Matching cancer patients with appropriate clinical trials can be a life-saving endeavor. However, the process is often time-consuming and challenging for medical professionals. According to recent statistics, only 3% to 5% of eligible patients actually enroll in clinical trials. Triomics, a generative AI startup, aims to revolutionize this process by significantly reducing the time it takes for doctors to match patients with trials.
Doctors’ recommendations play a crucial role in enrolling patients in clinical trials. Unfortunately, busy oncologists and nurses often lack the time to thoroughly research and learn about all the available trials for their patients. This lack of information can be frustrating for both medical professionals and patients alike. As a result, many cancer patients miss out on potential treatment options.
Personal experiences highlight the challenges of finding clinical trials for cancer patients. Family members and friends often spend hours searching through websites and databases like clinicaltrials.gov to find suitable trials. The complex criteria of most trials, including factors like cancer stage, mutations, and previous treatments, make it difficult for medical staff to manually review patient records. Furthermore, due to a shortage of oncology professionals, many cancer patients are not given the opportunity to participate in trials or miss their eligibility window.
Triomics was founded in 2021 by Sarim Khan, a former MIT biotech researcher, and Hrituraj Singh, an AI scientist at Adobe. Recognizing the potential of generative AI and language learning models (LLMs), the duo developed Triomics to extract data from electronic health records (EHR) and match cancer patients with clinical trials within minutes.
Through their LLM called OncoLLM, Triomics has partnered with six cancer centers and hospitals to streamline the trial matching process. The company plans to double this number by the end of the year. Recently, Triomics secured a $15 million Series A funding round from prominent investors such as Lightspeed, Nexus Venture Partners, General Catalyst, and Y Combinator. This investment will aid Triomics in further developing their platform and expanding their customer base.
While Triomics initially focused on matching patients with clinical trials, the company has discovered numerous other applications for their software. Khan states that doctors use Triomics for various use cases beyond trial matching. For instance, the software can help prepare medical staff for patient visits or assist in submitting cancer data to regulatory agencies.
While Triomics is not the only player in the AI clinical trial matching space, they stand out due to their focus on processing large datasets specifically for cancer centers. Other startups in this field include Deep 6 AI, QuantHealth, and Trajectory. However, Triomics’ dedication to addressing the unique needs of cancer patients and medical professionals sets them apart.
In conclusion, Triomics is revolutionizing the process of matching cancer patients with clinical trials through their generative AI technology. By significantly reducing the time it takes for doctors to find appropriate trials, they are increasing the chances of patients receiving life-saving treatments. With their recent funding and partnerships, Triomics is well-positioned to make a lasting impact in the field of oncology research and patient care.
