Triomics raises $15 M to automate oncology workflows with GenAI
09 May 2024 | News
To help cancer providers process free-text health record data at scale
Triomics, a health tech startup based in Bengaluru and US, has raised $15 million to help cancer centres streamline workflows and process oncology data at scale by applying their framework to build, institution-tuned large language models (OncoLLM) and use case-specific software.
The company has raised funds from several Silicon Valley firms making pioneering investments in generative AI and healthcare, including Lightspeed, Nexus Venture Partners, General Catalyst and Y Combinator.
Manual chart review can take hours per patient, and many health systems face significant backlogs in completing key oncology-related workflows for thousands of patients. This workload leads to clinical delays, such as patients missing out on clinical trials or biomarker-driven treatments, lagging quality reporting, and provider dissatisfaction and turnover.
After developing an OncoLLM with Medical College of Wisconsin researchers, Triomics found that, in just minutes, it found 90% of eligible patients for clinical trials, which would have taken days or weeks for qualified nurses. It also extracted structured data points from unstructured notes at similar or higher accuracy to proprietary models like GPT4 or Claude while being 40 times cheaper. Triomics recently also published the results of its information retrieval engine for oncology, which they found to be 1.5-2 times better than other state-of-the-art retrieval models.
Triomics next plans to publish additional data on OncoLLM efficacy across a diversity of settings and patient populations, and develop software that powers additional use cases.
