Gupta Nirzari, Rodriguez Jason D, Yilmaz Huzeyfe
Division of Complex Drug Analysis, Office of Testing and Research, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, St Louis, MO, USA.
Commun Chem. 2021 Sep 2;4(1):126. doi: 10.1038/s42004-021-00563-6.
The COVID-19 pandemic created an increased demand for hygiene supplies such as hand sanitizers. In response, a large number of new domestic or imported hand sanitizer products entered the US market. Some of these products were later found to be out of specification. Here, to quickly assess the quality of the hand sanitizer products, a quantitative, through-container screening method was developed for rapid and non-destructive screening. Using spatially offset Raman spectroscopy (SORS) and support vector regression (SVR), active ingredients (e.g., type of alcohol) of 173 commercial and in-house products were identified and quantified regardless of the container material or opacity. Alcohol content in hand sanitizer formulations were predicted with high accuracy [Formula: see text] using SVR and [Formula: see text] of the substandard test samples were identified. In sum, a SORS-SVR method was developed and used for testing medical countermeasures used against COVID-19, demonstrating a potential for high-volume testing during public health threats.
新冠疫情使得对手部消毒剂等卫生用品的需求增加。作为回应,大量新的国产或进口手部消毒剂产品进入美国市场。后来发现其中一些产品不符合规格。在此,为了快速评估手部消毒剂产品的质量,开发了一种定量的、透过容器的筛查方法,用于快速无损筛查。使用空间偏移拉曼光谱(SORS)和支持向量回归(SVR),无论容器材料或不透明度如何,均可识别和定量173种商业产品和内部产品中的活性成分(如酒精类型)。使用SVR以高精度预测手部消毒剂配方中的酒精含量[公式:见原文],并识别出[公式:见原文]的不合格测试样品。总之,开发了一种SORS-SVR方法并用于测试针对新冠疫情的医疗对策,证明了在公共卫生威胁期间进行大批量测试的潜力。