How Triomics Uses AI To Help Doctors Treat Cancer More Quickly

Doctors are under huge pressure to process patient records

LightRocket via Getty Images

Patients with a cancer diagnosis need access to the best possible treatment as quickly as possible – but clinicians who must wade through patient records that may extend to hundreds of pages often lack the capacity to help. New York-based scale-up Triomics, which has just unveiled a £22 million Series B funding round, thinks its artificial intelligence (AI) platform can make all the difference.

I first interviewed Triomics in 2024, when it was primarily focused on helping oncologists identify new trials and treatments that might work for patients. Since then, the business has grown rapidly – it now works with cancer centers responsible for treating around 15% of all American cancer patients – and expanded its use cases.

Still, the business’s focus has remained consistent: it aims to reduce the information processing workload that slows doctors down. “A patient’s record might be 1,000 pages long, spanning everything from handwritten notes to MRI images,” explains Sarim Khan, the CEO of Triomics, who co-founded the business with CTO Hrituraj Singh in 2021. “Before the physician even meets the patient, he or she needs to work through every detail of that record.”

Triomics’ AI platform, based on a large language model trained to specialise in oncology, can substantially relive this burden. It processes each patient’s record – including both structured and unstructured data – to produce a set of outputs that doctors can use to identify the most appropriate next treatment step. The company’s data, published with the American Society of Clinical Oncology, suggests it is possible to reduce chart review times by 67%. It has also published statistics showing a 40% improvement in matching patients to trials.

“Ultimately, this leads to better patient outcomes,” explains Khan. “New patients get the right treatment more quickly and doctors can also accelerate…

Source