Chapter 15. Computer Simulations in Pharmacokinetics and Pharmacodynamics
Synopsis
Author
Mr. Gourab Saha
Assistant Professor, Department of Pharmaceutics, College of Pharmaceutical Sciences, Berhampur, Mohada, Odisha, India
Abstract
Computer simulations have revolutionized the understanding and prediction of pharmacokinetic (PK) and pharmacodynamic (PD) processes in drug development. Advanced computational models integrate physiological parameters, drug properties, and patient characteristics to predict drug behavior in the body. These simulations employ complex mathematical algorithms to analyze drug absorption, distribution, metabolism, and excretion patterns while considering population variability. Modern PK/PD modeling incorporates artificial intelligence and machine learning to enhance prediction accuracy and optimize dosing regimens. Physiologically-based pharmacokinetic (PBPK) models utilize anatomical, physiological, and biochemical data to simulate drug disposition across different tissues and organs. Dynamic simulations assess drug-receptor interactions and subsequent physiological responses, providing insights into therapeutic effectiveness and potential adverse effects. Monte Carlo simulations generate probability distributions of PK/PD parameters, facilitating risk assessment and dosing strategy development. The combination of mechanistic modeling with empirical data analysis has enhanced understanding of drug behavior and improved the efficiency of pharmaceutical development processes.
Keywords: Pharmacokinetic Modeling; Pharmacodynamic Simulation; PBPK Models; Population Pharmacokinetics; Drug Development; Computer Simulation
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