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
Rhea-AI Summary
BridgeBio Pharma (Nasdaq: BBIO) has initiated a scientific collaboration with the CarDS Lab at Yale School of Medicine to address the underdiagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM). The TRACE-AI Network Study will deploy a scalable screening toolkit across diverse health system electronic health records (EHRs) to identify individuals with ATTR-CM earlier and quantify the potential prevalence of undiagnosed cases.
The CarDS Lab has developed novel deep learning tools applied to real-world data sets, including AI-electrocardiography, AI-point-of-care ultrasound, and AI-echocardiography, which may identify potentially missed ATTR-CM cases with high accuracy. This initiative aims to improve diagnosis across the U.S. and potentially enhance outcomes for patients in need.
Positive
- Collaboration with leading cardiovascular data science lab to improve ATTR-CM diagnosis
- Development of AI tools for early detection and risk stratification of ATTR-CM
- Potential to address underdiagnosis of ATTR-CM in diverse populations
- Presentation of original research at the European Society of Cardiology's Congress 2024
Negative
- None.
News Market Reaction
On the day this news was published, BBIO gained 2.33%, reflecting a moderate positive market reaction.
Data tracked by StockTitan Argus on the day of publication.
- 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 risk stratification, ultimately enhancing the effectiveness of the current diagnostic processes in healthcare systems.
"For the first time, the TRACE-AI Network Study represents a convergence of cutting-edge technology and clinical expertise aimed at addressing the challenges currently seen in ATTR-CM diagnosis across large, diverse U.S. health systems," said Dr. Khera. "One key aspect of our technology is its applicability to data routinely available at the point of care, which will enable us to facilitate widespread deployment, providing access to traditionally disadvantaged groups.”
“Early detection is critical for someone with ATTR-CM, and evidence suggests that ATTR-CM is markedly underdiagnosed due to its complex presentation. This initiative is incredibly important toward improving diagnosis across the U.S. and potentially improving outcomes for patients in need,” said Ahmad Masri, M.D., M.S., Cardiomyopathy Section Head and Director of the Cardiac Amyloidosis Program at Oregon Health & Science University and Steering Committee Member of the TRACE-AI Network.
Additionally, the CarDS Lab will present original research funded by BridgeBio that supports the tools utilized in the TRACE-AI Network Study at the European Society of Cardiology’s (ESC) Congress 2024. Details are as follows:
Oral Presentations
Title: Artificial intelligence applied to electrocardiographic images for scalable screening of cardiac amyloidosis
Presenter: Veer Sangha, Yale School of Medicine, U.S.
Presentation date & time: Friday, August 30th at 8:15 a.m. BST
Title: Artificial intelligence-guided screening of under-recognized cardiomyopathies adapted for point-of-care echocardiography
Presenter: Evangelos K. Oikonomou, M.D., DPhil, Yale School of Medicine, U.S.
Presentation date & time: Sunday, September 1 at 8:15 a.m. BST
Moderated Posters
Title: Characterizing the progression of sub-clinical cardiac amyloidosis through artificial intelligence applied to electrocardiographic images and echocardiograms
Presenter: Evangelos K. Oikonomou, M.D., DPhil, Yale School of Medicine, U.S.
Moderated poster date & time: Saturday, August 31st at 3:00 p.m. BST
Title: Detection of ATTR cardiac amyloidosis using a novel artificial intelligence algorithm for wearable-adapted noisy single-lead electrocardiograms
Presenter: Veer Sangha, Yale School of Medicine, U.S.
Moderated poster date & time: Monday, September 2nd at 12:00 p.m. BST
About BridgeBio Pharma, Inc.
BridgeBio Pharma, Inc. (BridgeBio) is a commercial-stage biopharmaceutical company founded to discover, create, test and deliver transformative medicines to treat patients who suffer from genetic diseases. BridgeBio’s pipeline of development programs ranges from early science to advanced clinical trials. BridgeBio was founded in 2015 and its team of experienced drug discoverers, developers and innovators are committed to applying advances in genetic medicine to help patients as quickly as possible. For more information visit bridgebio.com and follow us on LinkedIn, Twitter and Facebook.
BridgeBio Forward-Looking Statements
This press release contains forward-looking statements. Statements in this press release may include statements that are not historical facts and are considered forward-looking within the meaning of Section 27A of the Securities Act of 1933, as amended (the Securities Act), and Section 21E of the Securities Exchange Act of 1934, as amended (the Exchange Act), which are usually identified by the use of words such as “anticipates,” “believes,” “continues,” “estimates,” “expects,” “hopes,” “intends,” “may,” “plans,” “projects,” “remains,” “seeks,” “should,” “will,” and variations of such words or similar expressions. We intend these forward-looking statements to be covered by the safe harbor provisions for forward-looking statements contained in Section 27A of the Securities Act and Section 21E of the Exchange Act. These forward-looking statements, including statements relating to the plans, intentions, expectations and strategies of applying artificial intelligence to improve the diagnosis and prediction of ATTR-CM are based on the information currently available to us and on assumptions we have made. Although we believe that our plans, intentions, expectations and strategies as reflected in or suggested by those forward-looking statements are reasonable, we can give no assurance that the plans, intentions, expectations or strategies will be attained or achieved. Furthermore, actual results may differ materially from those described in the forward-looking statements and will be affected by a number of risks, uncertainties and assumptions, including, but not limited to, , the design and success of the artificial intelligence tools used in the TRACE-AI Network Study in early disease detection, or the sufficiency of data sets to which such tools are applied, the continuing success of our collaborations with the CarDS Lab, and adverse effects on healthcare systems and disruption of the global economy, as well as those risks set forth in the Risk Factors section of our most recent Annual Report on Form 10-K and our other filings with the U.S. Securities and Exchange Commission. Moreover, we operate in a very competitive and rapidly changing environment in which new risks emerge from time to time. These forward-looking statements are based upon the current expectations and beliefs of our management as of the date of this press release, and are subject to certain risks and uncertainties that could cause actual results to differ materially from those described in the forward-looking statements. Except as required by applicable law, we assume no obligation to update publicly any forward-looking statements, whether as a result of new information, future events or otherwise.
BridgeBio Contact:
Vikram Bali
contact@bridgebio.com
(650)-789-8220
FAQ
What is the TRACE-AI Network Study initiated by BridgeBio (BBIO)?
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