Dr. Davide Verotta’s main research interests are in pharmacokinetics and pharmacodynamics (PKPD) and mathematical statistical (MS) modeling. In PKPD, his main areas of interest are: mechanistic modeling (where prior knowledge about parts of a PKPD system is embedded in the model describing it); the development of empirical models (where no prior knowledge is embedded in the model) to analyze, simulate and control; population PKPD modeling with particular regard to empirical methods for population data analysis. In MS modeling, his main interests are in linear and non-linear system analysis, control, and experimental design. He is involved in collaborative research with scientists and different investigators in PKPD and clinical therapy (notably HIV therapy) modeling. Additional areas of investigation are the use of Bayesian methods, in particular applied to pharmacogenomics and mechanistic modeling, fractional differential equations, and applications of functional data analysis to population PKPD.