Triomics

Triomics

Intelligent clinical data utilization, transforming EHR data into actionable formats for clinical research, enabling better research that makes a difference, through advanced interoperability frameworks and AI.

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$15.0m

Series A
Total Funding000k
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More about Triomics
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Triomics operates as a specialized software company focused on the oncology sector, providing a generative AI-powered platform to streamline clinical workflows for cancer centers. The firm was established in 2020 by Sarim Khan (CEO), Hrituraj Singh (CTO), and Dr. Sajjan Rajpurohit, a medical oncologist with over a decade of experience. Khan, a former MIT biotech researcher, and Singh, previously an AI researcher at Adobe, combined their expertise in response to the inefficiencies and lack of integration they observed in the clinical trial landscape. The company participated in Y Combinator's Winter 2021 batch and has secured $28.9 million in total funding from investors including Lightspeed, Nexus Venture Partners, General Catalyst, and Y Combinator.

The core of Triomics' offering is its proprietary AI platform, OncoLLM™, a framework of interoperable AI components specifically trained on oncology data to interpret complex, unstructured information from electronic health records (EHRs). This system ingests various data formats, such as notes, PDFs, and lab results, to automate data-intensive tasks that traditionally require extensive manual review. The company serves cancer centers, hospitals, clinical research organizations, and healthcare administrators by providing tools to accelerate clinical trial enrollment, support quality improvement projects, and streamline care operations. Revenue is generated by providing these AI-driven solutions to its clients.

The platform offers several key products. Triomics Prism focuses on patient-to-trial matching by pre-screening patients against clinical trial criteria in real-time, which has been shown to identify 90% of eligible patients in minutes. Triomics Harmony curates EHR data for quality reporting, cohort analysis, and precision oncology. By automating the review of patient charts, the platform reduces the administrative burden on oncologists and research coordinators, allowing for quicker access to potentially life-saving treatments for patients and more efficient trial enrollment for pharmaceutical companies. Triomics distinguishes itself by building its models from the ground up for oncology, rather than adapting general AI solutions, and collaborates with over 20 NCI-designated cancer centers through the Collaboration for Oncology-focused LLM Training (COLT) to establish safety and performance benchmarks.

Keywords: oncology AI, clinical trial automation, generative AI, electronic health records, patient-trial matching, cancer care, clinical data abstraction, precision oncology, healthcare workflow, OncoLLM

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