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双层片剂的非破坏性近红外光谱法预测溶出度。

Prediction of dissolution profiles by non-destructive NIR spectroscopy in bilayer tablets.

机构信息

Department of Chemical & Biochemical Engineering, Rutgers University, 98 Brett Road, Piscataway NJ-08854, USA.

Pharmaceutical Research Center, Handok Inc., 749, Dongil-ro, Jungnang-gu, Seoul 02108, Republic of Korea.

出版信息

Int J Pharm. 2019 Jun 30;565:419-436. doi: 10.1016/j.ijpharm.2019.05.022. Epub 2019 May 11.

Abstract

This study describes how near infrared (NIR) spectroscopy can be used to predict the dissolution of bilayer tablets as a non-destructive approach. Tablets in this study consist of two active pharmaceutical ingredients (APIs) physically separated in layers and manufactured under three levels of hardness. NIR spectra were individually acquired for both layers in diffuse reflectance mode. Reference dissolution profile values were obtained using dissolution apparatus & HPLC. A multivariate partial least squares (PLS) calibration model was developed for each API relating its dissolution profile to spectral data. This calibration model was used to predict dissolution profiles of an independent test set and results of the prediction were compared using model free approaches i.e. dissimilarity (f) & similarity (f) factors to assure similarity in dissolution performance.

摘要

本研究描述了近红外(NIR)光谱如何可用于预测双层片剂的溶出度作为一种非破坏性方法。本研究中的片剂由两种活性药物成分(API)物理分层组成,并在三个硬度级别下制造。NIR 光谱以漫反射模式分别采集两个层的光谱。参考溶出度曲线值使用溶出度仪和 HPLC 获得。为每个 API 建立了一个多元偏最小二乘(PLS)校准模型,将其溶出度曲线与光谱数据相关联。该校准模型用于预测独立测试集的溶出度曲线,并使用无模型方法(即不相似性(f)和相似性(f)因子)比较预测结果,以确保溶出性能相似。

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