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采用质量源于设计原理,建立近红外法测定多结构类似物药物制剂均匀度的方法。

Development of a NIR-based blend uniformity method for a drug product containing multiple structurally similar actives by using the quality by design principles.

机构信息

Biogen Idec, 14 Cambridge Center, Cambridge, MA 02142, USA.

Niracle LLC, New Town, Pennsylvania, USA.

出版信息

Int J Pharm. 2015 Jul 5;488(1-2):120-6. doi: 10.1016/j.ijpharm.2015.04.025. Epub 2015 Apr 14.

Abstract

The aim of this study is to develop an at-line near infrared (NIR) method for the rapid and simultaneous determination of four structurally similar active pharmaceutical ingredients (APIs) in powder blends intended for the manufacturing of tablets. Two of the four APIs in the formula are present in relatively small amounts, one at 0.95% and the other at 0.57%. Such small amounts in addition to the similarity in structures add significant complexity to the blend uniformity analysis. The NIR method is developed using spectra from six laboratory-created calibration samples augmented by a small set of spectra from a large-scale blending sample. Applying the quality by design (QbD) principles, the calibration design included concentration variations of the four APIs and a main excipient, microcrystalline cellulose. A bench-top FT-NIR instrument was used to acquire the spectra. The obtained NIR spectra were analyzed by applying principal component analysis (PCA) before calibration model development. Score patterns from the PCA were analyzed to reveal relationship between latent variables and concentration variations of the APIs. In calibration model development, both PLS-1 and PLS-2 models were created and evaluated for their effectiveness in predicting API concentrations in the blending samples. The final NIR method shows satisfactory specificity and accuracy.

摘要

本研究旨在开发一种在线近红外(NIR)方法,用于快速同时测定四种结构相似的原料药(API)在粉末混合物中的含量,这些混合物旨在用于制造片剂。配方中的四种 API 中有两种的含量相对较少,一种为 0.95%,另一种为 0.57%。如此小的含量加上结构的相似性,使得混合物均匀性分析变得非常复杂。该 NIR 方法是使用六组实验室制备的校准样品的光谱以及一组来自大规模混合样品的少量光谱来开发的。应用质量源于设计(QbD)原理,校准设计包括四种 API 和主要赋形剂微晶纤维素的浓度变化。使用台式 FT-NIR 仪器采集光谱。在建立校准模型之前,通过应用主成分分析(PCA)对获得的 NIR 光谱进行分析。分析 PCA 的得分模式,以揭示潜在变量与 API 浓度变化之间的关系。在建立校准模型时,创建并评估了 PLS-1 和 PLS-2 模型,以评估它们在预测混合样品中 API 浓度方面的有效性。最终的 NIR 方法具有令人满意的特异性和准确性。

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