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Abstract：
The aim of this work was to develop a PAT platform consisting of four complementary instruments for the characterization of electrospun amorphous solid dispersions with meloxicam. The investigated methods, namely NIR spectroscopy, Raman spectroscopy, Colorimetry and Image analysis were tested and compared considering the ability to quantify the active pharmaceutical ingredient and to detect production errors reflected in inhomogeneous deposition of fibers. Based on individual performance the calculated RMSEP values ranged between 0.654% and 2.292%. Mid-level data fusion consisting of data compression through latent variables and application of ANN for regression purposes proved efficient, yielding an RMSEP value of 0.153%. Under these conditions the model could be validated accordingly on the full calibration range. The complementarity of the PAT tools, demonstrated from the perspective of captured variability and outlier detection ability, contributed to model performance enhancement through data fusion. To the best of the author\'s knowledge, this is the first application of data fusion in the field of PAT for efficient handling of big-analytical-data provided by high-throughput instruments.
摘要：
这项工作的目的是开发一个由四个互补仪器组成的PAT平台，用于表征具有美洛昔康的电纺无定形固体分散体。调查的方法，即近红外光谱，拉曼光谱,考虑到量化活性药物成分和检测反映在纤维不均匀沉积中的生产误差的能力,测试和比较比色法和图像分析。基于个体表现,计算的RMSEP值在0.654%和2.292%之间。中级数据融合包括通过潜在变量的数据压缩和用于回归目的的ANN应用被证明是有效的，产生0.153%的RMSEP值。在这些条件下，可以在整个校准范围内相应地验证模型。PAT工具的互补性，从捕获的变异性和异常值检测能力的角度证明，有助于通过数据融合提高模型性能。据作者所知,这是数据融合在PAT领域的首次应用，用于高效处理由高通量仪器提供的大分析数据。
