This week, Cleveland Clinic announced that it is scaling Dyania Health’s AI platform across its enterprise to accelerate clinical trial recruitment — and hopefully thereby enable patients to access beneficial therapies faster.
New Jersey-based Dyania, founded in 2019, is tackling one of healthcare’s most time-consuming tasks: manual chart review.
“Today, clinicians must sift through years of patient histories, piecing together information scattered across medical records to reach a conclusion. At the scale of thousands of patients in a clinical trial, this process would take human reviewers years to complete,” explained Dyania CEO Eirini Schlosser.
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Dyania’s platform automates this work and determines patients’ eligibility to participate in clinical trials. The system doesn’t just provide its reading once, but rather continuously reviews records for updates and changes to identify whether patients meet trial inclusion and exclusion criteria.
Schlosser added that the system is unique because it was developed with deep medical and technical rigor.
“Long before large language models became mainstream, Dyania was quietly in R&D, building and annotating a massive dataset to capture the real clinical context and nuance in electronic medical records to train our [large language model named] Synapsis AI,” she declared.
Whereas other healthcare AI developers may focus on polished interfaces, Dyania focuses on “the engine under the hood,” Schlosser stated.
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Cleveland Clinic began using Dyania’s technology in early 2024, launching pilot programs in oncology, cardiology and neurology.
In the melanoma pilot, Dyania’s AI identified eligible patients in 2.5 minutes at 96% accuracy — compared to more than 400 minutes for research nurses. In the cardiology pilot, the platform analyzed 1.2 million records and found twice as many eligible patients in a single week as traditional methods did over three months.
Lara Jehi, Cleveland Clinic’s chief research information officer, said that the deployment has been successful on multiple levels and called the decision to scale “obvious.”
“The technology is robust and met all our expected success milestones for accuracy, ease of use and speed to execution. The end user experience was very positive — our investigators interacted well with the Dyania team, and our research coordinators were happy to divert their effort from sifting through charts to spending more time directly interacting with patients,” she remarked.
She also noted that patients from regional practices — who typically are excluded from research opportunities — enjoyed having greater access to clinical trials.
To Jehi, the partnership between Cleveland Clinic and Dyania is a step in the right direction toward medical innovation. The slow pace of patient recruitment is one of the biggest hurdles accounting for the slow and costly clinical research process, she noted.
“Scientific progress in medicine aims to keep people healthier and to treat them faster and better. None of this can happen without testing medications for safety and efficacy through clinical trials. This process now takes almost a decade, on average, and costs billions of dollars,” she stated.
By automating one of clinical research’s most burdensome steps, Cleveland Clinic and Dyania are hoping to speed up the path from discovery to treatment.
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