NSF (CBET-1818906) and the Cottrell Foundation
Vaccine manufacturing strategies that lower capital and production costs could improve vaccine access by reducing the cost per dose and encouraging localized manufacturing. Continuous processing is increasingly utilized to drive lower costs in biological manufacturing by requiring fewer capital and operating resources. Aqueous two-phase systems (ATPS) are a liquid-liquid extraction technique that enables continuous processing for viral vectors. To date, no economic comparison between viral vector purifications using traditional methods and ATPS has been published. In this work, economic simulations of traditional chromatography-based virus manufacturing were compared to simulations of ATPS-based virus manufacturing for the same product output in both batch and continuous modes. First, the modeling strategy was validated by re-creating a viral subunit manufacturing economic simulation. Then, ATPS capital and operating costs were compared to that of a traditional chromatography purification at multiple scales of production. At all scales, ATPS purification required less than 10% of the capital expenditure compared to traditional chromatography-based purification. The production cost differences increased as manufacturing scale increased and were mainly attributed to chromatography resins required for the traditional method and absent from ATPS. At 11 kg per year production, the largest scale explored, the ATPS process cost 50% less than purification with chromatography per kg of viral product created. Based on these economic models, batch and continuous ATPS were similar in capital and production costs. These simulations show the significant reduction in manufacturing costs that ATPS-based purification could deliver to the vaccine industry.
Nold, N.M., Pearson, E., and Heldt, C. L. (2023). Intelligen SuperPro Designer Files for Economic Simulation of Batch and Continuous Aqueous Two-Phase Purification for Viral Products. Retrieved from: https://digitalcommons.mtu.edu/all-datasets/43