Technoeconomic Mixed Integer Nonlinear Programming (MINLP) optimization for design of Liquid‐Liquid Extraction (LLE) cascades in continuous pharmaceutical manufacturing of atropine

Optimization of key energy and performance metrics for drug product manufacturing

During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors (Sampat et al., 2022), this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. The results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.

Continuous Extraction of 2-Chloroethyl isocyanate for 1-(2-chloroethyl)-3-cyclohexylurea Purification

This study details the development of simulation-aided design, development, and successful operation of a continuous liquid-liquid extraction platform made with 1.5 mm tubing for the extraction of 2-chloroethyl isocyanate, an important reagent in the synthesis of cancer drugs. Preliminary solvent screening was carried out with partition coefficient calculations to determine solvents of interest. Next, batch and flow extraction experiments of 2-chloroethyl isocyanate in 2-methyl tetrahydrofuran and water were conducted to estimate extraction parameters. Following parameter estimation, experimental and model values for KLa were determined in the range of 1.13×10-3 to 36.0×10-3 s-1. Simulations of the extraction of 2-chloroethyl isocyanate were found to agree with experimental data resulting in a maximum efficiency of 77% and percent extraction of 69% for the continuous platform. Finally, model selection and discrimination was implemented for design space generation with experimental and model determined KLa values to guide lab-scale operation.

Flow synthesis kinetics for lomustine, an anti-cancer active pharmaceutical ingredient

An original reaction mechanism and kinetic parameter estimation has been achieved for lomustine, an anti-cancer active pharmaceutical ingredient (API).

Design Space Identification and Visualization for Continuous Pharmaceutical Manufacturing

Progress in continuous flow chemistry over the past two decades has facilitated significant developments in the flow synthesis of a wide variety of Active Pharmaceutical Ingredients (APIs), the foundation of Continuous Pharmaceutical Manufacturing (CPM), which has gained interest for its potential to reduce material usage, energy and costs and the ability to access novel processing windows that would be otherwise hazardous if operated via traditional batch techniques. Design space investigation of manufacturing processes is a useful task in elucidating attainable regions of process performance and product quality attributes that can allow insight into process design and optimization prior to costly experimental campaigns and pilot plant studies. This study discusses recent demonstrations from the literature on design space investigation and visualization for continuous API production and highlights attainable regions of recoveries, material efficiencies, flowsheet complexity and cost components for upstream (reaction + separation) via modeling, simulation and nonlinear optimization, providing insight into optimal CPM operation.