301 Pharmacy Lane, Room 3208, CB# 7569, Chapel Hill, NC, 27599
Many scientific studies propose wonderful new hypotheses or novel techniques. However, many investigators struggle with how to quantify the uncertainty in their results or approach to unexpected complexities in their data. Therefore, Matthew Loop, Ph.D., became a biostatistician in order to improve the quantification of scientific knowledge, particularly concerning human disease, its causes, and potential therapies. As an assistant professor in the Division of Pharmacotherapy and Experimental Therapeutics at the UNC Eshelman School of Pharmacy, Dr. Loop uses cutting-edge statistical models to understand complex data in research studies of human health, with particular focus on cardiovascular diseases, infectious diseases such as HIV/AIDS and malaria, and population-level exposures such as air pollution. To address the complexities of these data, Dr. Loop has expertise in spatial data analysis, supervised and unsupervised machine learning, and Bayesian multilevel modeling. His training in both biostatistics and epidemiology allows him to answer high-impact questions on human disease with the best methods currently available. These expertise are critical components of advancing scientific understanding of human diseases and delivering safe and effective therapies to treat them.
This project is led by Dr. Michelle Meyer in the Emergency Medicine Department at UNC. The goal is to measure pulse wave velocity (a proxy for arterial stiffness) among participants in the Jackson Heart Study (JHS) and determine its relationship to cognitive decline in later life, using the cognitive function surveillance in JHS. One aim will also leverage PWV collected among participants who are also participating in the Atherosclerosis Risk In Communities (ARIC) study to analyze changes in PWV over time.
This project is co-led by Dr. Rachel Urrutia in the Department of Obstetrics and Gynecology at UNC and Dr. Melissa Daubert in the Department of Medicine at Duke University. The goal is to understand the blood pressure outcomes of women who were diagnosed with a hypertensive disorder of pregnancy and gave birth at either Duke or UNC medical centers. The cohort consists of approximately 9,000 women, with data on medical history, pregnancy, and cardiovascular outcomes collected using the electronic medical record through the Carolinas Collaborative database.
This project is led by Dr. Dominick Lemas in the Department of Health Outcomes and Biomedical Informatics at the University of Florida. The goal is to understand how maternal health, mode of delivery, and breastfeeding outcomes affect pediatric outcomes, specifically pediatric obesity. This project uses natural language processing to create structured data on breastfeeding outcomes using clinical notes found in the electronic medical record among approximately 16,000 deliveries. Additional data include maternal and neonatal medications, vaccines, and antibiotic episodes in the first 2 years of life.