Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
CPT Pharmacometrics Syst Pharmacol. 2018 May;7(5):331-341. doi: 10.1002/psp4.12290. Epub 2018 Mar 25.
Reusing published models saves time; time to be used for informing decisions in drug development. In antihyperglycemic drug development, several published HbA1c models are available but selecting the appropriate model for a particular purpose is challenging. This study aims at helping selection by investigating four HbA1c models, specifically the ability to identify drug effects (shape, site of action, and power) and simulation properties. All models could identify glucose effect nonlinearities, although for detecting the site of action, a mechanistic glucose model was needed. Power was highest for models using mean plasma glucose to drive HbA1c formation. Insulin contribution to power varied greatly depending on the drug target; it was beneficial only if the drug target was insulin secretion. All investigated models showed good simulation properties. However, extrapolation with the mechanistic model beyond 12 weeks resulted in drug effect overprediction. This investigation aids drug development in decisions regarding model choice if reusing published HbA1c models.
复用已发表的模型可以节省时间；这些时间可用于为药物开发中的决策提供信息。在抗高血糖药物开发中，有几个已发表的 HbA1c 模型可供使用，但选择适合特定目的的合适模型具有挑战性。本研究旨在通过研究四个 HbA1c 模型来帮助选择，特别是识别药物作用（形状、作用部位和功效）和模拟特性的能力。所有模型都能够识别葡萄糖作用的非线性，尽管需要使用基于机制的葡萄糖模型来检测作用部位。使用平均血浆葡萄糖驱动 HbA1c 形成的模型具有最高的功效。胰岛素对功效的贡献取决于药物靶点，只有当药物靶点是胰岛素分泌时，它才有益。所有研究的模型都表现出良好的模拟特性。然而，在 12 周之后，使用基于机制的模型进行外推会导致药物作用过度预测。如果要重复使用已发表的 HbA1c 模型，那么本研究有助于在模型选择方面为药物开发提供决策依据。
