S. Chopra, Prashant K. Chaturvedi, Kalyani H. Joshi, S. Tauro, Pintu B. Prajapati
{"title":"Pitfalls and Opportunities in the Execution of Quality by Design in Analytical\nSciences","authors":"S. Chopra, Prashant K. Chaturvedi, Kalyani H. Joshi, S. Tauro, Pintu B. Prajapati","doi":"10.2174/1573412919666230517141015","DOIUrl":null,"url":null,"abstract":"\n\nQuality by Design (QbD) is a systematic approach integrated with quality risk management.\nIt uses different design approaches followed by statistical analysis to yield a quality\nproduct. Now, the pharmaceutical industries are intrested in the application of QbD principles to\nanalytical methods and term it as Analytical QbD (AQbD), which does not essentially mean less\nanalytical testing; to a particular extent, it means the right analysis at the right time, supported by\nscience and risk evaluation which ensures that the analytical method can be improved throughout\nits life cycle. However, for that, the analyst must have sound knowledge of Analytical Target Profile\n(ATP), method performance characteristics, risk assessment, choice of Design of Experiment\n(DoE), optimization of Method Operable Design Region (MODR). Some papers have cited the\nimportance, regulatory flexibility, theoretical aspects, and statistical analysis of AQbD, but only a\nfew discuss the core issue of gradual implementation of QbD in analytical sciences. For seamless\ntransition, researchers need clarification on AQbD terminologies, acceptable methods, criteria to\nembrace critical quality attributes (CQAs), and standards to judge the adequacy of controls. This\npaper summarizes the challenges and solutions for the implementation of AQbD.\n","PeriodicalId":0,"journal":{"name":"","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/1573412919666230517141015","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
Quality by Design (QbD) is a systematic approach integrated with quality risk management.
It uses different design approaches followed by statistical analysis to yield a quality
product. Now, the pharmaceutical industries are intrested in the application of QbD principles to
analytical methods and term it as Analytical QbD (AQbD), which does not essentially mean less
analytical testing; to a particular extent, it means the right analysis at the right time, supported by
science and risk evaluation which ensures that the analytical method can be improved throughout
its life cycle. However, for that, the analyst must have sound knowledge of Analytical Target Profile
(ATP), method performance characteristics, risk assessment, choice of Design of Experiment
(DoE), optimization of Method Operable Design Region (MODR). Some papers have cited the
importance, regulatory flexibility, theoretical aspects, and statistical analysis of AQbD, but only a
few discuss the core issue of gradual implementation of QbD in analytical sciences. For seamless
transition, researchers need clarification on AQbD terminologies, acceptable methods, criteria to
embrace critical quality attributes (CQAs), and standards to judge the adequacy of controls. This
paper summarizes the challenges and solutions for the implementation of AQbD.