Bridging the gap between PAT concepts and implementation: An integrated software platform for fermentation

Bioreactor control significantly impacts both the amount and quality of the product being manufactured. The complexity of the control strategy that is implemented increases with reactor size, which may vary from thousands to tens of thousands of litres in commercial manufacturing. The Process Analytical Technology (PAT) initiative has highlighted the need for having robust monitoring tools and effective control schemes that are capable of taking real time information about the critical quality attributes (CQA) and the critical process parameters (CPP) and executing immediate response as soon as a deviation occurs. However, the limited flexibility that present commercial software packages offer creates a hurdle. Visual programming environments have gradually emerged as potential alternatives to the available text based languages. This paper showcases development of an integrated programme using a visual programming environment for a Sartorius BIOSTAT® B Plus 5L bioreactor through which various peripheral devices are interfaced. The proposed programme facilitates real‐time access to data and allows for execution of control actions to follow the desired trajectory. Major benefits of such integrated software system include: (i) improved real time monitoring and control; (ii) reduced variability; (iii) improved performance; (iv) reduced operator‐training time; (v) enhanced knowledge management; and (vi) easier PAT implementation.

[1]  Sigurd Skogestad,et al.  An industrial and academic perspective on plantwide control , 2011, Annu. Rev. Control..

[2]  David A. Burdge,et al.  Open Source Software to Control Bioflo Bioreactors , 2014, PloS one.

[3]  Carl-Fredrik Mandenius,et al.  Integration of distributed multi-analyzer monitoring and control in bioprocessing based on a real-time expert system. , 2003, Journal of biotechnology.

[4]  Anurag S. Rathore,et al.  Integrating systems analysis and control for implementing process analytical technology in bioprocess development , 2015 .

[5]  George Stephanopoulos,et al.  Perspectives on the synthesis of plant-wide control structures , 2000 .

[6]  Gregory M. Troup,et al.  Process systems engineering tools in the pharmaceutical industry , 2013, Comput. Chem. Eng..

[7]  Cosku Kasnakoglu,et al.  Simulation time analysis of MATLAB/Simulink and LabVIEW for control applications , 2015, 2015 IEEE International Conference on Industrial Technology (ICIT).

[8]  A S Rathore,et al.  Process analytical technology (PAT) for biopharmaceutical products: Part I. concepts and applications , 2010, Biotechnology and bioengineering.

[9]  M E Gregory,et al.  A visual programming environment for bioprocess control. , 1994, Journal of biotechnology.

[10]  Sebastian Engell,et al.  Optimal operation: Scheduling, advanced control and their integration , 2012, Comput. Chem. Eng..

[11]  Ana P. Teixeira,et al.  Advances in on-line monitoring and control of mammalian cell cultures: Supporting the PAT initiative. , 2009, Biotechnology advances.

[12]  N. Aziz,et al.  Control Implementation in Bioprocess System: A Review , 2007 .

[13]  Anurag S. Rathore,et al.  On-line implementation of decoupled input-output linearizing controller in Baker's yeast fermentation , 2013 .

[14]  Anurag S. Rathore,et al.  QbD/PAT for bioprocessing: moving from theory to implementation , 2014 .

[15]  Raynitchka Tzoneva,et al.  Integrating LabVIEW capabilities for monitoring and supervisory control with a B-Braun Biotech Gmbh unit for fermentation processing and direct control , 2005 .

[16]  Günter Wozny,et al.  Plantwide Optimizing Control for the Continuous Bio-Ethanol Production Process , 2010 .

[17]  A. Daugulis,et al.  Mixed-feed exponential feeding for fed-batch culture of recombinant methylotrophic yeast , 2000, Biotechnology Letters.

[18]  Kalle Salonen,et al.  BIOREACTOR MEASUREMENT AND SIMULATION ENVIRONMENT , 2007 .

[19]  A S Rathore,et al.  Comparative Performance of Decoupled Input–Output Linearizing Controller and Linear Interpolation PID Controller: Enhancing Biomass and Ethanol Production in Saccharomyces cerevisiae , 2013, Applied Biochemistry and Biotechnology.

[20]  Joseph S. Alford,et al.  Bioprocess control: Advances and challenges , 2006, Comput. Chem. Eng..

[21]  Udo Reichl,et al.  How can measurement, monitoring, modeling and control advance cell culture in industrial biotechnology? , 2012, Biotechnology journal.

[22]  Anurag S Rathore,et al.  Maximizing biomass concentration in baker's yeast process by using a decoupled geometric controller for substrate and dissolved oxygen. , 2015, Bioresource technology.

[23]  A S Rathore,et al.  Process analytical technology (PAT) for biopharmaceutical products: Part II. Concepts and applications , 2010, Biotechnology and bioengineering.

[24]  Andrzej Stankiewicz,et al.  Opportunities and challenges for process control in process intensification , 2012 .

[25]  J Glassey,et al.  Issues in the development of an industrial bioprocess advisory system. , 2000, Trends in biotechnology.

[26]  Rimvydas Simutis,et al.  Control of cultivation processes for recombinant protein production: a review , 2008, Bioprocess and biosystems engineering.

[27]  Carl-Fredrik Mandenius,et al.  Soft sensors in bioprocessing: a status report and recommendations. , 2012, Biotechnology journal.

[28]  Jörg Edler,et al.  Comparison of LabVIEW and MATLAB for scientific research , 2012 .

[29]  Carl-Fredrik Mandenius,et al.  Process analytical technology (PAT) for biopharmaceuticals , 2011, Biotechnology journal.

[30]  Kai Loegering,et al.  Sequential/parallel production of potential Malaria vaccines--A direct way from single batch to quasi-continuous integrated production. , 2015, Journal of biotechnology.

[31]  Anton A. Kiss,et al.  A systems engineering perspective on process integration in industrial biotechnology , 2015 .

[32]  Krist V. Gernaey,et al.  Report and recommendation of a workshop on education and training for measurement, monitoring, modelling and control (M3C) in biochemical engineering , 2010, Biotechnology journal.