(337ck) Controlled Protein Capture Via Continuous Precipitation for Monoclonal Antibody Manufacturing

The biopharmaceutical industry has witnessed a growing interest in continuous processing over traditional batch processing for bio-separations due to the numerous advantages offered by the former. Continuous processing has the potential to deliver significant improvements in productivity, efficiency, and product quality while also reducing overall costs. Protein A chromatography is currently used for the initial capture step in the production of monoclonal antibodies for the treatment of cancers and autoimmune diseases. This step not only accounts for the high cost of operation and throughput bottlenecks in the downstream process, it is also difficult to adapt to continuous processing. This makes non-chromatographic methods like precipitation more appealing. In this work, we developed a more systematic approach for the design and control of precipitation processes for the initial capture of high-value therapeutic proteins as part of an integrated continuous downstream process using human serum Immunoglobulin G (IgG) and commercial monoclonal antibodies (mAbs). The precipitating agents used were PEG and ZnCl2. The precipitate morphology was analyzed and measured with the BlazeMetrics optical probe which provides multiple real-time derived statistics using chord-length distributions. The study also included a first-principles based precipitation kinetic model to predict the dynamic real-time precipitate populations. The precipitation module and BlazeMetrics measurement was followed by dewatering hollow-fiber membrane filters. For reduced fouling operations, the sustainable flux was estimated. Further, predictive sustainable flux models were built linking with the process operating conditions and BlazeMetrics statistics.

For Pharma 4.0 purposes, process automation and control play critical roles in the transformation from batch to continuous processing. Hence, using system identification techniques we developed data-driven models to design a Proportional-Integral controller with sample time of 1 minute. Two BlazeMetrics statistics were selected based on validation fits as the desired controlled variable while the PEG flowrate was selected as the manipulated variable.

Furthermore, to bring a biological-based therapeutic to market quickly it is important to use Smart Manufacturing (Industry 4.0) techniques to integrate data, model predictions, and closed-loop real-time automation to move from bench to pilot-plant to full scale manufacturing in a short period of

time. This was enabled for the bench scale system by the Smart Manufacturing Innovation Platform developed by the Clean Energy Smart Manufacturing Innovation Institute. The integrated operations, including hardware, software, algorithms, and cloud platforms demonstrate a first-of-kind continuous downstream technology using precipitation and filtration for next generation Pharma 4.0 processing.

Keywords: Pharma 4.0, Smart manufacturing (SM), Monoclonal Antibodies (mAbs), Process Control, Downstream Process, Precipitation, Simulation, Modeling.