Bohémier C, Ignacio M, Lamy X, Slater G W
Department of Physics, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada.
Institut de Mathématiques de Toulouse, UMR 5219, Université de Toulouse, CNRS, UPS IMT, F-31062 Toulouse Cedex 9, France.
Int J Pharm. 2023 Mar 5;634:122674. doi: 10.1016/j.ijpharm.2023.122674. Epub 2023 Feb 1.
Drug release experiments and numerical simulations only give access to partial release data (i.e., within a finite time range t∈[0,t]). In this article, we propose fitting-based procedures to estimate the asymptotic time scales of the release process, namely the global relaxation time τ and the longest (or terminal) relaxation time τ, from partially sampled data of diffusion-controlled drug release systems. We test these procedures on both synthetic and experimental data using, as an example, the well-known Weibull function. Our results show that the Weibull function must be used with great care because the values of the fitting parameters can vary significantly depending on the ratio t/τ. Beyond their practical simplicity, the usefulness of our procedures is evidenced by the fact that: (1) the initial loading profile does not need to be known and (2) the chosen fitting function does not require any physical basis. These two advantages allow us to determine the diffusion coefficient of the molecules directly from the characteristic time τ.
药物释放实验和数值模拟只能获取部分释放数据（即，在有限的时间范围t∈[0,t]内）。在本文中，我们提出了基于拟合的程序，用于从扩散控制药物释放系统的部分采样数据中估计释放过程的渐近时间尺度，即全局弛豫时间τ和最长（或终端）弛豫时间τ。我们以著名的威布尔函数为例，在合成数据和实验数据上测试了这些程序。我们的结果表明，必须非常谨慎地使用威布尔函数，因为拟合参数的值会根据t/τ的比值而显著变化。除了实际操作简单之外，我们程序的实用性还体现在以下事实上：（1）不需要知道初始加载曲线，（2）所选的拟合函数不需要任何物理基础。这两个优点使我们能够直接从特征时间τ确定分子的扩散系数。
