<\/p>\n
Kendall Cortelyou,\u00a0School of Global Health Management and Informatics Director,\u00a0using the\u00a0artificial intelligence-based drug overdose prevention system.<\/p>\n
Courtesy of UCF Today\/Natalie Fedor<\/p>\n
A UCF professor is working to develop an artificial intelligence-based drug overdose prevention system that hopes to bring relief to communities affected by drug usage.<\/p>\n
Dr. Kendall Cortelyou, associate professor\u00a0of healthcare informatics\u00a0and director of the School of Global Health Management at UCF,\u00a0partnered with Project Overdose to create this system, which launched in 2025 across Florida.<\/p>\n
DrugTRAC, the AI system,\u00a0turns drug activity data into a trend-prediction system. The trends help\u00a0community and healthcare leaders be prepared for spikes in\u00a0drug usage, down to the zip code.\u00a0\u00a0<\/p>\n
The goal of\u00a0<\/a>DrugTRAC<\/a>\u00a0is to reduce harm and\u00a0anticipate\u00a0life-saving procedures within a geographic location.\u00a0\u00a0<\/p>\n \u201cWith this line of research, I had the ability to impact the community today,\u201d Cortelyou said.\u00a0<\/p>\n When Cortelyou first started working with Project Overdose, she said, police officers were rarely carrying Naloxone<\/a>,<\/a>\u00a0the drug that can reverse an opioid overdose. She said her early involvement entailed\u00a0lots of\u00a0community\u00a0outreach with first responders to emphasize the importance of Naloxone as a life-saving tool.\u00a0\u00a0<\/p>\n \u201cI literally get to see my research changing people\u2019s lives every day,\u201d Cortelyou said. \u201cIt\u2019s the most fulfilling thing that I\u2019ve ever done.\u201d\u00a0<\/p>\n Dr. Kendall Cortelyou,\u00a0associate professor and director for the School of Global Health Management and Informatics at UCF, works out of the Dr. Phillips Academic Commons building at the UCF Downtown campus. Cortelyou launched DrugTRAC with partners Project Overdose and Social Innovation Technologies to help prevent community overdoses.\u00a0<\/p>\n Rachel Jones<\/p>\n Cortelyou said the launch just before the Electric Daisy Carnival\u00a0in November of 2025 allowed the team to notify the community of an increase in fentanyl presence along the Interstate-4 corridor.\u00a0\u00a0<\/p>\n Health care professionals and police officers were\u00a0then\u00a0able to\u00a0have adequate supplies of Naloxone and community members could be more hyper-vigilant in knowing what\u00a0they are taking\u00a0based on live data, Cortelyou said.\u00a0\u00a0<\/p>\n Maintaining\u00a0people\u2019s interest, Cortelyou said, in the overdose crisis is still critical, and before\u00a0the\u00a0DrugTRAC\u00a0technology\u00a0was developed, drug data was only available\u00a0from\u00a012-18 months\u00a0prior.<\/p>\n Within six months, the team aims to make DrugTRAC\u00a0into a predictive trend model\u00a0through the use of machine-learning algorithms.\u00a0<\/p>\n Cortelyou said if there should be a spike in drug presence\u00a0in any of the ZIP codes covered by UCFPD, the department would be briefed to better protect students.\u00a0\u00a0<\/p>\n \u201cMake sure you know what you\u2019re taking, and make sure you have Naloxone,\u201d Cortelyou said as a final message to UCF students.\u00a0<\/p>\n Craig Mora, AI entrepreneur\u00a0and CEO at Social Innovation Technologies, developed\u00a0DrugTRAC\u00a0alongside Cortelyou.\u00a0Mora said his role was developing the technology, but that the difficulty is making sure that the information is\u00a0digestible.\u00a0\u00a0<\/p>\n \u201cKendall plays a critical role in translating complex toxicology data into meaningful intelligence,\u201d Mora said. \u201cHer understanding of substances, testing methodologies and public health context directly informs how we design and refine our algorithms, so the outputs are both accurate and actionable.\u201d\u00a0<\/p>\n Mora said his goal with developing this system, and the benefit of it being an AI model, is that it can learn the patterns drugs are likely to take and predict the trends.<\/p>\n He is hopeful the system can get to a point where it can predict these trends four to five weeks into the future \u2014 but at only nine months into the\u00a0project,\u00a0it\u00a0hasn\u2019t\u00a0reached that point in its evolution.\u00a0\u00a0<\/p>\n \u201cI have\u00a0been in\u00a0developing for about 25 years and have never found a way to give back until this project,\u201d Mora said. \u201cIf we save one life,\u00a0it\u2019s\u00a0all been worth it.\u201d\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"Kendall Cortelyou,\u00a0School of Global Health Management and Informatics Director,\u00a0using the\u00a0artificial intelligence-based drug overdose prevention system. 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