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Determination of Ribavirin and Moisture in Pharmaceuticals by Near-Infrared Spectroscopy

机译:近红外光谱法测定药物中的利巴韦林和水分

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摘要

A robust near-infrared (NIR) method is reported for the determination of moisture and ribavirin in effervescent granules. Several key factors were used for model construction to obtain robust and universal models, including the number of batches, operators, days, temperature, and data acquisition. The moisture model covered seven representative moisture concentrations: 0.5, 1.0, 1.5, 2.0, 4.0, 6.0, and 8.0%. In this model, the ribavirin concentration varied from 80 to 120%. The NIR models were developed using algorithms for partial least squares and synergy interval partial least squares regression. The results of the algorithms were all suitable based on traditional evaluation standards. However, the accuracy of the synergy interval partial least squares regression algorithm for the moisture and ribavirin concentrations yielded particularly satisfactory results. The model was validated and its reliability evaluated with respect to the measurement of new pilot batches containing 90 and 110% of the active concentration and of individual industry batches. These findings showed that the NIR method is robust rapid, and nondestructive for the determination of moisture and ribavirin in effervescent granules.
机译:据报道,一种健壮的近红外(NIR)方法可用于测定泡腾颗粒中的水分和利巴韦林。使用几个关键因素进行模型构建以获得鲁棒且通用的模型,包括批数,操作员,天数,温度和数据采集。水分模型涵盖了七个代表性水分浓度:0.5%,1.0%,1.5%,2.0%,4.0%,6.0%和8.0%。在该模型中,利巴韦林浓度在80%至120%之间变化。使用部分最小二乘和协同区间部分最小二乘回归算法开发了NIR模型。基于传统评估标准,算法结果均合适。但是,针对水分和利巴韦林浓度的协同区间偏最小二乘回归算法的准确性产生了特别令人满意的结果。对于包含90%和110%活性浓度的新中试批次以及各个行业批次的测量,该模型经过了验证并评估了其可靠性。这些发现表明,NIR方法快速可靠,对泡腾颗粒中水分和利巴韦林的测定无损。

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