Continuous Pharmaceutical Manufacturing (CPM) has recently emerged as a promising alternative to current batch production methods, which require significant expenditures in order to ensure product quality and process reliability. Advances in new continuous synthesis routes, demonstrations of full end-to end continuous drug production and comparative technoecononiic analyses of potential cost advantages have all contributed to the advent of CPM and the strong interest of academic, corporate and regulatory beneficiaries. Continuous flow chemistry has been demonstrated for a variety of Active Pharmaceutical Ingredients (APIs), and there have been several landmark studies demonstrating practical CPM by illustrating the full design from raw materials to final product formulation. Fully continuous separations are critical to maximizing the CPM potential, but they arc frequently not eludicated. This paper presents the formulation and solution of a nonlinear optimization problem for the CPM of ibuprofen. Adapting published continuous synthesis routes and experimental data, and considering reactor design, explicit mass transfer, thermodynamics via UNIFAC-estimated API solubilities, and cost estimation, optimal total costs have been determined for two solvents (toluene and n-hexane) at three different temperatures (25, 45 and 65 degrees C). The minimum total cost (728.5 X 10(3) GBP) is achieved for n-hexane use at 65 degrees C, while the minimum total cost for toluene is only marginally higher (761.4 x 10(3) GBP, also at 65 degrees C). With respect to the E-factor, a measure of design sustainability, the cases are comparable: the best E-factor (39.9) is obtained for the n-hexane at 65 degrees C, and the best E-factor for toluene is again close at 42.1 (for 65 degrees C). Given that the differences are small, the use of toluene at 65 degrees C is the preferable option, as this solvent is more environmentally benign than n-hexane and offers comparable performance.

• University of Edinburgh

• API
• Modeling

1. API
2. continuous separation
3. E-factor
4. ibuprofen
5. modeling
6. optimal total cost
7. Research Article