In Silico Process Optimization and Quality by Design with Business and Environmental Sustainability Considerations

Abstract

In designing pharmaceutical manufacturing alongside the principles of quality by design (QbD) and process analytical technology (PAT), unit operations process development and corporate decision-making processes such as business profits and environmental impact assessments are often undertaken separately. This paper presents a strategic three-tier framework linking the process, operations, and business/enterprise levels for process development and improvement alongside an in silico optimization approach. At the process level, first principles reaction kinetics and semi-batch process parameters are used for process simulations. Data exchanges between the process and operations levels were achieved through the OLE for process control (OPC) protocol with real-time chemometrics modeling of in situ spectroscopic measurements. At the operations level, multivariate statistical models were utilized for continuous process improvement in conjunction with profit maximization and environmental waste considerations at the business/enterprise level. In silico optimization of consecutive semi-batch epoxidation reactions was performed using MATLAB/Simulink. Pareto-optimal operating parameters within the design space that considers product quality and process efficiency, profitability, and environmental impact were arrived through systematic simulations conducted using design of experiments (DoE) and partial least squares (PLS) modeling. A simple three-tier methodological framework was proposed to bridge process development, profitability, and environmental assessment. Through such a framework, the links between process, operations, and business/enterprise levels toward sustainable development and product value chain become more transparent. The Pareto-optimal solutions generated demonstrate how process development choices could impact business/enterprise decision-making.