Release modelling of nanoencapsulated food ingredients by probabilistic models: Cellular Automata and Monte Carlo Methods

Abstract Probabilistic modeling methods have found increasing importance in recent years, driven by concurrent growth in computing power with applications in the modeling of many fields of science, engineering, and medicine. This has been due not just to method scope and flexibility, but also in no small part to advance in computing capacity and interconnection speed and commensurate decreases in the costs of these. In this chapter, we review the literature on probabilistic methods with their different and varied forms, and describe the theory of the methods, together with practical applications in the fields of drug delivery systems in the pharmaceutical industry and nanoencapsulation within the food industry.