Shi Zhenqi, Rao Kallakuri Suparna, Thool Prajwal, Kuhn Robert, Thomas Rekha, Rich Sharyl, Mao Chen
Small Molecule Pharmaceutical Sciences, Genentech Inc, 1 DNA Way, South San Francisco, California, 94080, USA.
AAPS J. 2022 Dec 8;25(1):9. doi: 10.1208/s12248-022-00775-1.
With the advent of continuous direct compression (CDC) process, it becomes increasingly desirable to characterize inherent powder blend heterogeneity at a small batch scale for a robust and CDC-amenable formulation. To accomplish this goal, a near infrared spectroscopy (NIRS)-based characterization approach was developed and implemented on multiple direct compression (DC) blends in this study, with the intended purpose of complementing existing formulation development tools and enabling to build an early CMC data package for late-phased process analytical technology (PAT) method development. Three fumaric acid DC blends, designed to harbor varied degrees of inherent blend heterogeneity, were employed. Near infrared spectral data were collected on a kg-scale batch blender via both time- and angle-based triggering modes. The time-triggered data were used to investigate the blending heterogeneity with respect to rotation angles, while the angle-triggered data were used to provide blending variability characterization and compare against off-line HPLC-based results. The time-triggered data revealed that the greatest blend variability was observed between revolutions, while the blending variability within a single revolution stayed relatively low with respect to rotation angles. This confirmed earlier literature findings that the bottom layer of powder blends tends to move with the blender within each revolution, and the most intense powder mixing takes place across revolutions. This also indicates the use of blending speed and the number of co-adds are not able to increase sampling volume to improve signal-to-noise ratio under a tumble-bin blender as what were typically done in a feedframe application. The angle-triggered data showed that there is a consistent trend between NIRS and HPLC-based methods on characterizing blend heterogeneity across the blends at a given sample size. This study contributes to establishing NIRS as a potential characterization approach for inherent powder blend heterogeneity for early R&D. It also highlights the promise of continuous characterization of inherent powder blend heterogeneity from gram scale to mini-batch CDC scale.
随着连续直接压片(CDC)工艺的出现,越来越需要在小批量规模下对粉末混合物固有的不均匀性进行表征,以获得稳健且适用于CDC的配方。为实现这一目标,本研究开发并实施了一种基于近红外光谱(NIRS)的表征方法,用于多种直接压片(DC)混合物,旨在补充现有的配方开发工具,并为后期过程分析技术(PAT)方法开发建立早期的关键质量属性(CMC)数据包。使用了三种富马酸DC混合物,其设计具有不同程度的固有混合物不均匀性。通过基于时间和角度的触发模式,在千克级批量混合器上收集近红外光谱数据。时间触发数据用于研究混合不均匀性与旋转角度的关系,而角度触发数据用于提供混合变异性表征,并与基于离线高效液相色谱(HPLC)的结果进行比较。时间触发数据表明,在各次旋转之间观察到最大的混合变异性,而在单次旋转内,混合变异性相对于旋转角度保持相对较低。这证实了早期文献的发现,即粉末混合物的底层在每次旋转中倾向于随混合器移动,并且最剧烈的粉末混合发生在各次旋转之间。这也表明,在转鼓式混合器下,与在进料框架应用中通常所做的不同,使用混合速度和共添加次数并不能增加采样量以提高信噪比。角度触发数据表明,在给定样品量下,NIRS和基于HPLC的方法在表征混合物之间的混合不均匀性方面存在一致的趋势。本研究有助于将NIRS确立为早期研发中粉末混合物固有不均匀性的潜在表征方法。它还突出了从克级到小批量CDC规模连续表征粉末混合物固有不均匀性的前景。