MODELLA AI’S PATHCHAT OBTAINS FDA BREAKTHROUGH DEVICE DESIGNATION FOR ADVANCING PATHOLOGY DIAGNOSTIC

KUALA LUMPUR, Feb 3 (Bernama) -- Modella AI, a pioneer in generative and agentic artificial intelligence (AI) for biomedicine, has announced that its cutting-edge generative AI co-pilot, PathChat DX, has been granted Breakthrough Device Designation by the United States (US) Food and Drug Administration (FDA).

This recognition underscores PathChat DX’s potential to transform diagnostic workflows and enhance patient outcomes in the field of pathology.

“The Breakthrough Device Designation is a testament to the transformative potential of PathChat DX as one of the first generative AI tools specifically trained for human pathology.

“This milestone brings us closer to our mission of using generative and agentic AI to accelerate diagnostic workflows,” said Modella AI chief executive officer, Dr Jill Stefanelli in a statement.

The FDA’s Breakthrough Device Designation is reserved for medical devices that offer significant advantages over existing standards of care, addressing unmet medical needs or providing critical advancements in healthcare.

PathChat DX, which is an extension of the PathChat model recently published in Nature and developed in the Mahmood Lab at Mass General Brigham under the leadership of Dr Faisal Mahmood.

PathChat integrates advanced generative AI and multimodal analysis, which are designed to assist pathologists in diagnosing complex cases with greater accuracy and efficiency.

The platform leverages a unique combination of pathology foundation models, pretrained on extensive histology image and image-text datasets, and a custom-trained multimodal large language model (MLLM) to analyse high-resolution pathology images and clinical data.

With this designation, Modella AI will benefit from prioritised FDA review and increased collaboration with the agency, expediting the development and commercialisation process for PathChat DX.

The designation highlights the FDA’s recognition of the platform’s potential to address critical challenges in pathology, including diagnostic variability and increasing case volumes.

-- BERNAMA