The overall goal of the Severe Asthma Research Program (SARP) is to develop a new paradigm for the understanding of severe asthma and its sub-phenotypes, in children and adults, by defining disease longitudinally at the molecular and cellular level. The Department of Public Health Sciences at the Penn State College of Medicine proposes to serve as the Clinical Coordinating Center (CCC) for SARP. The CCC will provide biostatistical leadership and scientific coordination for SARP; design and maintain the SARP operations management system; provide logistical and communications support for SARP; and distribute funds for a shared longitudinal protocol. The Department of Public Health Sciences is uniquely qualified to serve as the Clinical Coordinating Center for SARP, as the home of the Asthma Clinical Research Network (ACRN) and the Childhood Asthma Research and Education (CARE) Data Coordinating Centers since their inceptions in 1993 and 1999, respectively, and the AsthmaNet DCC since 2009. The PI and core biostatistician of this application is David T. Mauger, PhD, who is currently the PI of the CARE and Asthma Net DCCs. Dr. Mauger will head a DPHS team well-experienced in data collection and management, biostatistical design and analysis, quality control, network infrastructure development and maintenance, and working with national repositories and oversight committees. This application also includes a very strong clinical co-investigator with extensive research experience in asthma, Joanna Floros, PhD. Although there will be many clinician investigators at the network clinical centers who are leaders in the field, frequent, direct interaction between CCC personnel and local co-investigators with clinical expertise greatly facilitates the activities of the CCC. In summary, through its long history of managing successful data coordinating centers, Penn State College of Medicine's Department of Public Health Sciences is well poised to successfully implement and execute the Severe Asthma Research Program.
By integrating genetic, epigenetic, genomic and other approaches to identify pathobiologic processes and validate biomarkers that correlate over time with sub-phenotype progression, we expect to develop practical biomarker-based tools to predict loss of symptom control and risk of exacerbation. This will serve to ameliorate a part of the burden of Asthma, a disease which affects 22 million people in the United States.
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