Vivek Venu

Project Lead
CardiAI.Inc​
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Dr. Venu completed his PhD in Cardiovascular diseases where he studied the role of fibronectin splice variants in atherosclerosis from University of Milan, Italy. He then did his PDF with Dr. Sam Parthasarthy, UCF, Florida and then moved to University of Calgary, Canada for his next PDF with Prof. Morley Hollenberg. Here, he studied the role of orphan receptors in the vascular function. Through this training he published over 10+ articles in the field of drug interaction with receptors. He joined CardiAi in 2020 as a research scientist and worked on molecular biology and developed LAMP based detection of SARS-Cov2. The test was provided to various destinations in Canada. Post-Covid, he is now working on developing rapid point of care diagnostics for cardiac biomarkers. Their team currently focuses on developing POCT devices for cardiac and chronics disorders.
 

Speech title & Synopsis

Development of Rapid Point of care Diagnostics for Cardiac Biomarkers – Role of artificial intelligence 

Heart failure (HF) remains as one of the leading cause of death globally. The condition that starts with left ventricular dysfunction can occur as a part of coronary heart disease and myocardial diseases. If the left ventricular dysfunction is left untreated can lead to HF. HF markers, measuring NT-proBNP, D-dimer, and cTnI together provides a comprehensive assessment for patients with acute cardiac or thromboembolic symptoms. NT-proBNP is highly sensitive for heart failure diagnosis and risk stratification, while D-dimer is a sensitive marker for ruling out venous thromboembolism, such as pulmonary embolism, especially in low-risk patients. cTnI is the gold standard for detecting myocardial injury, such as acute myocardial infarction. Individually, NT-proBNP points to cardiac dysfunction or heart failure, D-dimer indicates active clot formation and breakdown, and cTnI signals myocardial cell damage. When combined, these markers improve diagnostic specificity and confidence, particularly in complex cases like dyspnea or suspected pulmonary embolism, where their joint interpretation can help distinguish between cardiac and thromboembolic causes, guide risk stratification, and potentially reduce unnecessary imaging or interventions.The rapid detection of these markers at remote, at-home and off-grid areas help in disease mitigation. This project aims to address the needs of at-home testing which requires sensitivity to the limit of detection, while for  hospitals which require highly sensitive test. Here we discuss the work performed by CardiAI towards the pathway of achieving the product development.