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This book provides a user-friendly introduction to the Nonlinear Mixed Effects Modeling (NONMEM) system, the most powerful tool for pharmacokinetic / pharmacodynamic analysis. Introduces requisite background to using NONMEM/Phoenix NLME , covering data requirements, model building and evaluation. Provides examples of nonlinear modeling concepts and estimation basics with discussion on the model building process and applications of empirical Bayesian estimates in the drug development environment. Includes detailed chapters on data set structure, developing control streams for modeling and simulation, model applications, interpretation of NONMEM output and results. Using population approach, precise estimates of the pharmacokinetic parameters and their variability will be quantifiable and significant covariates will be identified.