Statistical and Continuous Manufacturing approach by Design of Experiment (DoE) for a Robust Synthetic Process of a Sorafenib Analogue Saxena Shikha1, Bawa Sandhya2, Katare Deepshikha Pande3,* 1Amity Institute of Pharmacy, Amity University, Noida 2Department of Pharmaceutical Chemistry, SPER, Jamia Hamdard, New Delhi 3Centre for Medical Biotechnology, Amity Institute of Biotechnology, Amity University, Noida *Corresponding Author E-mail: dpkatare@amity.edu
Online published on 24 February, 2020. Abstract Graphical-Statistical Design of experiment (DoE) is a new approach to reaction chemist over the age old technique of Quality by Testing. Modern era of ‘Continuous Manufacturing’, as a newly proposed ICH guideline Q13 introduces new concept of robust reaction designing bypassing the myriad of reactions involved in traditional approach as One Variable at a Time (OVAT). Present study demonstrates the amalgamation of complete reaction process with stat-software analysis of a novel multikinase inhibitor Sorafenib's analogue using Design Expert ® Software. The Benzyl Analogue of Sorafenib is designed using Sorafenib as lead molecule. Each step of synthesis process involves the selection of solvents and bases scientifically and through Principal Component Analysis (PCA). Further, the key factors were established with low and high range as a preliminary study. The key factors like substrate molar concentration, temperature and time of reaction, were considered for DoE study wherein influence of factors and their interactions were studied over yield and quality of the product in a statistically relevant manner. For each step of reaction ‘Response Surface Methodology’ (RSM) was adopted with either Central Composite or Box-Behnken randomized matrix model design type. Synopsis for each DoE study was elaborated through analysis of variance (ANOVA) of defined model type. Data from non-linear studies have been shown through Contour plots, 3-D di-interaction plots and Coded Factor Interaction Reaction Equations. A cost effective and an unambiguous robust design space for each step of reaction was achieved with practical confirmation. The cost reduction of about 81.8% with exceptionally reduced number of experiments is obtained. Top Keywords DOE, Process Optimisation, Sorafenib, RSM. Top |