Unlock the future of clinical trial recruitment with an AI-driven solution that identifies the right patients with unprecedented speed and precision.
OncoLens leverages specialized AI, Natural Language Processing, and Large Language Models (LLMs) to revolutionize patient pre-screening for oncology clinical trials. By seamlessly mining both structured and unstructured data, this innovative approach not only distinguishes complex medical nuances—like differentiating between an emergency room visit and an estrogen receptor status—but also dramatically reduces manual chart review time. This study highlights real-world applications in challenging trials such as diffuse large B-cell lymphoma and lungMAP, demonstrating significant efficiency gains and improved patient accrual. With a human-in-the-loop model ensuring nuanced review and continuous re-screening of patient records, OncoLens paves the way for faster, more accurate trial matching and ultimately accelerates the journey to personalized cancer care. Download this case study to learn more.
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