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Abstract

REVIEW ON IMPLEMENTATION OF AQBD APPROACH TO THE HPTLC METHOD DEVELOPMENT AND VALIDATION

Ronak Vanzara* and Dr. Hina Bagada

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Abstract

Applying QbD method is very beneficial over traditional method validation. According to ICH Q8 (R2) guideline it is defined as “systematic approach to development that begins with predefine objectives, emphasizes product, understanding and process control, based on sound science and quality risk management. The QbD concept applied to analytical method validation is known as AQbD. AQbD offering a systematic and robust approach to the development of analytical procedure involving all the stages of product’s lifecycle. For developing HPTLC method, AQbD approach is based on taking one parameter variable and keeping other parameter constant for getting required response. The traditional HPTLC method development requires many experimentations with lots of trials and error which affects method performance such as accuracy, precision, robustness. Hence, to minimize time, complication & most importantly the failure of validation, AQbD is implemented for analytical method validation. There are 6 elements of AQbD they are, Analytical target profile (ATP), Critical quality attributes (CQAs), Risk assessment, Design space, Design of Experiment (DoE) in that Screening and Optimization, Method control strategy. ATP defines what the method has to measure (i.e. acceptance criteria, certain level of impurity) and to what level the measurement is required (i.e. performance level characteristics, such as precision, accuracy, range, sensitivity). CQA defined as a “Physical, chemical, biological or microbiological property or characteristics that should be within an appropriate limit, range of distribution to ensure the desired product quality”. the CQAs are mostly chromatographic plates, mobile phase, sample strength, the time require for plate development, color derivatizing agent & mode of detection. Risk assessment tools can be used to identify of rank parameters (e.g. process, equipment, input materials) with potential to have an impact on product quality based on prior knowledge & initial experimental data. Design space is the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality. Design of Experiment (DoE) is part of AQbD used for optimization of the method. Various tools are used for screening they are, factorial design, central composite design, placket-Burman design, Taguchi design and D-optimal mixture design. Various CMPs from risk assessment and screening process are selected for optimization. The most common experimental design that can be used for HPTLC method development are Box-Behnker design, Full factorial design, fractional factorial design and Doehlert design. Drug product quality ensured by risk-based control strategy for well understood product and process. AQbD in HPTLC is essential to understand different factors showing significant impact on method outcome. The HPTLC method should display robustness to facilitate use for a longer period along with very low potential of failure.

Keywords: HPTLC, QbD, DoE, AQbD, Analytical method validation, ICH Q8(R2).


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