For cancer patients, drugs administered to clinical trials can help save or extend lives.
But despite thousands of testing in the United States each year, only 3% to 5% of eligible patients are enrolled in research studies of new treatments.
Triomicsa prolific AI startup, claims it can significantly reduce the time it takes doctors to match patients with tests.
Physician recommendations are often key to enrolling patients. However, busy oncologists and nurses often do not have time to learn about all the clinical trials that may be appropriate 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. When my father was sick, I spent countless hours looking at clinicaltrials.gov, a website and database that lists thousands of ongoing trials. And just in March, I spent half a Saturday trying to find a clinical trial for a friend who has stage IV cancer. The doctor only offered her one test, so she asked me if there were any other options.
Since most clinical trials have complex criteria, there are often dozens of factors such as cancer stage, mutations and previous treatments for eligibility. Medical staff often need hours to manually review a patient’s medical record to find an appropriate clinical trial. However, due to a shortage of oncology professionals, many cancer patients are not offered to participate or miss their eligibility window.
Triomics was founded by former MIT biotech researcher Sarim Khan and Adobe AI scientist Hrituraj Singh. The pair, who have been friends since college, decided to build Triomics in 2021 after realizing that advances in genetic artificial intelligence and LLMs could help extract data from electronic health records (EHRs) to help find suitable clinical trials for cancer patients in minutes instead of hours.
Khan and Singh joined Y Combinator in the winter of 2021 and went on 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 or piloting its LLM and plans to double that number by the end of the year. And now the company has raised a $15 million round from Lightspeed, Nexus Venture Partners, General Catalyst, and Y Combinator to help it continue to grow its platform and roll it out to new customers.
While reducing the time it takes to match patients to clinical trials may seem like the most immediate application of Triomics software, Khan says Triomics is much more than a clinical trials company. “Physicians use it for so many different use cases that I could go on and on,” he said.
After Triomics’ LLM, which the company calls OncoLLM, “reads” the patient’s medical record, the data could be used to help prepare doctors and other medical staff for patient visits or to help report cancer data with details of the organs affected and the progress stage to the state regulatory agencies.
Of course, Triomics is not alone in tackling this area. Other startups matching AI clinical trials include Deep 6 AI, QuantHealth, Trajectory, among others.
However, Khan believes that Triomics is one of the few startups processing large data sets specifically for cancer centers.
