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SELECTBIO Conferences POC Diagnostics, Global Health-Viral Diseases 2017

John T McDevitt's Biography

John T McDevitt, Professor, Division of Biomaterials, New York University College of Dentistry Bioengineering Institute

John T. McDevitt now serves as a Full Professor within the Division of Biomaterials within the Department of Molecular Pathobiology at New York University, is a member of NYU’s Bioengineering Institute and participates as a distinguished faculty member in the NYU Department of Chemical and Biomolecular Engineering within the Tandon School of Engineering at NYU. Prior to this time, McDevitt served as the Chair of the Department of Biomaterials at NYU, the Brown-Weiss Professor of Bioengineering/Chemistry at Rice University, the Director of the Gulf Coast Consortium on early Disease Detection within the Texas Medical Center and a Full Professor of Chemistry and Biochemistry at University of Texas at Austin. McDevitt completed his Ph.D. degree in Chemistry from Stanford University.

Professor McDevitt is a pioneer in the development of ‘programmable bio-nano-chip’ technologies. He has a strong track record of translating essential bioscience, artificial intelligence and medical microdevice discoveries into real-world clinical practice. In this capacity, he has served as the Scientific Founder for a number of diagnostic and clinical services companies including OraLiva which features smart diagnostics for early disease detection as well as SensoDx which develops and monetizes programmable diagnostic hardware. McDevitt and his team have raised over $45M in Federal and Foundation support for academic efforts and over $50M to support commercial diagnostic activities. McDevitt and his team have process over 100 patent and patent applications. His recent research has been sponsored by major programs funded by National Institute of Dental and Craniofacial Research (NIDCR) division of the National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA) at NIH, Bill and Melinda Gates Foundation, Cancer Prevention Research Institute of Texas (CPRIT), NASA (National Aeronautics and Space Administration), Renaissance Health Service Corporation (Delta Dental of MI), the Army and the United Kingdom’s Home Office Scientific Development Branch.

McDevitt and his team have written more than 200 peer-reviewed scientific manuscripts and have contributed. This work was recognized with the “2020 People’s Choice Award for the TOPx COVID-19 initiative”, “2016 AACC Wallace H. Coulter Lectureship Award,” “Best of What's New Award” in the Medical Device Category by Popular Science as well as for the “Best Scientific Advances Award” by the Science Coalition. Dr. McDevitt’s individual honors include the Presidential Young Investigator Award, the California Polytechnic Distinguished Alumni Award and the Exxon Education Award. Over the past years, Dr. McDevitt has served as the Principal Investigator for 6 major clinical trials and 2 clinical pilot studies, all involving the programmable bio-nano-chip. Through these clinical efforts, mini-sensor ensembles are being developed for major diseases in the areas of COVID-19 disease severity, oral cancer, cardiac heart disease, trauma, drugs of abuse, ovarian cancer and prostate cancer.

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Programmable Bio-Nano-Chip Platform: A Point-of-Care Biosensor System with the Capacity to Learn

Tuesday, 3 October 2017 at 10:00

Add to Calendar ▼2017-10-03 10:00:002017-10-03 11:00:00Europe/LondonProgrammable Bio-Nano-Chip Platform: A Point-of-Care Biosensor System with the Capacity to LearnPOC Diagnostics, Global Health-Viral Diseases 2017 in Coronado Island, CaliforniaCoronado Island,

The combination of point-of-care (POC) medical microdevices and machine learning has the potential transform the practice of medicine. In this area, scalable lab-on-a-chip (LOC) devices have many advantages over standard laboratory methods, including faster analysis, reduced cost, lower power consumption, and higher levels of integration and automation. Despite significant advances in LOC technologies over the years, several remaining obstacles are preventing clinical implementation and market penetration of these novel medical microdevices. Similarly, while machine learning has seen explosive growth in recent years and promises to shift the practice of medicine toward data-intensive and evidence-based decision making, its uptake has been hindered due to the lack of integration between clinical measurements and disease determinations. In this talk, recent developments in the programmable bio-nano-chip (p-BNC) system, a biosensor platform with the capacity for learning will be highlighted. The p-BNC is a ‘platform to digitize biology’ in which small quantities of patient sample generate immunofluorescent signal on agarose bead sensors that is optically extracted and converted to antigen concentrations. The platform comprises disposable microfluidic cartridges, a portable analyzer, automated data analysis software, and intuitive mobile health interfaces. The single-use cartridges are fully integrated, self-contained microfluidic devices containing aqueous buffers conveniently embedded for POC use. A novel fluid delivery method was developed to provide accurate and repeatable flow rates via actuation of the cartridge’s blister packs. A portable analyzer instrument was designed to integrate fluid delivery, optical detection, image analysis, and user interface, representing a universal system for acquiring, processing, and managing clinical data while overcoming many of the challenges facing the widespread clinical adoption of LOC technologies. We demonstrate here the p-BNC’s flexibility through the completion of multiplex assays within the single-use disposable cartridges for numerous clinical applications including prostate cancer, ovarian cancer, and acute myocardial infarction. Toward the goal of creating ‘sensors that learn’, we have developed and describe here the Cardiac ScoreCard, a clinical decision support system for a spectrum of cardiovascular disease. The Cardiac ScoreCard approach comprises a comprehensive biomarker panel and risk factor information in a predictive model capable of assessing early risk and late-stage disease progression for heart attack and heart failure patients.

Add to Calendar ▼2017-10-02 00:00:002017-10-04 00:00:00Europe/LondonPOC Diagnostics, Global Health-Viral Diseases 2017POC Diagnostics, Global Health-Viral Diseases 2017 in Coronado Island, CaliforniaCoronado Island,