Mohammed Azheruddin, Cournoyer Antoine, Gosselin Ryan
Department of Chemical & Biotechnological Engineering, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, Québec, Canada J1K 2R1.
Process Monitoring Automation and Control Group, Pfizer Global Supply, 17300 Trans-Canada Highway, Kirkland, Québec, Canada PQ H9J 2M5; and.
PDA J Pharm Sci Technol. 2023 Mar-Apr;77(2):55-66. doi: 10.5731/pdajpst.2020.012443. Epub 2022 Sep 19.
Near-infrared (NIR) spectroscopy (NIRS) is a widely accepted method of measuring moisture in pharmaceutical freeze-dried products, both during the process and in the finished products. Multiple NIR measurement approaches have been introduced to monitor product moisture in freeze-dried vials. However, the spatial moisture gradients within a vial have not been investigated in depth. Like any other point-focused process analytical technology (PAT) tool, a spectrum produced by NIRS represents an average over a given area of the product vial. Implementing a point-focused NIR on any random position without proper understanding of spatial moisture variations within the vial may severely impact the reliability of the results. The present work focuses on understanding the moisture distribution within freeze-dried vials. We performed an investigation using NIR tools, NIR chemical imaging (NIR-CI), and NIRS to understand the spatial variations in moisture on the outer surface (i.e., periphery) of the freeze-dried vials. To achieve this, the moisture distribution within individual vials was mapped using NIR images. Then, NIRS was used to determine the necessity of using multiple measurement points to produce robust models quantifying the moisture inside freeze-dried products. Overall, the results show a simplified version of the phenomenon in which non-homogenous distribution of moisture, as well as the non-uniform drying front, occur within the vials. The findings from the NIRS-based partial least squares (PLS) models indicate that to achieve reliable product/process information, measurements must be drawn from multiple measurement points on the surface of the freeze-dried products.
近红外(NIR)光谱法(NIRS)是一种广泛认可的用于测量药物冻干产品在冻干过程中和成品中的水分含量的方法。已经引入了多种近红外测量方法来监测冻干小瓶中的产品水分。然而,小瓶内的空间水分梯度尚未得到深入研究。与任何其他点聚焦过程分析技术(PAT)工具一样,近红外光谱法产生的光谱代表了产品小瓶给定区域上的平均值。在未正确了解小瓶内空间水分变化的情况下,在任何随机位置实施点聚焦近红外测量可能会严重影响结果的可靠性。目前的工作重点是了解冻干小瓶内的水分分布。我们使用近红外工具、近红外化学成像(NIR-CI)和近红外光谱法进行了一项研究,以了解冻干小瓶外表面(即周边)的水分空间变化。为了实现这一点,使用近红外图像绘制了单个小瓶内的水分分布。然后,使用近红外光谱法确定使用多个测量点来生成量化冻干产品内部水分的稳健模型的必要性。总体而言,结果显示了小瓶内水分分布不均匀以及干燥前沿不均匀这一现象的简化版本。基于近红外光谱法的偏最小二乘法(PLS)模型的研究结果表明,为了获得可靠的产品/过程信息,必须从冻干产品表面的多个测量点进行测量。