Construction and Validation of Quantification Methods for Determining the Cannabidiol Content in Liquid Pharma-Grade Formulations by Means of Near-Infrared Spectroscopy and Partial Least Squares Regression.
{"title":"Construction and Validation of Quantification Methods for Determining the Cannabidiol Content in Liquid Pharma-Grade Formulations by Means of Near-Infrared Spectroscopy and Partial Least Squares Regression.","authors":"Joan Espel Grekopoulos","doi":"10.1159/000500266","DOIUrl":null,"url":null,"abstract":"<p><p>There is an increasing interest in cannabinoids as they are being proved to effectively treat the symptoms of a variety of medical conditions. Commercialization of cannabinoid-based pharmaceutical products is expected to grow in the near future, favored by the recent changes in medical regulations in many developed countries. Hence, robust and reliable analytical methods for determining the content of the active pharmaceutical ingredient will be needed, as this is one of the most relevant parameters for the decision to release the final pharmaceutical product into the market. The aim of this work was to demonstrate that near-infrared (NIR) spectroscopy fulfills the needed requirements for this purpose, as well as to provide a methodology to be applied to other cannabinoid-based products. We present two validated methods for the quantification of different liquid pharma-grade cannabidiol (CBD) formulations based on NIR spectroscopy and partial least squares regression modelling. The methods were constructed and validated with spectra belonging both to production samples and to laboratory samples specifically made for this purpose, and they fulfill European Medicines Agency and International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use guideline requirements. These methods allow determining the CBD content with results comparable to the usual method of choice while saving reagent- as well as time-related costs.</p>","PeriodicalId":18415,"journal":{"name":"Medical Cannabis and Cannabinoids","volume":"2 1","pages":"43-55"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000500266","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Cannabis and Cannabinoids","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1159/000500266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/9/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 8
Abstract
There is an increasing interest in cannabinoids as they are being proved to effectively treat the symptoms of a variety of medical conditions. Commercialization of cannabinoid-based pharmaceutical products is expected to grow in the near future, favored by the recent changes in medical regulations in many developed countries. Hence, robust and reliable analytical methods for determining the content of the active pharmaceutical ingredient will be needed, as this is one of the most relevant parameters for the decision to release the final pharmaceutical product into the market. The aim of this work was to demonstrate that near-infrared (NIR) spectroscopy fulfills the needed requirements for this purpose, as well as to provide a methodology to be applied to other cannabinoid-based products. We present two validated methods for the quantification of different liquid pharma-grade cannabidiol (CBD) formulations based on NIR spectroscopy and partial least squares regression modelling. The methods were constructed and validated with spectra belonging both to production samples and to laboratory samples specifically made for this purpose, and they fulfill European Medicines Agency and International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use guideline requirements. These methods allow determining the CBD content with results comparable to the usual method of choice while saving reagent- as well as time-related costs.