Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariate chemometric analysis.
Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariate chemometric analysis.
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DOI：
10.1016/j.talanta.2011.09.040
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发表时间：
2011-12-15
期刊：
影响因子：
6.1
通讯作者：
Kumar, G. Manoj
中科院分区：
文献类型：
--
作者：
Myakalwar, Ashwin Kumar;Sreedhar, S.;Barman, Ishan;Dingari, Narahara Chari;Rao, S. Venugopal;Kiran, P. Prem;Tewari, Surya P.;Kumar, G. Manoj
我们报告的有效性，激光诱导击穿光谱（LIBS）在探测药物片剂的内容，并探讨其可行性，为常规分类。该方法在其精细的化学特异性和远程和现场表征的适用性显著提高质量控制和保证过程的速度和准确性的应用中特别有益。我们的实验表明，除了主要归因于活性药物成分的碳、氢、氮和氧的存在外，所有片剂中还存在特定的无机原子。使用氧氮组成值通过比率法进行分类的初始尝试产生了具有最小相对标准偏差的最佳值（在746.83 nm处），但仍然未能提供可接受的分类。为了克服检测过程中的这一瓶颈，两种化学计量学算法，即主成分分析（PCA）和类类比软独立建模（SIMCA），被实施来利用LIBS数据的多变量性质，证明LIBS具有区分和区分药物片剂的潜力。我们报告优秀的前瞻性分类精度使用监督分类通过SIMCA算法，展示其在过程分析技术的未来应用的潜力，特别是在制药行业的快速在线过程控制监控应用。
We report the effectiveness of laser-induced breakdown spectroscopy (LIBS) in probing the content of pharmaceutical tablets and also investigate its feasibility for routine classification. This method is particularly beneficial in applications where its exquisite chemical specificity and suitability for remote and on site characterization significantly improves the speed and accuracy of quality control and assurance process. Our experiments reveal that in addition to the presence of carbon, hydrogen, nitrogen and oxygen, which can be primarily attributed to the active pharmaceutical ingredients, specific inorganic atoms were also present in all the tablets. Initial attempts at classification by a ratiometric approach using oxygen to nitrogen compositional values yielded an optimal value (at 746.83 nm) with the least relative standard deviation but nevertheless failed to provide an acceptable classification. To overcome this bottleneck in the detection process, two chemometric algorithms, i.e. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA), were implemented to exploit the multivariate nature of the LIBS data demonstrating that LIBS has the potential to differentiate and discriminate among pharmaceutical tablets. We report excellent prospective classification accuracy using supervised classification via the SIMCA algorithm, demonstrating its potential for future applications in process analytical technology, especially for fast on-line process control monitoring applications in the pharmaceutical industry.
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影响因子：
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作者：
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