PBPK分析使用结合生理学、群体和药物特征的模型和模拟来机械地描述药物的药代动力学（PK）行为。在药物的整个生命周期中，PBPK模型预测可用于支持是否、何时以及如何进行某些临床药理学研究的决策，并支持产品标签中的剂量建议。
作为一个迭代过程，PBPK建模可以从非常有限的信息开始，也可以在药物开发的任何一点上进行。有时，在整个开发过程中会多次使用和优化模型。
例如，一个小分子的非常简单的PBPK模型可以仅用分子结构信息和预测的物理化学性质来启动。这个模型可以用来指导未来的研究设计，在那里，额外的数据可以反馈到模型中，以创建一个更准确的预测。这个过程可以在整个开发过程中重复，以便在模型走向临床时进一步细化模型。
一年一次诊所，实际的人体PK数据可用于验证/告知模型，从而改进和简化临床研究设计。
While PBPK is not specifically required for a regulatory filing, the FDA has issued the 2018 FDA Guidance on PBPK Modeling Submissions and has strongly suggested including modeling in your data package. In addition, the 2017 EMA guideline for first-in-human (FIH) dosing recommends that estimation of FIH should be based on state-of-the-art modelling (e.g. PK/PD and PBPK) and/or using allometric factors.
PBPK can be used to support drug-drug interaction assessments and, in some cases, has been accepted in lieu of running clinical DDI studies.
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