{"title":"A Novel Method to Assay Aspirin in Pharmaceutical Formulations by Smartphone Camera-Based Image Scanning Densitometry","authors":"Rimsha Khan, Jamil Anwar","doi":"10.18596/jotcsa.1339301","DOIUrl":null,"url":null,"abstract":"Aspirin, a widely-used anti-inflammatory drug, can lead to serious consequences when overdosed. Therefore, there's a need for simple, cost-effective methods to determine its concentration and mitigate potential risks. This study aimed to develop a method for assessing aspirin in pharmaceutical preparations without the need for expensive equipment and with minimal sensitivity to ambient light. In this work, aspirin was subjected to a reaction with Fe(III), leading to the formation of violet-colored spots on filter paper and a 96-microwell plate. These colored spots were then captured using a smartphone in normal lighting conditions and analyzed on a computer. The integrated density of each spot was measured using a novel grayscale technique, and a calibration curve was created to relate integrated density to aspirin concentration. Analytical parameters and reagent concentrations were optimized for accuracy. To validate the method, three commercial aspirin samples were assayed and compared to ultraviolet-visible spectrophotometry, a reference method. The developed technique demonstrated excellent precision (coefficient of variation <0.68%) and relative errors below 5.2%. When compared to traditional color models like red-green-blue (RGB) and hue-saturation-luminosity (HSL), the grayscale model showed superior correlation (R2> 0.996), while the RGB model yielded less precise results (R2= 0.792). This study showcased the effectiveness of a cost-effective methodology for accurate aspirin quantification using a smartphone camera, even in the presence of ambient light.","PeriodicalId":17299,"journal":{"name":"Journal of the Turkish Chemical Society Section A: Chemistry","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Turkish Chemical Society Section A: Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18596/jotcsa.1339301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Aspirin, a widely-used anti-inflammatory drug, can lead to serious consequences when overdosed. Therefore, there's a need for simple, cost-effective methods to determine its concentration and mitigate potential risks. This study aimed to develop a method for assessing aspirin in pharmaceutical preparations without the need for expensive equipment and with minimal sensitivity to ambient light. In this work, aspirin was subjected to a reaction with Fe(III), leading to the formation of violet-colored spots on filter paper and a 96-microwell plate. These colored spots were then captured using a smartphone in normal lighting conditions and analyzed on a computer. The integrated density of each spot was measured using a novel grayscale technique, and a calibration curve was created to relate integrated density to aspirin concentration. Analytical parameters and reagent concentrations were optimized for accuracy. To validate the method, three commercial aspirin samples were assayed and compared to ultraviolet-visible spectrophotometry, a reference method. The developed technique demonstrated excellent precision (coefficient of variation <0.68%) and relative errors below 5.2%. When compared to traditional color models like red-green-blue (RGB) and hue-saturation-luminosity (HSL), the grayscale model showed superior correlation (R2> 0.996), while the RGB model yielded less precise results (R2= 0.792). This study showcased the effectiveness of a cost-effective methodology for accurate aspirin quantification using a smartphone camera, even in the presence of ambient light.