Transthyretin Amyloidosis with cardiac myopathy, ATTR-CM, represent a serioushealthcare issue. ATTR-CM is involved in 13% of heart failure, 16% of transcatheter aortic-valve replacement,and 5% of individuals with presumed hypertrophic cardiomyopathy. The primary challenge is that mostpatients are undiagnosed or their diagnosis is delayed for multiple years. Since the damage ATTR-CM causesto the heart is progressive, diagnosis delays strongly impact prognosis and increase mortality. Diagnosis isproblematic for two reasons: ATTR-CM has a variable presentation and the prevalence is not high. Thus,ATTR-CM is often not considered during diagnosis and a more common diagnosis with similar symptoms isgiven erroneously. Up to 98% of patients are not diagnosed due to the low prevalence and variablepresentation. One study found that 32% of ATTR-CM patients had previously been misdiagnosed as havingmore common cardiovascular diseases. A readily-available genetic test can be used to detect hATTR and99mTc-DPD-scintigraphy can be used to diagnose ATTR-CM (both hereditary and wild type). Fortunately,once diagnosed, ATTR is treatable. Thus, the main challenge for ATTR-CM is diagnosis, not therapy. Aneffective and economical precision screening system is needed to find the individuals most at risk of ATTR-CM. Those identified via precision screening could be tested and, treated with effective therapy resulting insaved lives and reduced healthcare costs. Atomo's goal in this SBIR Fast-Track proposal is to create, optimizeand implement an AI-based Clinical Decisions Support System (CDSS) to identify probable yet undiagnosedATTR patients before they develop CM. For this work, we are partnering with Dr. Dan Rader and PENNMedicine. Dr. Rader is the Seymour Gray Professor of Molecular Medicine and Chair of the Department ofGenetics at the Perelman School of Medicine of the University of Pennsylvania. Dr. Rader also directs thePenn Medicine Biobank. We would utilize the BioBank to identify True Positive patients to train and evaluatean AI model to find probable yet undiagnosed ATTR individuals. The model would be used in a pilot, mostlikely as a quality improvement initiative. To complete this work, Atomo will leverage its proven MLtechnologies that have been used and verified clinically, with published in peer-reviewed journals. The ATTRAI model would be commercialized as an Insights As A Service (IaaS) CDSS.
Public Health Relevance Statement: Transthyretin Amyloidosis with cardiac myopathy, ATTR-CM, represent a serious healthcare issue. ATTR-CM is involved in 13% of heart failure, 16% of transcatheter aortic-valve replacement, and 5% of individuals with presumed hypertrophic cardiomyopathy. The primary challenge is that most patients are undiagnosed or their diagnosis is delayed for multiple years. Atomo, in partnership with PENN Medicine, will develop an AI-based Clinical Decision Support Solution called "PERCEPTION" that will flag probable yet undiagnosed ATTR individuals before they develop CM so they can be clinically evaluated and receive the proper diagnosis and therapy.
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