(697c) Applications of Model-Based Quality by Design for Reaction Engineering
AIChE Annual Meeting
Thursday, November 11, 2010 - 3:55pm to 4:15pm
Chemical process development implementing Quality by Design (QbD) methodology requires a comprehensive risk assessment, understanding of process parameter multivariate interactions, establishing a potential design space, and ultimately the implementation of a robust control strategy to ensure quality.
In this case study, a multifactor experimental design protocol was employed utilizing automated reactor blocks with robotic powder dispensing, liquid handling, and sampling capabilities to elucidate the effect of reaction parameters on reaction rate and reaction selectivity. The Design of Experiments (DoE) output was used to generate empirical reaction kinetics models for the desired and undesired reaction pathway which were subsequently used to perform quantitative recursive risk assessment and define acceptable ranges for operational flexibility and a potential design space. A normal operating range (NOR) was established by refining reaction parameters which provided a predicted response within tolerance levels while affording adequate practical parameter flexibility. A design plan demonstrating variability within the normal operating range was adopted at pilot scale to demonstrate process scale independence, process robustness and adequate process control.
We will present an expansion of this procedure to a series of synthetic steps demonstrating the utility of this approach to predict and control reaction parameters on scale.