Pharmaceutical Development, Boehringer Ingelheim Pharma, 88397 Biberach an der Riss, Germany.
Pharmaceutical Development, Boehringer Ingelheim Pharma, 88397 Biberach an der Riss, Germany.
Int J Pharm. 2021 Apr 1;598:120209. doi: 10.1016/j.ijpharm.2021.120209. Epub 2021 Jan 23.
Fluid bed granulation (FBG) is used extensively in the pharmaceutical industry and it is known to be a complex process, because the final product quality of the FBG process is determined by a complex interplay between the process parameters, fluid dynamics, and material properties. Due to this complexity, the FBG process is inherently nonlinear and as such difficult to scale-up. The field of chemical engineering has shown that complex nonlinear processes can be assumed to be linear under limiting conditions. We leverage this idea and present a linear scale-up approach (LiSA) to the FBG process. We derive the key LiSA equation from first principles, and then use it in combination with the similarity principle for scale-up purposes. Furthermore, we present a novel regression-based LiSA. The regression-based LiSA is founded on the hypothesis that there is a linear relationship between the moisture content and a scaling parameter called the Maus factor. This hypothesis is based on our experience and it is shown to be plausible due to high R values ranging from 0.86 to 0.98. Moreover, we successfully demonstrate that LiSA is effective under typical industrial process settings by applying it to two different formulations during pharmaceutical drug product development.
流化床造粒（FBG）在制药行业中得到了广泛的应用，它是一个众所周知的复杂过程，因为 FBG 过程的最终产品质量是由工艺参数、流体动力学和材料特性之间的复杂相互作用决定的。由于这种复杂性，FBG 过程本质上是非线性的，因此难以放大。化学工程领域已经表明，复杂的非线性过程在极限条件下可以被假设为线性的。我们利用这个想法，提出了一种用于 FBG 过程的线性放大方法（LiSA）。我们从第一性原理推导出关键的 LiSA 方程，然后将其与相似性原理结合起来用于放大目的。此外，我们还提出了一种新的基于回归的 LiSA。基于回归的 LiSA 基于这样一个假设，即水分含量与一个称为 Maus 因子的缩放参数之间存在线性关系。该假设基于我们的经验，并且由于高达 0.86 到 0.98 的高 R 值，表明其是合理的。此外，我们通过在药物产品开发过程中应用于两种不同的配方，成功地证明了 LiSA 在典型的工业过程设置下是有效的。
