(541c) Systematic Decomposition & Evaluation of a Process Design Space for Monoclonal Antibody (mAb) Manufacturing

Three of the major trials within drug development and commercialization are phase 1 to 3 clinical trials. As these trials proceed product-process understanding increases and these are utilized via a feedback loop to the different development areas. The complex feedback loop consists of knowledge from input and output material properties (product related) and unit operations performance (process related). Monoclonal antibodies (mAbs) are of importance because they are proteins that are purposely engineered to treat various severe diseases for example cancer or hemophilia (Wolf Pérez et al., 2019). A typical pharmaceutical process for a specific active pharmaceutical ingredient (API) is batch-based because batch processes provide the flexibility of quality control at different intermediate steps and batch tracing inside the process boundaries and outside, that is, the product supply chain. Of interest, whether a continuous or batch process, is the evaluation of technologies that have a positive impact on process performance. Therefore, it is of interest to systematically evaluate relevant technologies for improving process performance and sustainability beyond high level “what-if analyses” to provide the foundation for advanced process understanding, design and optimization (Yang et al., 2020).

The mAb platform process to be investigated is pre-selected to be a batch process and therefore, any pre-selected flowsheet model for representation of the process is dynamic. Therefore, in analyzing upscale data for the platform process (lab and/or pilot), a systematic approach where multiple ideas associated with evaluating new technologies with respect to mass throughput and time execution is of importance. For the platform process, based on the large number of alternative placements of new technologies (integer decisions) and estimation of the input/outputs (continuous decisions) a systematic approach consisting of two layers of decisions is proposed. The decomposition layer addresses the integer decision problem, that is, placement of the new technology and the evaluation layer; having fixed the placement; addresses the continuous decision, that is, the expected gain in process performance, capacity and sustainability. This is performed using a simulation-based approach of material flow analysis with embedded non-linear process behavior.

The objective of this presentation is to present the systematic method for mAb process design space generation and screening. First, the problem and method will be presented. Second, the concept of discrete-event simulation will be introduced and how this can be used within the method for decomposition and evaluation of the design space. Finally, the method will be exemplified through an example of a promising technology for mAb manufacturing.

References

Wolf Pérez A. M., Sormanni P., Andersen J. S., Sakhnini L. I., Rodriguez-Leon I., Bjelke J. R., Gajhede A. J., De Maria L., Otzen D. E., Vendruscolo M. and Lorenzen N. 2014. In vitro and in silico assessment of the developability of a designed monoclonal antibody library. mAbs, 11(2), 388–400.

Yang, O., Qadan, M. & Ierapetritou, M. Economic Analysis of Batch and Continuous Biopharmaceutical Antibody Production: a Review. 2019. Journal of pharmaceutical innovation, 15, 182–200.