) recorded an increase of up to 55% response-rate (vs. 30%, RECIST) for advanced cancer patients (NCT03724097).

 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.