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BridgeBio Partners with Leading Cardiovascular Data Science Lab (CarDS Lab) to Improve Transthyretin Amyloid Cardiomyopathy (ATTR-CM) Diagnosis in Diverse Patient Populations with Multimodal Artificial Intelligence
- The TRACE-AI Network Study will deploy a scalable screening toolkit for ATTR-CM across large, diverse health system electronic health records (EHRs) aiming
About this update from Bridgebio Pharma, Inc.
[{"type":"text","content":"- The TRACE-AI Network Study will deploy a scalable screening toolkit for ATTR-CM across large, diverse health system electronic health records (EHRs) aiming to identify individuals who have ATTR-CM earlier in their disease course and quantify the potential prevalence of undiagnosed ATTR-CM PALO ALTO, Calif., Aug. 26, 2024 (GLOBE NEWSWIRE) -- BridgeBio Pharma, Inc. (Nasdaq: BBIO) (“BridgeBio” or the “Company”), a commercial-stage biopharmaceutical company focused on genetic diseases, today announced the initiation of a scientific collaboration with the CarDS Lab, led by cardiologist-data scientist, Rohan Khera, M.D., M.S. at Yale School of Medicine, to help address the underdiagnosis of ATTR-CM. The TRACE-AI Network Study will be deployed as a novel paradigm of large-scale federated screening for ATTR-CM that harnesses a central repository of validated AI tools across multiple participating sites to evaluate the scale of ATTR-CM underdiagnosis across the U.S. The participating sites in the network will aim to evaluate the scale of underdiagnosis among key socioeconomic and demographic subpopulations, estimate the prevalence of presymptomatic phenotypes of people with ATTR-CM, and assess the association between high-risk ATTR-CM on opportunistic testing and adverse clinical outcomes across the Network. \"At BridgeBio, we have long invested in computational approaches to aid drug discovery; similarly, by using AI with real-world data streams, we have a unique opportunity to improve the detection and optimize the utilization of advanced diagnostic testing. In this national initiative, we will deploy scalable and accessible strategies that improve the diagnosis and prediction of ATTR-CM in diverse populations, which has long been an unmet need in this category,” said Jennifer Hodge, Ph.D., Vice President of Evidence Generation at BridgeBio. The CarDS Lab has developed a series of novel deep learning tools applied to real-world data sets, including AI-electrocardiography (AI-ECG), AI-point-of-care ultrasound (AI-POCUS), and AI-echocardiography (AI-Echo), which may be capable of identifying those with potentially missed ATTR-CM, such as those with heart failure, with high accuracy, sensitivity and specificity. This strategy not only offers a novel and accessible method for early disease detection but also serves as a valuable tool for...