Crowley Mary Ellen, Hegarty Avril, McAuliffe Michael A P, O'Mahony Graham E, Kiernan Luke, Hayes Kevin, Crean Abina M
Synthesis and Solid State Pharmaceutical Centre, School of Pharmacy, University College Cork, Ireland.
MACSI, Department of Mathematics and Statistics, University of Limerick, Ireland.
Eur J Pharm Sci. 2017 May 1;102:103-114. doi: 10.1016/j.ejps.2017.02.024. Epub 2017 Feb 16.
The aim of this study was to highlight how variability in roller compacted ribbon quality can impact on NIR spectral measurement and to propose a simple method of data selection to remove erroneous spectra. The use of NIR spectroscopy for monitoring ribbon envelope density has been previously demonstrated, however to date there has been limited discussion as to how spectral data sets can contain erroneous outliers due to poor sample presentation to the NIR probes. In this study compacted ribbon of variable quality was produced from three separate blends of microcrystalline cellulose (MCC)/lactose/magnesium stearate at 8 Roll Force settings (2-16kN/cm). The three blends differed only in the storage conditions of MCC prior to blending and compaction. MCC sublots were stored at ambient (41% RH/20°C), low humidity (11% RH/20°C) and high humidity (75% RH/40°C) conditions prior to blending. Ribbon envelope density was measured and ribbon NIR spectral data was acquired at line using a multi-probe spectrometer (MultiEye™ NIR). Initial inspection of the at-line NIR spectral data set showed a large degree of variability which indicated that some form of data cleaning was required. The source of variability in spectral measurements was investigated by subjective visual examination and by statistical analysis. Spectral variability was noted due to the storage conditions of MCC prior to compaction, Roll Force settings and between individual ribbon samples sampled at a set Roll Force/Blend combination. Variability was also caused by ribbon presentation to probes, such as differences in the presentation of broken, curved and flat intact ribbons. Based on the subjective visual examination of data, a Visual Discard method was applied and was found to be particularly successful for blends containing MCC stored at ambient and low humidity. However the Visual Discard method of spectra cleaning is subjective and therefore a non-subjective method capable of screening for erroneous probe readings was developed. For this data set a Trimmed Mean method was applied to set a limit on how data is cleaned from the data set allowing for the removal of a faulty probe reading (25% of data) or a poor sample (33% of data). The 33% Trimmed Mean reduced the impact of spectral variation or misreads between samples or probes and was found to be as successful as the Visual Discard method at cleaning the data set prior to development of the calibration equation.
本研究的目的是强调滚压带状物质量的变异性如何影响近红外光谱测量，并提出一种简单的数据选择方法以去除错误光谱。先前已证明使用近红外光谱法监测带状物包封密度，然而，迄今为止，关于由于向近红外探头呈现的样品不佳，光谱数据集如何可能包含错误的异常值的讨论有限。在本研究中，由微晶纤维素（MCC）/乳糖/硬脂酸镁的三种不同混合物在8种滚压力设置（2-16kN/cm）下制备了质量可变的压实带状物。这三种混合物仅在混合和压实之前MCC的储存条件上有所不同。在混合之前，MCC子批分别储存在环境条件（41%相对湿度/20°C）、低湿度（11%相对湿度/20°C）和高湿度（75%相对湿度/40°C）条件下。测量带状物包封密度，并使用多探头光谱仪（MultiEye™ NIR）在线采集带状物近红外光谱数据。对在线近红外光谱数据集的初步检查显示出很大程度的变异性，这表明需要某种形式的数据清理。通过主观视觉检查和统计分析研究了光谱测量变异性的来源。注意到光谱变异性是由于压实之前MCC的储存条件、滚压力设置以及在设定的滚压力/混合物组合下采样的各个带状物样品之间的差异。变异性还由带状物向探头的呈现方式引起，例如破碎、弯曲和平整完整带状物呈现方式的差异。基于对数据的主观视觉检查，应用了视觉丢弃法，发现该方法对于含有在环境条件和低湿度下储存的MCC的混合物特别成功。然而，光谱清理的视觉丢弃法是主观的，因此开发了一种能够筛选错误探头读数的非主观方法。对于该数据集，应用了截尾均值法来设定从数据集中清理数据的限度，从而允许去除错误的探头读数（25%的数据）或不良样品（33%的数据）。33%截尾均值减少了样品或探头之间光谱变化或误读带来的影响，并且发现在建立校准方程之前清理数据集方面与视觉丢弃法同样成功。
