A Systematic Framework for Process Control Design and Risk Analysis in Continuous Pharmaceutical Solid-Dosage Manufacturing

The paradigm shift in the pharmaceutical industry to continuous manufacturing, which has recently progressed from conceptual demonstration to pilot production, has stimulated the development and application of process systems engineering (PSE) tools for implementing efficient and robust control strategies. In this study, a systematic framework for process control design and risk analysis for continuous pharmaceutical solid-dosage manufacturing is proposed, consisting of system identification with state-space models; control design and analysis metrics; hierarchical three-layer control structures; risk mapping, assessment and planning (Risk MAP) strategies; and control performance indicators. The framework is applied to a feeding-blending system, wherein the major source of variance in the product quality arises. It can be demonstrated that the variance in the feeding-blending system can be mitigated and managed through the proposed systematic framework for control design and risk analysis. The process analytical technology (PAT) tool for mass fraction measurement of active pharmaceutical ingredient (API) and its relative standard deviation (RSD) were indispensable to achieve an efficient control design at the advanced layers. Specifically, the improvements in control performance by implementing advanced model-based control strategy are found to be limited by model-plant mismatch and the sampling time of the PAT tools.

[1]  Lawrence X. Yu,et al.  Modernizing Pharmaceutical Manufacturing: from Batch to Continuous Production , 2015, Journal of Pharmaceutical Innovation.

[2]  Manfred Morari,et al.  Design of resilient processing plants—III: A general framework for the assessment of dynamic resilience , 1983 .

[3]  Zoltan K. Nagy,et al.  Dynamic impact milling model with a particle-scale breakage kernel , 2016 .

[4]  Brahim Benyahia,et al.  A Plant-Wide Dynamic Model of a Continuous Pharmaceutical Process , 2012 .

[5]  Michael T Harris,et al.  A novel microwave sensor to determine particulate blend composition on-line. , 2014, Analytica chimica acta.

[6]  Sigurd Skogestad,et al.  Simple frequency-dependent tools for control system analysis, structure selection and design , 1992, Autom..

[7]  Marianthi Ierapetritou,et al.  An engineering study on the enhanced control and operation of continuous manufacturing of pharmaceutical tablets via roller compaction. , 2012, International journal of pharmaceutics.

[8]  Thomas F. Edgar,et al.  Process Dynamics and Control , 1989 .

[9]  Michael Nikolaou,et al.  MPC: Current practice and challenges , 2012 .

[10]  Aditya U. Vanarase,et al.  Real-time monitoring of drug concentration in a continuous powder mixing process using NIR spectroscopy , 2010 .

[11]  Richard D. Braatz,et al.  The Application of an Automated Control Strategy for an Integrated Continuous Pharmaceutical Pilot Plant , 2015 .

[12]  Fernando J. Muzzio,et al.  Using Compartment Modeling to Investigate Mixing Behavior of a Continuous Mixer , 2008, Journal of Pharmaceutical Innovation.

[13]  G. Hewer,et al.  Necessary and sufficient conditions for balancing unstable systems , 1987 .

[14]  Zoltan K. Nagy,et al.  Evaluation study of an efficient output feedback nonlinear model predictive control for temperature tracking in an industrial batch reactor , 2007 .

[15]  Randy Zachery,et al.  Singular value decomposition of system input-output matrix and its symmetry property , 1996 .

[16]  Gintaras V. Reklaitis,et al.  Intelligent Alarm Management Applied to Continuous Pharmaceutical Tablet Manufacturing: An Integrated Approach , 2013 .

[17]  Babu Joseph,et al.  Inferential control of processes: Part I. Steady state analysis and design , 1978 .

[18]  Marianthi G. Ierapetritou,et al.  A systematic framework for onsite design and implementation of a control system in a continuous tablet manufacturing process , 2014, Comput. Chem. Eng..

[19]  Gene F. Franklin,et al.  Digital control of dynamic systems , 1980 .

[20]  Sudarshan Ganesh,et al.  Application of X-Ray Sensors for In-line and Noninvasive Monitoring of Mass Flow Rate in Continuous Tablet Manufacturing. , 2017, Journal of pharmaceutical sciences.

[21]  Klavs F. Jensen,et al.  Synthesis of control structures by singular value analysis: Dynamic measures of sensitivity and interaction , 1985 .

[22]  Richard D. Braatz,et al.  Just-in-Time-Learning based Extended Prediction Self-Adaptive Control for batch processes , 2016 .

[23]  Weining Feng,et al.  A New Procedure to Account for Performance Interaction in Multivariable Systems , 1989, 1989 American Control Conference.

[24]  Richard D. Braatz,et al.  Model‐based design of a plant‐wide control strategy for a continuous pharmaceutical plant , 2013 .

[25]  Krist V. Gernaey,et al.  Model-based computer-aided framework for design of process monitoring and analysis systems , 2009, Comput. Chem. Eng..

[26]  Sergio M. Savaresi,et al.  Control System Design for a Continuous Gravimetric Blender , 2011 .

[27]  Athanasios C. Antoulas,et al.  Approximation of Large-Scale Dynamical Systems , 2005, Advances in Design and Control.

[28]  Manfred Morari,et al.  Interaction measures for systems under decentralized control , 1986, Autom..

[29]  G. K. Raju,et al.  Understanding Pharmaceutical Quality by Design , 2014, The AAPS Journal.

[30]  Lakshman Pernenkil,et al.  Continuous blending of dry pharmaceutical powders , 2008 .

[31]  Zhong-xiang Zhu Variable Pairing Selection Based on Individual and Overall Interaction Measures , 1996 .

[32]  Marianthi Ierapetritou,et al.  Integrated Moving Horizon-Based Dynamic Real-Time Optimization and Hybrid MPC-PID Control of a Direct Compaction Continuous Tablet Manufacturing Process , 2015, Journal of Pharmaceutical Innovation.

[33]  Gintaras V. Reklaitis,et al.  Modeling and Control of Roller Compaction for Pharmaceutical Manufacturing , 2010, Journal of Pharmaceutical Innovation.

[34]  Marianthi G. Ierapetritou,et al.  Modeling of Particulate Processes for the Continuous Manufacture of Solid-Based Pharmaceutical Dosage Forms , 2013 .

[35]  G. Reklaitis,et al.  Perspectives on the continuous manufacturing of powder‐based pharmaceutical processes , 2016 .

[36]  Gintaras V. Reklaitis,et al.  Modeling and Control of Roller Compaction for Pharmaceutical Manufacturing. Part I: Process Dynamics and Control Framework , 2010, Journal of Pharmaceutical Innovation.

[37]  Martin Horn,et al.  Optimized continuous pharmaceutical manufacturing via model-predictive control. , 2016, International journal of pharmaceutics.

[38]  John F. MacGregor,et al.  Robustness of multivariable linear controllers to process nonlinearities , 1992 .

[39]  Fernando J. Muzzio,et al.  A Combined Feed-Forward/Feed-Back Control System for a QbD-Based Continuous Tablet Manufacturing Process , 2015 .

[40]  Rohit Ramachandran,et al.  Model-Based Control-Loop Performance of a Continuous Direct Compaction Process , 2011, Journal of Pharmaceutical Innovation.