Surrogate-Based Optimization of Expensive Flowsheet Modeling for Continuous Pharmaceutical Manufacturing

Simulation-based optimization is a research area that is currently attracting a lot of attention in many industrial applications, where expensive simulators are used to approximate, design, and optimize real systems. Pharmaceuticals are typical examples of high-cost products which involve expensive processes and raw materials while at the same time must satisfy strict quality regulatory specifications, leading to the formulation of challenging and expensive optimization problems. The main purpose of this work was to develop an efficient strategy for simulation-based design and optimization using surrogates for a pharmaceutical tablet manufacturing process. The proposed approach features surrogate-based optimization using kriging response surface modeling combined with black-box feasibility analysis in order to solve constrained and noisy optimization problems in less computational time. The proposed methodology is used to optimize a direct compaction tablet manufacturing process, where the objective is the minimization of the variability of the final product properties while the constraints ensure that process operation and product quality are within the predefined ranges set by the Food and Drug Administration.

[1]  Dimitris Bertsimas,et al.  Robust Optimization for Unconstrained Simulation-Based Problems , 2010, Oper. Res..

[2]  Marianthi G. Ierapetritou,et al.  A centroid-based sampling strategy for kriging global modeling and optimization , 2009 .

[3]  Krist V. Gernaey,et al.  A perspective on PSE in pharmaceutical process development and innovation , 2012, Comput. Chem. Eng..

[4]  Rommel G. Regis,et al.  Stochastic radial basis function algorithms for large-scale optimization involving expensive black-box objective and constraint functions , 2011, Comput. Oper. Res..

[5]  Sonja Kuhnt,et al.  Design and analysis of computer experiments , 2010 .

[6]  A. B. Antognini,et al.  Exact optimal designs for computer experiments via Kriging metamodelling , 2010 .

[7]  Joachim Werther,et al.  Flowsheet simulation of solids processes: Data reconciliation and adjustment of model parameters , 2008 .

[8]  Ka Ming Ng,et al.  Design and development of solids processes - a process systems engineering perspective , 2002 .

[9]  Donald R. Jones,et al.  A Taxonomy of Global Optimization Methods Based on Response Surfaces , 2001, J. Glob. Optim..

[10]  John McConnell,et al.  Six Sigma in the Pharmaceutical Industry: Understanding, Reducing, and Controlling Variation in Pharmaceuticals and Biologics , 2007 .

[11]  Ignacio E. Grossmann,et al.  Systematic Methods of Chemical Process Design , 1997 .

[12]  San Kiang,et al.  Can pharmaceutical process development become high tech , 2006 .

[13]  Michael C. Fu,et al.  Feature Article: Optimization for simulation: Theory vs. Practice , 2002, INFORMS J. Comput..

[14]  Marianthi G. Ierapetritou,et al.  Computer Aided Design and Analysis of Continuous Pharmaceutical Manufacturing Processes , 2011 .

[15]  Rohit Ramachandran,et al.  A multi-dimensional population balance model approach to continuous powder mixing processes , 2013 .

[16]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[17]  Deng Huang,et al.  Experimental planning and sequential kriging optimization using variable fidelity data , 2005 .

[18]  I. Grossmann,et al.  An algorithm for the use of surrogate models in modular flowsheet optimization , 2008 .

[19]  Warren D. Seider,et al.  Product and Process Design Principles: Synthesis, Analysis, and Evaluation , 1998 .

[20]  B. Nunnally,et al.  Comprar Six Sigma in the Pharmaceutical Industry: Understanding, Reducing, and Controlling Variation in Pharmaceuticals and Biologics | John S. McConnell | 9781420054392 | Informa Healthcare , 2007 .

[21]  Donald R. Jones,et al.  Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..

[22]  R.,et al.  Density-Pressure Relationships in Powder Compaction , 2010 .

[23]  M. Patriksson,et al.  A method for simulation based optimization using radial basis functions , 2010 .

[24]  Aditya U. Vanarase,et al.  Multi-dimensional population balance modeling and experimental validation of continuous powder mixing processes , 2012 .

[25]  J. Yin,et al.  Kriging metamodel with modified nugget-effect: The heteroscedastic variance case , 2011, Comput. Ind. Eng..

[26]  Noel A. C. Cressie,et al.  Statistics for Spatial Data: Cressie/Statistics , 1993 .

[27]  Thomas J. Santner,et al.  The Design and Analysis of Computer Experiments , 2003, Springer Series in Statistics.

[28]  Joachim Werther,et al.  Design specifications in the flowsheet simulation of complex solids processes , 2009 .

[29]  A. J. Booker,et al.  A rigorous framework for optimization of expensive functions by surrogates , 1998 .

[30]  Marianthi G. Ierapetritou,et al.  Design Optimization under Parameter Uncertainty for General Black-Box Models , 2002 .

[31]  K. Plumb,et al.  Continuous Processing in the Pharmaceutical Industry: Changing the Mind Set , 2005 .

