Abstract
Formulation design is an important phase in the drug development process. However, this process at an experimental level requires exhaustive experimental work. Excipient selection, prediction of solubility, encapsulation efficiency, release patterns, drug absorption, stability, and mechanism of nanoparticle formation are some of the essential steps in formulation design. The use of various computational tools, including quantitative structure-activity relationships (QSARs), molecular modeling, molecular mechanics, discrete element modeling, finite element method, computational fluid dynamics, and physiologically based pharmacokinetics (PBPK) modeling, help in the identification of drug product inadequacies and to recommend avenues for understanding complex formulation design in less time with lower investment. Here, we focus on computational modeling tools used in formulation design and its applications.
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