Division of Product Quality Research, Office of Pharmaceutical Science, Food and Drug Administration, Silver Spring, Maryland, 20993-0002.
J Pharm Sci. 2014 Feb;103(2):539-44. doi: 10.1002/jps.23812. Epub 2013 Dec 10.
There is an urgent need for the analysis of melamine in the global pharmaceutical supply chain to detect economically motivated adulteration or unintentional contamination using a simple, nondestructive analytical technique that confirms the extent of adulteration in a shorter time period. In this work, different analytical techniques (thermal analysis, X-ray diffraction, Fourier transform infrared (FT-IR), FT-Raman, and near-infrared (NIR) spectroscopy) were evaluated for their ability to detect a range of melamine levels in gelatin. While FT-IR and FT-Raman provided qualitative assessment of melamine contamination or adulteration, powder X-ray diffraction and NIR were able to detect and quantify the presence of melamine at levels as low as 1.0% w/w. Multivariate analysis of the NIR data yielded the most accurate model when three principal components were used. Data were pretreated using standard normal variate transformation to remove multiplicative interferences of scatter and particle size. The model had a root-mean-square error of calibration of 2.4 (R(2) = 0.99) and root-mean square error of prediction of 2.5 (R(2) = 0.96). The value of the paired t test for actual and predicted samples (1%-50% w/w) was 0.448 (p < 0.05), further indicating the robustness of the model.
全球医药供应链中急需采用一种简单、无损的分析技术来分析三聚氰胺,以检测出人为的掺假或无意的污染,同时确认在更短的时间内掺假的程度。在这项工作中,评估了不同的分析技术(热分析、X 射线衍射、傅里叶变换红外(FT-IR)、FT-Raman 和近红外(NIR)光谱)检测明胶中不同三聚氰胺含量的能力。FT-IR 和 FT-Raman 提供了三聚氰胺污染或掺假的定性评估,而粉末 X 射线衍射和 NIR 则能够检测和定量存在的三聚氰胺,检出限低至 1.0%w/w。当使用三个主成分进行多元分析时,NIR 数据的分析得到了最准确的模型。对 NIR 数据进行了标准正态变量变换预处理,以消除散射和粒径的乘法干扰。该模型的校准均方根误差为 2.4(R²=0.99),预测均方根误差为 2.5(R²=0.96)。实际和预测样品(1%-50%w/w)的配对 t 检验值为 0.448(p<0.05),进一步表明了模型的稳健性。