This paper provides a perspective on the increasingly critical role that systems analysis and process control play in bioprocess development today. This is particularly of importance to the manufacturers of biotech therapeutics since the product quality is critical and depends on the process and its control. Because a large number of process variables and raw materials can influence the overall outcome of a bioprocess, the correct determination of the process trajectory is often an intensive exercise. A follow-up involving design of a suitable process control strategy for implementation of process conditions would be logical. However, such an exercise can no longer consider each unit operation one at a time but rather requires holistic inclusion of all upstream and downstream unit operations for successfully meeting the global standards laid down by various regulatory agencies by exploring the potential of process analytical technology (PAT) to achieve bigger objectives. In this perspective, we focus on the core issues associated with process integration and how may these influence future process development.
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.
A real time monitoring of fouling in liquid chromatography has been presented. The versatility of the approach has been proven by successful implementation in three case studies with an error <1%. The first application demonstrates the monitoring of protein A ligand density and foulant concentration for assessing performance of protein A chromatography resin during purification of monoclonal antibodies. The observations have been supported from LC-MS/MS studies that were independently performed. The second application involves monitoring of foulant deposition during multimode cation exchange chromatography based purification of human serum albumin. Finally, in the third application, monitoring of foulants during multimodal hydrophobic interaction chromatography of recombinant human granulocyte colony stimulating factor is demonstrated. In all three cases, it is observed that the fluorescence intensity consistently increases with resin reuse as more foulants are deposited over time. The proposed approach can be readily used for real time monitoring of fouling and process control.
Continuous bioprocessing is significantly changing the biological drugs (or biologics) manufacturing landscape by potentially improving product quality, process stability, and overall profitability, as was similarly seen during the adoption of advanced manufacturing processes for small molecule drugs in the past decade. However, the implementation of continuous manufacturing for biological processes producing protein-based drug molecules, such as monoclonal antibodies (mAbs), is facing several new hurdles. The barriers to continuous bioprocessing can be overcome through improved process understanding via better predictive capabilities enabled by hybrid modeling that can also lead to robust process control. This review article summarizes the recent advances and ongoing obstacles faced during the use of advanced process analytical technologies (PAT), process modeling, and control strategies to enable continuous manufacturing of mAbs. In addition, this review also discusses the process strategies and future directions of advanced continuous manufacturing approaches that have been adapted by other industries and that could be implemented for mAbs production soon.
A decoupled input-output linearizing controller (DIOLC) was designed as an alternative advanced control strategy for controlling bioprocesses. Simulation studies of its implementation were carried out to control ethanol and biomass production in Saccharomyces cerevisiae and its performance was compared to that of a proportional-integral-derivative (PID) controller with parameters tuned according to a linear schedule. The overall performance of the DIOLC was better in the test experiments requiring the controllers to respond accurately to simultaneous changes in the trajectories of the substrate and dissolved oxygen concentration. It also exhibited better performance in perturbation experiments of the most significant parameters q (S,max), q (O2,max), and k ( s ), determined through a statistical design of experiments involving 730 simulations. DIOLC exhibited a superior ability of constraining the process when implemented in extreme metabolic regimes of high oxygen demand for maximizing biomass concentration and low oxygen demand for maximizing ethanol concentration.
Mass transfer is known to play a critical role in bioprocess performance and henceforth monitoring dissolved O2 (DO) and dissolved CO2 (dCO2) is of paramount importance. At bioreactor level these parameters can be monitored online and can be controlled by sparging air/oxygen or stirrer speed. However, traditional small‐scale systems such as shake flasks lack real time monitoring and also employ only surface aeration with additional diffusion limitations imposed by the culture plug. Here we present implementation of intensifying surface aeration by sparging air in the headspace of the reaction vessel and real‐time monitoring of DO and dCO2 in the bioprocesses to evaluate the impact of intensified surface aeration. We observed that sparging air in the headspace allowed us to keep dCO2 at low level, which significantly improved not only biomass growth but also protein yield. We expect that implementing such controlled smart shake flasks can minimize the process development gap which currently exists in shake flask level and bioreactor level results.
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