Model‐based design and control of a small‐scale integrated continuous end‐to‐end mAb platform

Abstract

A continuous integrated bioprocess available from the earliest stages of process development allows for an easier, more efficient and faster development and characterization of an integrated process as well as production of small-scale drug candidates. The process presented in this article is a proof-of-concept of a continuous end-to-end monoclonal antibody production platform at a very small scale based on a 200 ml alternating tangential flow filtration perfusion bioreactor, integrated with the purification process with a model-based design and control. The downstream process, consisting of a periodic twin-column protein A capture, a virus inactivation, a CEX column and an AEX column, was compactly implemented in a single chromatography system, with a purification time of less than 4 hr. Monoclonal antibodies were produced for 17 days in a high cell density perfusion culture of CHO cells with titers up to 1.0 mg/ml. A digital twin of the downstream process was created by modelling all the chromatography steps. These models were used for real-time decision making by the implementation of control strategies to automatize and optimize the operation of the process. A consistent glycosylation pattern of the purified product was ensured by the steady state operation of the process. Regarding the removal of impurities, at least a 4-log reduction in the HCP levels was achieved. The recovery yield was up to 60%, and a maximum productivity of 0.8 mg/ml/day of purified product was obtained.

Bioprocess Control: Current Progress and Future Perspectives

“…The upstream process included bioreactor integrated with ATF and downstream process included protein A capture, viral inactivation, cation and anion exchange chromatography integrated together. The proposed control strategy was capable of automation of the process for optimal operation [105,106].…”

“…As an example, supervisory control and data acquisition (SCADA) platform is implemented for an end-to-end integrated process wherein the system integrates and analyses different unit operations and collects and stores data to enable monitoring and control [143]. Additionally, the concept of digital twin for enabling control is shown for small scale end-to-end monoclonal antibody production platform [105]. However, full potential of automation in end-to-end bio-manufacturing process at industrial scale is yet to be realized.…”

Oncolytic virus purification with periodic counter‐current chromatography

“…Efforts to reduce the overall costs of the downstream chromatographic steps, replacing batch with continuous processing mode, have been initiated with the purification of monoclonals (Feidl et al, 2020; Gomis‐Fons et al, 2020; Müller‐Späth et al, 2008). More recently, examples of (semi‐) continuous multicolumn purification of exosomes and viruses for vaccines and gene therapy applications have been reported, making use of size‐exclusion matrices (Kröber et al, 2013; Moleirinho et al, 2019; Nestola, Silva, et al, 2014, 2015; Silva et al, 2015) or bind and elute chromatography (Fischer et al, 2018; Silva et al, 2020).…”

An integrated continuous downstream process with real‐time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

“…Another reason for studying integrated and continuous processes is the need for flexibility to allow many similar candidates to be rapidly produced and screened. Many studies on integrated continuous biomanufacturing processes have been performed on monoclonal antibodies (Arnold et al, 2019; Godawat et al, 2015; Gomis‐Fons et al, 2020; Kamga et al, 2018; Steinebach et al, 2017). Continuous approaches and techniques for capture steps have been explored previously, such as the commercial BioSMB™ technology (Bisschops & Brower, 2013).…”

“…For example, Mendhe et al (2015) analyzed a variety of PAT‐based pooling strategies and found that the most successful application was a feedforward approach based on the retention time of a characteristic peak eluting before the main peak. Another example is the implementation of a strategy to control the load factor in a twin‐column periodic capture step coupled with a bioreactor for the production of monoclonal antibodies, as in our previous study (Gomis‐Fons et al, 2020), which was achieved by online estimation of the harvest concentration and the model‐based assessment of the dynamic binding capacity of the column. This type of control is necessary to avoid overloading the column when the harvest concentration increases, or to maximize the resin utilization when the harvest concentration is low.…”