Technical Research and Development, Novartis Pharmaceuticals Corporation, One Health Plaza, East Hanover, NJ 07936, United States.
J Pharm Biomed Anal. 2011 Jun 1;55(3):429-34. doi: 10.1016/j.jpba.2011.02.017. Epub 2011 Feb 18.
A multivariate calibration approach using near-infrared (NIR) spectroscopy for determining blend uniformity end-point of a pharmaceutical solid dosage form containing 29.4% (w/w) drug load with three major excipients (crospovidone, lactose, and microcrystalline cellulose) is presented. A set of 21 off-line, static calibration samples were used to develop a multivariate partial least-squares (PLS) calibration model for on-line predictions of the API content during the blending process. The concentrations of the API and the three major excipients were varied randomly to minimize correlations between the components. A micro-electrical-mechanical-system (MEMS) based NIR spectrometer was used for this study. To minimize spectral differences between the static and dynamic measurement modes, the acquired NIR spectra were preprocessed using standard normal variate (SNV) followed by second derivative Savitsky-Golay using 21 points. The performance of the off-line PLS calibration model were evaluated in real-time on 67 production scale (750L bin size) blend experiments conducted over 3 years. The real-time API-NIR (%) predictions of all batches ranged from 93.7% to 104.8% with standard deviation ranging from 0.5% to 1.8%. These results showed the attainment of blend homogeneity and were confirmed with content uniformity by HPLC of respective manufactured tablets values ranging from 95.4% to 101.3% with standard deviation ranging from 0.5% to 2.1%. Furthermore, the performance of the PLS calibration model was evaluated against off-target batches manufactured with high and low amounts of water during the granulation phase of production. This approach affects the particle size and hence blending. All the off-target batches exhibited API-NIR (%) predictions of 94.6% to 103.5% with standard deviation ranging from 0.7% to 1.9%. Using off-target data, a systematic approach was developed to determine blend uniformity end-point. This was confirmed with 3 production scale batches whereby the blend uniformity end-point was determined using the PLS calibration model. Subsequently, the uniformity was also ascertained with conventional thief sampling followed by HPLC analysis and content uniformity by HPLC of the manufactured tablets.
本文提出了一种使用近红外(NIR)光谱法测定含有 29.4%(w/w)药物负荷的药物固体制剂混合均匀终点的多元校准方法,该药物固体制剂含有三种主要赋形剂(交联聚维酮、乳糖和微晶纤维素)。使用一组 21 个离线静态校准样品建立了多元偏最小二乘(PLS)校准模型,以便在线预测混合过程中 API 的含量。API 和三种主要赋形剂的浓度随机变化,以最小化各成分之间的相关性。本研究使用基于微机电系统(MEMS)的 NIR 光谱仪。为了最小化静态和动态测量模式之间的光谱差异,使用标准归一化变量(SNV)预处理采集的 NIR 光谱,然后使用 21 个点进行二阶导数 Savitzky-Golay 处理。离线 PLS 校准模型的性能在过去 3 年中进行的 67 批生产规模(750L 料仓大小)混合实验中进行了实时评估。所有批次的实时 API-NIR(%)预测值范围为 93.7%至 104.8%,标准偏差范围为 0.5%至 1.8%。这些结果表明实现了混合均匀性,并通过 HPLC 对各自制造的片剂值进行了确认,其含量均匀性范围为 95.4%至 101.3%,标准偏差范围为 0.5%至 2.1%。此外,还评估了 PLS 校准模型对生产过程中造粒阶段添加高水量和低水量的目标外批次的性能。这会影响颗粒大小,从而影响混合。所有目标外批次的 API-NIR(%)预测值范围为 94.6%至 103.5%,标准偏差范围为 0.7%至 1.9%。使用目标外数据,开发了一种系统方法来确定混合均匀终点。通过 3 批生产规模批次验证了这一点,其中使用 PLS 校准模型确定了混合均匀终点。随后,通过传统的小偷取样进行了均匀性的进一步确定,并通过 HPLC 分析和制造片剂的 HPLC 含量均匀性进行了确认。