Design of experiments as per QbD approach is systematic statistical technique for planning & execution of experiments in terms of screening, advanced screening & optimization. Also, to draw meaningful inferences from the data along with predefined objective. [4,10] Quality of pharmaceutical product is affected by variety of factors to overcome from this problem with the appropriate linkage of critical material attributes and critical process parameters to critical quality attributes is must. DoE examines how the input factors (CMA’s/ CPP’s) affect on an output (Responses/CQA’s) of the pharmaceutical product at a same time. This paper illustrates broad theoretical as well as practical view of screening, advanced screening & optimization designs. As well as to provide an overview and workflow to DoE and tasks to be executed in developmental activities for drug product formulation. In addition to the statistical concepts Analysis of variance (ANOVA), regression analysis, parato chart, residual diagnosis, p-value, curvature, lack-of-fit, coefficient of determination (R2), design space and multiple response prediction.
Cite this article:
Yogita M. Kolekar. Understanding of DoE and its advantages in Pharmaceutical development as per QbD Approach. Asian J. Pharm. Tech. 2019; 9 (4):271-275. doi: 10.5958/2231-5713.2019.00045.X
Yogita M. Kolekar. Understanding of DoE and its advantages in Pharmaceutical development as per QbD Approach. Asian J. Pharm. Tech. 2019; 9 (4):271-275. doi: 10.5958/2231-5713.2019.00045.X Available on: https://ajptonline.com/AbstractView.aspx?PID=2019-9-4-7