The industrial production of complex biopharmaceuticals using recombinant mammalian cell lines is still mainly built on a quality by testing approach, which is represented by fixed process conditions and extensive testing of the end-product. In 2004 the FDA launched the process analytical technology initiative, aiming to guide the industry towards advanced process monitoring and better understanding of how critical process parameters affect the critical quality attributes. Implementation of process analytical technology into the bio-production process enables moving from the quality by testing to a more flexible quality by design approach. The application of advanced sensor systems in combination with mathematical modelling techniques offers enhanced process understanding, allows on-line prediction of critical quality attributes and subsequently real-time product quality control. In this review opportunities and unsolved issues on the road to a successful quality by design and dynamic control implementation are discussed. A major focus is directed on the preconditions for the application of model predictive control for mammalian cell culture bioprocesses. Design of experiments providing information about the process dynamics upon parameter change, dynamic process models, on-line process state predictions and powerful software environments seem to be a prerequisite for quality by control realization.
Keywords: Biopharmaceutical production · Design of experiments · Mathematical modelling · Process analytical technology · Soft-sensingCorrespondence: Dr. Gerald Striedner, Department of Biotechnology (DBT), University of Natural Resources and Life Sciences (BOKU), Muthgasse 18, 1190 Vienna, Austria E-mail: gerald.striedner@boku.ac.at Abbreviations: CHO, Chinese hamster ovary; CPP, critical process parameter; CQA, critical quality attribute; DCS, distributed control system; DoE, design of experiments; FDA, Food and Drug Administration; iDoE, intensified design of experiments; MBDoE, model based design of experiments; MPC, model predictive control; MVDA, multivariate data analysis; PAT, process analytical technology; QbD, quality by design; SCADA, supervisory control and data acquisition; TPP, target product profile