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Triomics Secures $15M to Streamline Cancer Trials

Triomics, a generative AI startup, has secured a $15M Series A funding round for cancer clinical trials matching
May 10, 2024

For cancer patients, access to medicines through clinical trials can be life-saving. However, despite the thousands of trials conducted in the United States annually, only a small percentage of eligible patients actually enroll in these investigations.

Triomics, a generative AI startup, claims it can drastically reduce the time it takes for doctors to match patients with appropriate clinical trials.

Oncologists and nurses, often overwhelmed with their workload, struggle to stay informed about all available clinical trials suitable for their patients. As a result, patients miss out on potential opportunities for treatment. 

Founder Sarim Khan, along with AI scientist Hrituraj Singh, recognized this problem and established Triomics in 2021. Their aim was to leverage advances in generative AI and language learning models (LLMs) to extract data from electronic health records (EHR) and match cancer patients with suitable clinical trials in minutes, rather than hours.

Three years later, Triomics has made significant strides. Six cancer centers and hospitals are actively using or piloting its LLM, OncoLLM, which is specifically designed for oncology departments. With a recent $15 million Series A funding round led by Lightspeed, Nexus Venture Partners, General Catalyst, and Y Combinator, Triomics plans to expand its platform to new customers while continuing to enhance its capabilities.

While the immediate value of Triomics' software lies in accelerating the patient-trial matching process, Khan emphasizes that the platform serves multiple purposes. From assisting doctors in patient visits to facilitating the submission of cancer data to regulatory agencies, OncoLLM proves to be a versatile tool for medical professionals.

Triomics faces competition from other startups in the AI clinical trial matching space, such as Deep 6 AI, QuantHealth, and Trajectory. However, Khan believes that Triomics stands out due to its focus on processing large datasets specifically for cancer centers, ensuring that patients receive the most suitable treatment options available.

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