Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands.
Department of Pharmacokinetics, Toxicology and Targeting, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, the Netherlands.
AAPS J. 2020 Dec 24;23(1):10. doi: 10.1208/s12248-020-00549-7.
The relationship between the concentration of a drug and its pharmacological effect is often described by empirical mathematical models. We investigated the relationship between the steepness of the concentration-effect relationship and inter-individual variability (IIV) of the parameters of the sigmoid E model, using the similarity between the sigmoid E model and the cumulative log-normal distribution. In addition, it is investigated whether IIV in the model parameters can be estimated accurately by population modeling. Multiple data sets, consisting of 40 individuals with 4 binary observations in each individual, were simulated with varying values for the model parameters and their IIV. The data sets were analyzed using Excel Solver and NONMEM. An empirical equation (Eq. (11)) was derived describing the steepness of the population-predicted concentration-effect profile (γ*) as a function of γ and IIV in C50 and γ, and was validated for both binary and continuous data. The tested study design is not suited to estimate the IIV in C50 and γ with reasonable precision. Using a naive pooling procedure, the population estimates γ* are significantly lower than the value of γ used for simulation. The steepness of the population-predicted concentration-effect relationship (γ*) is less than that of the individuals (γ). Using γ*, the population-predicted drug effect represents the drug effect, for binary data the probability of drug effect, at a given concentration for an arbitrary individual.
药物浓度与其药效之间的关系通常用经验数学模型来描述。我们使用 sigmoid E 模型与累积对数正态分布之间的相似性，研究了浓度-效应关系的陡峭程度与 sigmoid E 模型参数的个体间变异性（IIV）之间的关系。此外，还研究了通过群体建模是否可以准确估计模型参数中的 IIV。使用 Excel Solver 和 NONMEM 对具有 40 个个体和每个个体 4 个二项观测值的多个数据集进行了模拟，这些数据集的模型参数及其 IIV 值各不相同。基于群体预测的浓度-效应曲线的陡峭程度（γ*）作为 γ 和 C50 中的 IIV 和 γ 的函数，推导出了一个经验方程（式（11）），并对二项式和连续数据进行了验证。所测试的研究设计不适合以合理的精度估计 C50 和 γ 中的 IIV。使用简单的合并程序，群体估计值γ显著低于模拟所用的γ值。群体预测的浓度-效应关系的陡峭程度（γ）小于个体的陡峭程度（γ）。使用γ*，群体预测的药物效应代表了在给定浓度下任意个体的药物效应，对于二项数据则代表药物效应的概率。
Zotero 插件
