Triomics is helping cancer care providers by reducing the burden associated with manually reviewing patient charts. Utilizing our OncoLLM™—a family of oncology-focused language models—we are able to accelerate clinical trial enrollment, power quality improvement projects, and address many other key strategic priorities.
I am a chemical engineer with previous research experience in tissue engineering and neuroscience. The lack of vertical integration in the clinical trial space inspired me to work on Triomics.
Before starting Triomics, I was a Researcher at Adobe Research, where I worked on language models and reinforcement learning problems. I now use the same technologies to interpret oncology patient charts.