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New AI-powered clinical trial-matching platform expands access to cancer research

The approach relies upon extracting patient data (structured and unstructured text from electronic health records) and then processing this.

First introduced five decades ago, MRI scanners are now a cornerstone of modern medicine, vital for diagnosing strokes, tumors, spinal conditions and more, without exposing patients to radiation
First introduced five decades ago, MRI scanners are now a cornerstone of modern medicine, vital for diagnosing strokes, tumors, spinal conditions and more, without exposing patients to radiation - Copyright AFP/File ALAIN JOCARD
First introduced five decades ago, MRI scanners are now a cornerstone of modern medicine, vital for diagnosing strokes, tumors, spinal conditions and more, without exposing patients to radiation - Copyright AFP/File ALAIN JOCARD

The Mount Sinai Tisch Cancer Center (TCC) has launched a new artificial intelligence platform to help connect more cancer patients across the Mount Sinai Health System to life-saving clinical trials. The platform, which was created by the AI company Triomics, is called PRISM, and is powered by Triomics’ OncoLLM, a large language model-based pipeline built especially for cancer care.

Consequently, Mount Sinai becomes the first U.S. National Cancer Institute (NCI)-designated Comprehensive Cancer Center in New York City to deploy this oncology-specific AI tool for systemwide clinical trial matching.

Utilising patient data

The approach relies upon extracting patient data (structured and unstructured text from electronic health records) and then processing this using Natural Language Processing and SNOMED CT/ontologies, to convert medical terms (e.g., “Aspirin,” “ASA”) into standard concepts. AI then generate keywords or concepts from patient summaries to facilitate search. Here, AI models analyse the similarity between patient profiles and trial criteria, assigning eligibility scores to rank potential matches.

In addition, this type of deployment marks a major step forward in expanding access to innovative cancer research, accelerating clinical trial enrolment, and ensuring patients across the Health System are considered for cutting-edge treatment options earlier in their care.

Commenting on the initiative, Karyn Goodman (Icahn School of Medicine at Mount Sinai) says: “Clinical trials are essential to advancing cancer care, but too often patients and their treating physicians are not aware of studies that may be appropriate for them.”

AI & Clinical trial matching

Goodman adds: “By deploying an AI platform trained specifically for oncology, we can identify trial opportunities earlier, more consistently, and more equitably, allowing clinicians to focus on meaningful conversations with patients rather than manual chart review.”

Clinical trial matching refers to the process of determining which research studies a patient may be eligible for based on their electronic health records, diagnosis, medical history, and specific clinical characteristics. Traditionally, this work has relied on manual review of lengthy trial protocols and fragmented medical records, a time-intensive process that can sometimes delay or limit patient access to promising new therapies.

Historically, trial participation has been concentrated at flagship academic sites. However, with a systemwide deployment, patients seen at Mount Sinai Queens, Mount Sinai Brooklyn, Mount Sinai South Nassau, Mount Sinai Morningside, Mount Sinai West, and other sites have the same accessibility to available trials as those treated at The Mount Sinai Hospital.

This initiative also advances the health sector’s systemwide access to clinical trials. It also accelerates research integration across care settings, and this supports improved outcomes for diverse communities, such as the community served by the Mount Sinai group.

By expanding the pool of patients who can be considered for research at the right moment in their care, medical organisations like Mount Sinai are positioned to meet national benchmarks for trial participation.

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Written By

Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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