Litcius/Paper detail

A Review on Quality by Design Approach in Analytical Methods

Vinayak A. Katekar, Dipali Sangule, Om Bhurbhure, Priyanka Ingle, Shivprasad Dhage, Krushna Jadhav

2022Journal of Drug Delivery and Therapeutics16 citationsDOIOpen Access PDF

Abstract

Quality by Design (QbD) is a systematic approach to development that begins with predefined objectives for a product, process understanding, and process control based on knowledge and quality risk management. All conventional methods may fail to the intended purpose during method development and validation. In a QbD approach, the impact and interactions between critical method variables are understood using a Design of Experiments (DOE) approach, which gives multivariate analysis and modeling leading to the consistent quality of drug products. QbD tools like risk assessment and design of experiments, enable better quality to be incorporated into the analytical method and facilitate prior understanding and identification of variables affecting method performance. The main objective of the present review article is to describe different steps involved in method development by the QbD approach for analytical method development. The QbD Approach for method development comprises various steps that include defining method intent, performing experimental design, evaluating experimental results, selecting proper method conditions, and performing risk assessment with changing analytical parameters and conditions for evaluation. The purpose of analytical QbD is to attain quality in measurement. Keywords: Quality by Design (QbD), Design of Experiments (DOE), Critical attributes

Topics & Concepts

Quality by DesignComputer scienceQuality (philosophy)Critical quality attributesDesign of experimentsProcess (computing)Risk analysis (engineering)Identification (biology)Reliability engineeringNew product developmentManagement scienceEngineeringMathematicsMarketingMedicineEpistemologyOperating systemBusinessPhilosophyStatisticsBotanyBiologyComputational Drug Discovery Methods