首页> 外文期刊>Journal of Pharmaceutical and Biomedical Analysis: An International Journal on All Drug-Related Topics in Pharmaceutical, Biomedical and Clinical Analysis >Application of miniaturized near-infrared spectroscopy for quality control of extemporaneous orodispersible films
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Application of miniaturized near-infrared spectroscopy for quality control of extemporaneous orodispersible films

机译:小型化近红外光谱法在省力近代薄膜质量控制中的应用

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Highlights ? Miniaturized NIR spectroscopy was applied for quality control of extemporaneous ODF. ? SVM classification gave 100% prediction accuracy for drug identification. ? A PLS regression model was developed for quantification of ondansetron drug content. ? The quantitative model was validated to be linear, accurate and precise. Abstract Extemporaneous oral preparations are routinely compounded in the pharmacy due to a lack of suitable formulations for special populations. Such small-scale pharmacy preparations also present an avenue for individualized pharmacotherapy. Orodispersible films (ODF) have increasingly been evaluated as a suitable dosage form for extemporaneous oral preparations. Nevertheless, as with all other extemporaneous preparations, safety and quality remain a concern. Although the United States Pharmacopeia (USP) recommends analytical testing of compounded preparations for quality assurance, pharmaceutical assays are typically not routinely performed for such non-sterile pharmacy preparations, due to the complexity and high cost of conventional assay methods such as high performance liquid chromatography (HPLC). Spectroscopic methods including Raman, infrared and near-infrared spectroscopy have been successfully applied as quality control tools in the industry. The state-of-art benchtop spectrometers used in those studies have the advantage of superior resolution and performance, but are not suitable for use in a small-scale pharmacy setting. In this study, we investigated the application of a miniaturized near infrared (NIR) spectrometer as a quality control tool for identification and quantification of drug content in extemporaneous ODFs. Miniaturized near infrared (NIR) spectroscopy is suitable for small-scale pharmacy applications in view of its small size, portability, simple user interface, rapid measurement and real-time prediction results. Nevertheless, the challenge with miniaturized NIR spectroscopy is its lower resolution compared to state-of-art benchtop equipment. We have successfully developed NIR spectroscopy calibration models for identification of ODFs containing five different drugs, and quantification of drug content in ODFs containing 2–10mg ondansetron (OND). The qualitative model for drug identification produced 100% prediction accuracy. The quantitative model to predict OND drug content in ODFs was divided into two calibrations for improved accuracy: Calibration I and II covered the 2–4mg and 4–10mg ranges respectively. Validation was performed for method accuracy, linearity and precision. In conclusion, this study demonstrates the feasibility of miniaturized NIR spectroscopy as a quality control tool for small-scale, pharmacy preparations. Due to its non-destructive nature, every dosage unit can be tested thus affording positive impact on patient safety.
机译:强调 ?施用小型化的NIR光谱,用于省略ODF的质量控制。还是SVM分类给药预测准确性100%用于药物鉴定。还是开发了PLS回归模型,用于定量ondansetron药物含量。还是定量模型被验证为线性,准确和精确。由于缺乏适当的特殊种群制剂,摘要在药房中常规地复合了脱孕口服制剂。这种小规模的药房制剂还为个性化药物疗法提供了一条途径。 Orodispersible薄膜(ODF)越来越多地评估为适当的剂型,用于脱颞口制制剂。尽管如此,与所有其他省势的备用制剂一样,安全和质量仍然是一个问题。虽然美国药典(USP)建议对质量保证的复合制剂的分析测试,由于常规测定方法如高效液相色谱如高效测定方法的复杂性和高成本,通常不常规地对这种非无菌药物制剂进行常规进行药物测定。 (HPLC)。包括拉曼,红外和近红外光谱的光谱方法已成功应用于该行业的质量控制工具。这些研究中使用的最先进的台式光谱仪具有卓越的分辨率和性能的优点,但不适用于小规模的药房设置。在这项研究中,我们研究了将小型化的近红外(NIR)光谱仪作为质量控制工具的应用,以识别和定量即时ODF中的药物含量。近红外线(NIR)光谱分子化适用于小规模的药房应用,考虑到其小尺寸,便携性,简单的用户界面,快速测量和实时预测结果。然而,与艺术技术的台式设备相比,具有小型化NIR光谱的挑战是其较低分辨率。我们已成功开发了NIR光谱校准模型,用于鉴定含有五种不同药物的ODF,以及含有2-10mg Ondansetron(OND)的ODF中药物含量的定量。药物识别的定性模型产生了100%的预测精度。预测ODF中的对ODF药物含量的定量模型分为两种校准,以提高精度:校准I和II分别覆盖2-4mg和4-10mg的范围。对方法精度,线性度和精度进行验证。总之,本研究证明了小型化NIR光谱的可行性作为小规模,药房制剂的质量控制工具。由于其无损性质,可以测试每种剂量单位,从而为患者安全产生积极影响。

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