Suppr超能文献

近红外光谱与化学计量学联用用于药物制剂中地塞米松的定量分析

Coupling of NIR Spectroscopy and Chemometrics for the Quantification of Dexamethasone in Pharmaceutical Formulations.

作者信息

Biancolillo Alessandra, Scappaticci Claudia, Foschi Martina, Rossini Claudia, Marini Federico

机构信息

Department of Physical and Chemical Sciences, University of L'Aquila, Via Vetoio snc, Coppito, 67100 L'Aquila, Italy.

Department of Chemistry, University of Rome "La Sapienza", Piazzale Aldo Moro 5, 00185 Rome, Italy.

出版信息

Pharmaceuticals (Basel). 2023 Feb 16;16(2):309. doi: 10.3390/ph16020309.

Abstract

Counterfeit or substandard drugs are pharmaceutical formulations in which the active pharmaceutical ingredients (APIs) have been replaced or ingredients do not comply with the drug leaflet. With the outbreak of the COVID-19 pandemic, fraud associated with the preparation of substandard or counterfeit drugs is expected to grow, undermining health systems already weakened by the state of emergency. Analytical chemistry plays a key role in tackling this problem, and in implementing strategies that permit the recognition of uncompliant drugs. In light of this, the present work represents a feasibility study for the development of a NIR-based tool for the quantification of dexamethasone in mixtures of excipients (starch and lactose). Two different regression strategies were tested. The first, based on the coupling of NIR spectra and Partial Least Squares (PLS) provided good results (root mean square error in prediction (RMSEP) of 720 mg/kg), but the most accurate was the second, a strategy exploiting sequential preprocessing through orthogonalization (SPORT), which led (on the external set of mixtures) to an R of 0.9044, and an RMSEP of 450 mg/kg. Eventually, Variable Importance in Projection (VIP) was applied to interpret the obtained results and determine which spectral regions contribute most to the SPORT model.

摘要

假冒或不合格药品是指其中活性药物成分(API)已被替换或成分不符合药品说明书的药物制剂。随着新冠疫情的爆发,与制备不合格或假冒药品相关的欺诈行为预计会增加,这会损害已因紧急状态而削弱的卫生系统。分析化学在解决这一问题以及实施能够识别不合格药品的策略方面发挥着关键作用。有鉴于此,本研究是关于开发一种基于近红外(NIR)的工具用于定量辅料(淀粉和乳糖)混合物中地塞米松的可行性研究。测试了两种不同的回归策略。第一种基于近红外光谱与偏最小二乘法(PLS)的结合,取得了较好的结果(预测均方根误差(RMSEP)为720 mg/kg),但最准确的是第二种,即通过正交化进行顺序预处理的策略(SPORT),该策略(在混合物外部集上)得到的R值为0.9044,RMSEP为450 mg/kg。最后,应用投影变量重要性(VIP)来解释所得结果,并确定哪些光谱区域对SPORT模型贡献最大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b336/9961082/a23858e40ca3/pharmaceuticals-16-00309-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验