Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, PA 15282, United States; Duquesne Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, PA 15282, United States.
Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, PA 15282, United States; Duquesne Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, PA 15282, United States.
Int J Pharm. 2023 Oct 15;645:123354. doi: 10.1016/j.ijpharm.2023.123354. Epub 2023 Aug 28.
Near-infrared (NIR) spectroscopy is a powerful process analytical tool for monitoring chemical constituents in continuous pharmaceutical processes. However, the density variation introduced when quantitative NIR measurements are performed on powder streams at different flow rates is a potential source of a lack of model robustness. Since different flow rates are often required to meet the production requirements (e.g., during scale-up) of a continuous process, the development of efficient strategies to characterize, understand, and mitigate the impact of powder density on NIR measurements is highly desirable. This study focused on assessing the effect of powder physical variation on NIR by enabling the in-line characterization of powder stream density in a simulated continuous system. The in-line measurements of powder stream density were facilitated through a unique analytical interface to a flowing process. Powder streams delivered at various design levels of flow rate and tube angle were monitored simultaneously by NIR diffuse reflectance spectroscopy, live imaging, and dynamic mass characterization. Statistical analysis and multivariate modeling confirmed powder density as a significant source of spectral variability due to flow rate. Besides providing broader process understanding, results elucidated potential mitigation strategies to facilitate effective continuous process scale-up while ensuring NIR model robustness against density.
近红外（NIR）光谱学是一种强大的过程分析工具，可用于监测连续制药过程中的化学成分。然而，在不同流速下对粉末流进行定量 NIR 测量时引入的密度变化是模型稳健性不足的潜在来源。由于连续过程的生产要求（例如在放大规模时）通常需要不同的流速，因此开发有效的策略来表征、理解和减轻粉末密度对 NIR 测量的影响是非常可取的。本研究通过在模拟连续系统中实现粉末流密度的在线表征，重点评估了粉末物理变化对 NIR 的影响。通过与流动过程的独特分析接口，实现了粉末流密度的在线测量。通过近红外漫反射光谱、实时成像和动态质量表征，同时监测了以不同设计流速和管角度输送的粉末流。统计分析和多元建模证实，由于流速，粉末密度是光谱可变性的重要来源。除了提供更广泛的过程理解外，结果还阐明了潜在的缓解策略，以促进有效的连续过程放大，同时确保 NIR 模型对密度具有稳健性。
