Speaker Profile

Ph.D., Chief Data Scientist & Co-Founder, OneThree Biotech

Cory Gilvary’s research has primarily focused on developing new machine learning techniques for increasing the efficiency and innovation of drug development and discovery. She takes the unique approach of combining distinct types of noisy, high-throughput data to maximize algorithmic performance, while also building interpretable models that allow for a deeper mechanistic insight to the mode of action of therapeutics. She has leveraged cutting edge AI concepts across diverse disease areas including, but not limited to, oncology, diabetes and Parksinson’s disease. Outside of her biological research, she spent time developing cutting edge machine learning models at one of the world’s leading quantitative hedge funds. Currently, Cory leads OneThree’s data science and computational biology efforts and much of her early research work formed the core OneThree platform. At the beginning of 2020, she spearheaded OneThree’s internal efforts to provide free toxicity screening to any researchers working on treatment for COVID-19.

AI & Data Science Showcase:
OneThree Biotech

OneThree Biotech is a VC backed startup working to change how new medicines are discovered using biology-driven AI. We are clinically validated and work with biotech and pharmaceutical companies to apply our mechanism focused AI to both pre-clinical and clinical pain points.

Interpretable AI for Early Stage Oncology Target Discovery
OneThree has created a platform of mechanism focused algorithms to address key questions within drug discovery. Our interpretable AI, allows us to elucidate the underlying mechanism of our predicted novel targets, a target's expected toxicity, and the ideal patient populations for positioning.

 Session Abstract – PMWC 2022 Silicon Valley

The PMWC 2022 AI Company Showcase will provide a 15-minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.