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.

制剂设计是药物开发过程中的重要阶段。但是，这个实验阶段的过程需要详尽的实验工作。辅料的选择，溶解度的预测，包封效率，释放方式，药物吸收，稳定性以及纳米颗粒形成的机理是制剂设计中的一些必要步骤。使用各种计算工具，包括定量构效关系（QSAR），分子模型，分子力学，离散元素模型，有限元方法，计算流体动力学和基于生理学的药代动力学（PBPK）模型，有助于识别药物产品上的不足之处，并提供建议途径，以便在较短的时间内以较低的投资了解复杂的配方设计。这里，