Pharmacokinetic and Statistical Modeling

The statistical modeling with numerical simulation are important analytical process involving various steps to optimize the clinical data sets, it is fundamental tool in mathematical science that have been used extensively and for a long period of time in various disciplines of science (medical, clinical, agricultural, astronomical, physical, etc.). Advanced numerical simulation techniques should be eagerly used for mathematical and statistical derivations for taking clinical decision about the population, the demonstrated models which are simplified descriptions of complex system under research investigations at micro and macro level. In this chapter, we have discussed different and new advanced pharmacokinetic (PK) models like Brownian, random walk, and Quadratic regression and are demonstrated by real data sets, and we also discuss the basic principles of formulation of PK models and suitable derivations. The post hoc tests were employed for testing fitted mathematical models. The models clearly integrate the contents related to various pharmacokinetic intervention and supplements the real data for derivation of model at greater accuracy and higher precision. The present analytical research findings describe briefly with suitable illustrations and eye-catching charts and diagrams. Therefore, the reader can easily refer formulated models as a reference book for their research interventions.