Chapter 2. Statistical Modeling in Pharmaceutical Research and Development
Synopsis
Author
Mr. Zeeshan Ansari
PG Scholar, Dept. of Pharmacology, School of Pharmaceutical Sciences, CSJM University, Kanpur, Uttar Pradesh, India
Abstract
Statistical modeling stands as a cornerstone in pharmaceutical research and development, bridging theoretical frameworks with practical drug development applications. The comprehensive exploration of descriptive and mechanistic modeling approaches provides crucial insights into drug behavior and development processes. Through systematic examination of statistical parameters, estimation techniques, and confidence regions, researchers can make informed decisions in drug development pathways. The analysis of nonlinearity at optimal points, coupled with robust sensitivity analyses, enables precise model validation and optimization. Optimal design strategies enhance experimental efficiency while minimizing resource utilization. Population modeling approaches complete the framework by addressing drug behavior across diverse patient groups, ultimately contributing to more effective and targeted therapeutic solutions. The integration of these statistical methodologies provides a robust foundation for modern pharmaceutical development, enabling data-driven decision-making and enhanced drug development outcomes.
Keywords: Statistical modelling; Pharmaceutical research; Descriptive modelling; Mechanistic modelling; Parameter estimation; Confidence regions; Sensitivity analysis; Optimal design; Population modelling; Nonlinear optimization
. 