Department of Chemical and Biochemical Engineering, Rutgers University, United States.
Department of Mechanical and Aerospace Engineering, Rutgers University, United States.
Int J Pharm. 2016 Oct 15;512(1):96-107. doi: 10.1016/j.ijpharm.2016.08.033. Epub 2016 Aug 16.
A method for predicting dissolution profiles of directly compressed tablets for a fixed sustained release formulation manufactured in a continuous direct compaction (CDC) system is presented. The methodology enables real-time release testing (RTRt). Tablets were made at a target drug concentration of 9% Acetaminophen, containing 90% lactose and 1% Magnesium Stearate, and at a target compression force of 24kN. A model for predicting dissolution profiles was developed using a 3(4-1) fractional factorial experimental design built around this targeted condition. Four variables were included: API concentration (low, medium, high), blender speed (150rpm, 200rpm, 250rpm), feed frame speed (20rpm, 25rpm, 30rpm), compaction force (8KN, 16KN, 24KN). The tablets thus obtained were scanned at-line in transmission mode using Near IR spectroscopy. The dissolution profiles were described using two approaches, a model-independent "shape and level" method, and a model-dependent approach based on Weibull's model. Multivariate regression was built between the NIR scores as the predictor variables and the dissolution profile parameters as the response. The model successfully predicted the dissolution profiles of the individual tablets (similarity factor, f2 ∼72) manufactured at the targeted set point. This is a first ever published manuscript addressing RTRt for dissolution prediction in continuous manufacturing, a novel and state of art technique for tablet manufacturing.
介绍了一种用于预测在连续直接压缩(CDC)系统中制造的固定持续释放制剂的直接压缩片剂溶出曲线的方法。该方法实现了实时释放测试(RTRt)。以 9%对乙酰氨基酚为目标药物浓度,含有 90%乳糖和 1%硬脂酸镁的片剂,目标压缩力为 24kN。建立了一个预测溶出曲线的模型,该模型基于针对该目标条件的 3(4-1)部分析因实验设计。包括四个变量:API 浓度(低、中、高)、混合器速度(150rpm、200rpm、250rpm)、给料架速度(20rpm、25rpm、30rpm)、压缩力(8KN、16KN、24KN)。由此获得的片剂以透射模式在线使用近红外光谱进行扫描。使用两种方法描述了溶出曲线,一种是无模型的“形状和水平”方法,另一种是基于 Weibull 模型的模型依赖方法。多元回归是在 NIR 评分作为预测变量和作为响应的溶出曲线参数之间建立的。该模型成功地预测了在目标设定点制造的各个片剂的溶出曲线(相似因子,f2∼72)。这是第一篇关于连续制造中溶出预测的 RTRt 的已发表的手稿,是一种用于片剂制造的新颖的、最先进的技术。