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Triomics Raises $15M Series A to Automate Cancer Clinical Trial Matching

For cancer patients, drugs given in clinical trials can help save or extend lives.

But despite thousands only trials in the United States each year 3% to 5% eligible patients are enrolled in research into new treatments.

Triomics, a generative AI startup, claims it can significantly reduce the time it takes doctors to match patients to trials.

Physician referrals are often key to enrolling patients. However, busy oncologists and nurses often don’t have time to learn about all the clinical trials that might be right for their patients.

I’m not a doctor, so I don’t know about the daily challenges of oncology medical staff. But unfortunately I know from personal experience how difficult it is to find clinical trials for cancer patients. I spent countless hours poring over Clinicaltrials.gov, a website and database that lists the thousands of trials that were ongoing while my father was ill. And just in March, I spent half a Saturday trying to find a clinical trial for a friend who has stage IV cancer. Her doctor only offered one trial, so she asked me if there were other options.

Because most clinical trials have complex criteria, there are often dozens of factors such as cancer stage, mutations, and prior treatments for eligibility. Medical staff often need hours to manually review a patient’s medical record to find the appropriate clinical trial. But due to a shortage of oncology specialists, many cancer patients were not offered participation or missed their eligibility period.

The company was founded by former MIT biotech researcher Sarim Khan and Adobe artificial intelligence scientist Hrituraj Singh. The pair, who have been friends since college, decided to build Triomics in 2021 after realizing that advances in generative artificial intelligence and LLM could help extract data from electronic health records (EHR) to find appropriate clinical trials for patients with cancer in minutes instead of hours.

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Khan and Singh entered the Y combinator in winter 2021 and continued to work on an LLM built specifically for cancer centers and oncology departments in hospital systems.

Three years later, Triomics says six cancer centers and hospitals are actively using or piloting its LLM, and it plans to double that number by the end of the year. And now the company has raised a $15 million Series A from Lightspeed, Nexus Venture Partners, General Catalyst and Y Combinator to help it continue to develop its platform and offer it to new users.

While reducing the time it takes patients to qualify for clinical trials may seem like the most valuable application of Triomics software, Khan says Triomics is much more than a clinical trials company. «Doctors are using it for several different use cases that I could go on and on about,» he said.

After Triomics’ LLM, which the company calls OncoLLM, «reads» a patient’s medical record, the data could be used to help prepare doctors and other medical staff for patient visits or to submit cancer data detailing organs involved and stage of progression to state regulators agencies.

Of course, Triomics is not the only one involved in this area. Other startups conducting AI clinical trial alignment include Deep 6 AI, QuantHealth, Path, among other

But Khan believes Triomics is one of the few startups that is processing big data sets specifically for cancer centers.

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