Process control design implementation for

continuous manufacturing of tablets

Introduction

The pharmaceutical industry has always implemented the traditional batch processes for Active Pharmaceutical Ingredient (API) manufacturing. The industry has opted for batch processing as it has several advantages such as flexibility in configuration of the plant unit operations, convenient tracking of different drugs at various stages of production and dispatch and product recalls. However, there is high variability in the product quality from batch to batch, challenges in scale up from laboratory to pilot to commercial manufacturing scale1. Due to these limitations, the pharmaceutical industry is enthusiastic on implementing continuous manufacturing1-2. Continuous Manufacturing (CM) has various advantages when compared to batch processing such as: integrated processing with fewer steps, increased safety, no manual handling, less carbon footprint, lower capital costs, etc. Currently various organizations have filed for approvals for producing new drugs via continuous manufacturing and hence FDA is keen on developing new standards with respect to continuous manufacturing, serialization and traceability of the API and final dosage forms. However, there are several technical challenges involved in development and implementation of continuous manufacturing of powder-based API processes. Some of them are material characterization and properties prediction, online measurement, modelling and simulation of unit operations & processes1. The goal of this project is to develop and implement process automation and control system design to ensure robust operation of the Tablet press2.

Literature Review

Continuous manufacturing is strongly united with the FDA’s support of the quality-by-design (QbD) model for pharmaceutical development and manufacturing. QbD is a systematic, scientific and risk-based approach which demonstrates product and process understanding to implement effective quality control strategies to achieve the desired results.  A robust process can be developed by identifying the variation sources of product quality and design appropriate control strategies to mitigate the risks associated with it3.  Some of the main barriers of implementation of closed loop control and advanced strategies are:

Integration of hardware, software and process equipment sensors due to the lack of standard control systems

Challenges in real time/online/inline monitoring of process parameters

Control strategies appropriate for continuous tablet manufacturing processes are still under development

Lack of availability of a commercial control4  

Therefore, for the pharmaceutical industry to successfully transition to continuous manufacturing, a systematic framework for process control design and risk analysis is required5. Various control techniques, ranging from simple proportional-integral-derivative (PID) controllers to advanced model-based control strategies (MPC) and real time optimization have been verified for set point tracking and rejection of disturbances observed during the process5. However, it has been identified that a resilient and fault-tolerant plant wide control system design plays a vital role in executing a safe continuous manufacturing process6. By implementing the proposed systematic framework integrated with hardware control and sensing technologies, more efficient manufacturing operations and QbD can be easily facilitated in the industry4.

2.1 Systematic framework for Process Control Design and Risk Analysis

In a typical batch manufacturing setup, the quality control of the product is done by extensive testing of the final dosage form. Whereas, in a continuous manufacturing setup, the quality of the product and the intermediate streams leading to it should be monitored and controlled in real time at its specified points. The control framework should respond to all variations arising due to disturbances in process variables, equipment conditions, incoming raw materials so that the product quality is unaffected. This is usually referred to as real-time release. A systematic framework consisting of various process systems engineering (PSE) and process analytical technology (PAT) tools, to develop and evaluate feasible advanced control strategies is shown in Fig12, 5.

Fig.1 Systematic framework for process control design and risk analysis

By integrating additional knowledge and supporting tools with the proposed systematic framework, the design and implementation of the control strategy can be easily integrated into the software and hardware of the system2, 5. 

2.2 Resilient fault-tolerant control design

In general, there are two main approaches to handle faults. The first approach is to respond to the failure by re-organizing the remaining system parameters to complete necessary control functions. The second approach is to design a system which is failure proof for a well-defined fault/risk sets7.  Fault tolerant control systems primarily aim at preventing any simple fault from developing into a failure at system level and use information redundancy to detect faults6.

2.3 A Hierarchical three-layer control design

The risk of producing out of specification products can be reduced by implementing advance control strategies such as fault tolerant control systems and predictive state space models. Such models allow the application of control strategies that automatically adjust the critical process parameters (CPPs) in response to any disturbances created to ensure that the critical quality attributes (CQAs) are unaffected and in the desired specification range2, 5.

As shown in Fig. 2, a control strategy can include three levels of controls in pharmaceutical management systems. This proposed classification is general and can be applied to both batch and continuous manufacturing systems. Depending on the process requirement and desired control performance, the complexity of the design can be manipulated5, 8.

Fig 2. General three-layer classification of control strategies

For example (see Fig 3), in a direct compaction process using a tablet press, the Level 0 control includes single/multiple loop single input single output (SISO) control. This is executed using a programmable logic control (PLC) panel built in the equipment. Usually, this level of control is designed by the vendor to control multiple CPPs to the given set point as desired by the end user. The Level 1 control also involves a single or multiple SISO controllers, but the control loop mainly depends on the data measured by the PAT tools to control CQAs. The Level 1 control manages Level 0 using a cascaded loop to achieve the desired set points of the CQAs, measured in situ by the PAT sensors.  The Level 2 uses more advanced control strategies such as mathematical models to predict the effect of disturbances in the CPPs and CQAs. Level 2 can accommodate large multivariable systems and integrates multiple unit operations. Hence, it can be used for executing plant wide process control.

Fig 3. The hierarchical three-layer control design in direct compaction.

Experiments and Results

Seventy five percent of the pharmaceutical products manufactured are solids produced mainly using direct compression, dry granulation or wet granulation to accommodate the formulation requirements. 

References:

Ierapetritou, M.; Muzzio, F.; Reklaitis, G., Perspectives on the continuous manufacturing of powder‐based pharmaceutical processes. AIChE Journal 2016, 62 (6), 1846-1862.

Su, Q.; Moreno, M.; Ganesh, S.; Reklaitis, G. V.; Nagy, Z. K., Resilience and risk analysis of fault-tolerant process control design in continuous pharmaceutical manufacturing. Journal of Loss Prevention in the Process Industries 2018, 55, 411-422.

Lee, S.; O’Connor, T.; Yang, X.; Cruz, C.; Chatterjee, S.; Madurawe, R.; Moore, C.; Yu, L.; Woodcock, J., Modernizing Pharmaceutical Manufacturing: from Batch to Continuous Production. From R&D to Market 2015, 10 (3), 191-199.

Singh, R.; Sahay, A.; Muzzio, F.; Ierapetritou, M.; Ramachandran, R., A systematic framework for onsite design and implementation of a control system in a continuous tablet manufacturing process. Computers and Chemical Engineering 2014, 66.

Su, Q.; Moreno, M.; Giridhar, A.; Reklaitis, G.; Nagy, Z., A Systematic Framework for Process Control Design and Risk Analysis in Continuous Pharmaceutical Solid-Dosage Manufacturing. From R&D to Market 2017, 12 (4), 327-346.

Blanke, M.; Izadi-Zamanabadi, R.; Bøgh, S. A.; Lunau, C. P., Fault-tolerant control systems — A holistic view. Control Engineering Practice 1997, 5 (5), 693-702.

Jiang, J.; Yu, X., Fault-tolerant control systems: A comparative study between active and passive approaches. Annual Reviews in Control 2012, 36 (1), 60-72.

Yu, L.; Amidon, G.; Khan, M.; Hoag, S.; Polli, J.; Raju, G.; Woodcock, J., Understanding Pharmaceutical Quality by Design. An Official Journal of the American Association of Pharmaceutical Scientists 2014, 16 (4), 771-783.