Presentation description

The accuracy and efficiency of disease diagnoses are essential for making informed decisions regarding healthcare treatment and intervention. This research looks at the ability to rapidly diagnose Tuberculosis and other respiratory diseases by utilizing volatile organic biomarkers (VOBs), namely Methyl Nicotinate (MN), in an electrochemical solution containing copper salts. The process looks at specific redox reactions with copper ions and electrochemical profiles to differentiate between positive and negative tests. For our samples, Methyl Nicotinate is incorporated into a solution containing copper salt (CuCl2), sodium salt (NaCl), and deionized water, and is then processed with voltage on an electroactive sensor. With the results of this data, we are looking to train a machine learning algorithm to identify significant features exhibited in the plots of these tests, allowing us to create a baseline to determine a positive result. This project additionally assesses developing and testing a new Time-of-Flight Mass Spectroscopy method using Hydrogen as a carrier gas in the two-dimensional gas chromatograph, due to issues such as helium shortages. We aim to do this to provide a framework for future experimentation, as well as fill gaps in existing literature to better understand the processes. Due to the relevance of making disease diagnostics more efficient across the globe, this project seeks to solve one of the greatest healthcare problems in the modern era and provide a promising tool for rapid, non-invasive use in clinical settings.