Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, United States.
GlaxoSmithKline (GSK), Collegeville, PA 19426, United States.
Int J Pharm. 2021 Jun 1;602:120594. doi: 10.1016/j.ijpharm.2021.120594. Epub 2021 Apr 20.
In-line measurements of low dose blends in the feed frame of a tablet press were performed for API concentration levels as low as 0.10% w/w. The proposed methodology utilizes the advanced sampling capabilities of a Spatially Resolved Near-Infrared (SR-NIR) probe to develop Partial Least-Squares calibration models. The fast acquisition speed of multipoint spectra allowed the evaluation of different numbers of co-adds and feed frame paddle speeds to establish the optimum conditions of data collection to predict low potency blends. The interaction of the feed frame paddles with the SR-NIR probe was captured with high resolution and allowed the implementation of a spectral data selection criterion to remove the effect of the paddles from the calibration and testing process. The method demonstrated accuracy and robustness when predicting drug concentrations across different feed frame paddle speeds.
在压片机的料斗中对低剂量混合物进行在线测量,API 浓度低至 0.10%w/w。所提出的方法利用空间分辨近红外(SR-NIR)探头的先进采样功能来开发偏最小二乘校准模型。多点光谱的快速采集速度允许评估不同数量的共加和料斗桨叶速度,以确定最佳数据采集条件,从而预测低效力混合物。通过高分辨率捕捉到料斗桨叶与 SR-NIR 探头的相互作用,从而可以实施光谱数据选择标准,以从校准和测试过程中去除桨叶的影响。该方法在预测不同料斗桨叶速度下的药物浓度时表现出准确性和稳健性。