Prof Anna Bershteyn
NYU, Grossman School of Medicine, U.S.A.
Prof. Diego F Cuadros, University of Cincinnati
Dr. Diego Cuadros is an Associate Professor of Digital Epidemiology at the University of Cincinnati. Dr. Cuadros earned his Ph.D. degree in Biology at the University of Kentucky and holds a B.Sc. degree in Biology from the National University of Colombia.
Before joining UC in 2016, he served as a Postdoctoral Research Associate at Weill Cornell Medicine in Qatar and a Research Fellow at the University of KwaZulu-Natal in South Africa. Dr. Cuadros is an epidemiologist with strong mathematical and computational skills specialized in quantitative epidemiology, particularly in the study of geospatial patterns of disease distribution, and pathogen-pathogen interactions.
He has an extensive experience in the study of the spatial epidemiology of communicable and noncommunicable diseases in different regions of the world, including Africa, Latin America, and North America.
In this presentation, Dr. Cuadros will provide an overview of the epidemiology and health policy related to the COVID-19 pandemic in the U.S. with a focus on Ohio, an early public health leader in the US. He will also describe the creation of predictive models and linking these models to available healthcare resources using advanced geospatial mapping and mathematical modelling techniques.
Ene I. Ette, BS Pharm (Hons), B.Sc. (Hons), M.Sc., MBA, Ph.D., FCP, FCCP, FAAPS
Most of drug development continues expensive, time consuming, and inefficient, while pharmacotherapy often is practiced at suboptimal levels of performance. This trend has not waned despite the availability of massive amounts of drug data. Within these massive amounts of data (big data), knowledge that would improve drug development and pharmacotherapy lays hidden and undiscovered. A systematic application of pharmacometrics to drug development has the potential to significantly improve drug development and pharmacotherapy enabling the making of model-informed decisions to promote rational drug development and precision medicine. The presentation will focus on how pharmacometrics, through the use of mathematical models, enables knowledge extraction from drug development and pharmacotherapy data and the leveraging of such knowledge across different phases of drug development thereby aiding model-informed drug development and precision in pharmacotherapy.
Pharmacometrics, which incorporates disease progression modelling, is a valuable tool in drug development and rational pharmacotherapy. This introductory workshop has been designed to provide the necessary information about the theory underlying the practice of pharmacometrics, and to provide foundational understanding of the tools required for pharmacometric analyses. Examples relevant to the local context will be presented and used to provide details of the practical application of pharmacometrics. The facilitators will provide examples from their experience in model-informed drug development. This workshop is relevant to students, scientists and managers in academia, industry and regulatory institutions.