(577g) Industry 4.0: Advanced Bi-Layer Control System for Continuous Pharmaceutical Manufacturing Pilot-Plant

The industry 4.0 standard continuous pharmaceutical manufacturing (CM) integrated with real time monitoring, advanced process control (APC), and a novel data management system is highly desired to consistently produce the better quality product with less time and resources. This modernized integrated system also open the possibilities of achieving Quality by Control (QbC) and real time release (RTR) paradigm [1-2]. However, there are different levels of challenges in implementation of industry 4.0 standard CM including advanced process control system. Therefore, this is still an open area of research.

In this work, a bi-layer advanced control strategy has been developed and implemented into CM pilot-plant using industry standard real time monitoring sensors, data management tool and control platform. In first layer, the CPP’s and CQA’s are controlled in real time using advanced model predictive control (MPC) system while in second layer, the none-confirming products are diverted in real time in waste to assure the final CQA’s of qualified tablet lots. This bi-layer control strategy assures the final product quality, improves the production efficiency and minimizes the need of off line testing.

The critical control variables that have been controlled in first layer using model predictive control (MPC) system are drug concertation, powder level before tablet press, main and pre compression forces, tablet weight and hardness. A novel control strategy for powder level control in a chute placed in between blender and tablet press unit operation of continuous tablet manufacturing process has been developed, implemented and evaluated. A noninvasive technique based on change in electric field concept has been used for real time monitoring of powder level in continuous manufacturing pilot-plant. The sensor has been integrated with a control panel (DeltaV (Emerson)) through relays and charms. The control panel then send the signal (4-20 mA) to control platform where the control strategy, a program to operate the sensor and a program to convert the sensor signal into powder level have been implemented. Subsequently, an advanced model predictive controller for powder level have been implemented into our continuous pharmaceutical manufacturing pilot-plant facility. The APC has been used to control feeder, blender and tablet press as well.

A systematic framework including the methods and tools for real time diversion of tablets have been developed and implemented into continuous pharmaceutical manufacturing process as a second layer assurance of product quality. In CM, the drug concentration is measured in real time before the tablet compaction (chute &/or feed frame) using PAT sensor. The proposed control strategy then uses this inlet concentration to determine a signal for the diversion strategy that can accurately be used to reject tablets that are out of tolerance limits at the outlet of the tablet press. Two strategies, i.e. ‘fixed window based strategy’ and RTD based strategy have been developed, compared and evaluated. In fixed window approach, the tablet diversion is facilitated through knowledge of time delays from the point of detection to the point of the affect (tablet press outlet gate) in the system. The sensor that detects the concentration is connected to a comparator block which decides if the said concentration is within the specifications. If it is not within specification, the experimentally derived time delay is applied and post this the diversion begins. The diversion stops when a concentration within spec is detected and the another time delay is applied. In RTD based approach, the RTD is used to predict the outlet concentration from the inlet concentration. The predicted signal is then used to initiate the diversion. The first approach is simpler to implement but may lead to lower production efficiency. The second approach is based on more advanced technique and will ensure more efficiency but is relatively complex to implement. All the relevant data generated during continuous manufacturing has been systematically collected, stored and organized in a data hub (OSI PI) and cloud system as per industry 4.0 standard.

The objective of this presentation is to demonstrate the performance of integrated MPC and RTD based bi-layer control strategy together with advanced data management system implemented into our continuous pharmaceutical manufacturing pilot-plant facility.

References

1. Bhaskar, A., Barros, F. N., Singh, R. (2017). Development and implementation of an advanced model predictive control system into continuous pharmaceutical tablet compaction process. International Journal of Pharmaceutics, 534 (1-2), 159-178.
2. Bhaskar, A., Singh, R. (2018). Residence time distribution (RTD) based control system for continuous pharmaceutical manufacturing process. Journal of Pharmaceutical Innovation. DOI: 10.1007/s12247-018-9356-7.