[32]  Silvana M. B. Afonso,et al.  A concurrent efficient global optimization algorithm applied to polymer injection strategies , 2010 .

[33]  Antonios Zavaliangos,et al.  Comparison of various modeling methods for analysis of powder compaction in roller press , 2003 .

[34]  G. Box,et al.  On the Experimental Attainment of Optimum Conditions , 1951 .

[35]  Kwang-Yong Kim,et al.  Enhanced multi-objective optimization of a microchannel heat sink through evolutionary algorithm coupled with multiple surrogate models , 2010 .

[36]  Gintaras V. Reklaitis,et al.  Simulation-based optimization with surrogate models - Application to supply chain management , 2005, Comput. Chem. Eng..

[37]  Marianthi G. Ierapetritou,et al.  Computational Approaches for Studying the Granular Dynamics of Continuous Blending Processes, 2 – Population Balance and Data‐Based Methods , 2012 .

[38]  Charles Audet,et al.  A method for stochastic constrained optimization using derivative-free surrogate pattern search and collocation , 2010, J. Comput. Phys..

[39]  Grazia Vicario,et al.  New Sampling Procedures in Coordinate Metrology Based on Kriging-Based Adaptive Designs , 2009 .

[40]  Marianthi G. Ierapetritou,et al.  A kriging based method for the solution of mixed-integer nonlinear programs containing black-box functions , 2009, J. Glob. Optim..

[41]  Dimitrios I. Gerogiorgis,et al.  Economic Analysis of Integrated Continuous and Batch Pharmaceutical Manufacturing: A Case Study , 2011 .

[42]  Raphael T. Haftka,et al.  Surrogate-based Analysis and Optimization , 2005 .

[43]  William J. Welch,et al.  Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization , 2006 .

[44]  Marianthi G. Ierapetritou,et al.  An integrated approach for dynamic flowsheet modeling and sensitivity analysis of a continuous tablet manufacturing process , 2012, Comput. Chem. Eng..

[45]  Jack P. C. Kleijnen,et al.  Kriging Metamodeling in Simulation: A Review , 2007, Eur. J. Oper. Res..

[46]  N. Zheng,et al.  Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models , 2006, J. Glob. Optim..

[47]  Marianthi G. Ierapetritou,et al.  Feasibility Evaluation of Nonconvex Systems Using Shape Reconstruction Techniques , 2005 .

[48]  Tao Yu,et al.  Reliable multi-objective optimization of high-speed WEDM process based on Gaussian process regression , 2008 .

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

[50]  Gintaras V. Reklaitis,et al.  Process systems engineering: From Solvay to modern bio- and nanotechnology.: A history of development, successes and prospects for the future , 2011 .

[51]  Krist V. Gernaey,et al.  A model-based systems approach to pharmaceutical product-process design and analysis , 2010 .

[52]  Pasquale Erto,et al.  Statistics for Innovation , 2009 .

[53]  Eric Walter,et al.  Global optimization of expensive-to-evaluate functions: an empirical comparison of two sampling criteria , 2009, J. Glob. Optim..

[54]  Andy J. Keane,et al.  Engineering Design via Surrogate Modelling - A Practical Guide , 2008 .

[55]  Grazia Vicario,et al.  Design for Computer Experiments: comparing and generating designs in Kriging models , 2009 .

[56]  Marianthi G. Ierapetritou,et al.  A Kriging-Based Approach to MINLP Containing Black-Box Models and Noise , 2008 .

[57]  Marianthi G. Ierapetritou,et al.  Feasibility analysis of black-box processes using an adaptive sampling Kriging-based method , 2012, Comput. Chem. Eng..

[58]  R. Pinal,et al.  Utility of Multivariate Analysis in Modeling the Effects of Raw Material Properties and Operating Parameters on Granule and Ribbon Properties Prepared in Roller Compaction , 2008 .

[59]  Spandan Maiti,et al.  Computationally efficient black-box modeling for feasibility analysis , 2010, Comput. Chem. Eng..

[60]  Joachim Werther,et al.  Flowsheeting of solids processes for energy saving and pollution reduction , 2004 .

[61]  Ignacio E. Grossmann,et al.  Optimal process design under uncertainty , 1983 .

[62]  Lawrence X. Yu.  Pharmaceutical Quality by Design: Product and Process Development, Understanding, and Control , 2008, Pharmaceutical Research.

[63]  Eric Walter,et al.  An informational approach to the global optimization of expensive-to-evaluate functions , 2006, J. Glob. Optim..

[64]  M. Ierapetritou,et al.  A kriging method for the solution of nonlinear programs with black‐box functions , 2007 .

[65]  Selden B. Crary,et al.  Design of Computer Experiments for Metamodel Generation , 2002 .

[66]  Lawrence X. Yu.  Pharmaceutical Quality by Design: Product and Process Development, Understanding, and Control , 2008, Pharmaceutical Research.

[67]  Scott M. LaLonde,et al.  Understanding the effects of polymer extrusion filter layering configurations using simulation-based optimization , 2010 .

[68]  H Leuenberger,et al.  New trends in the production of pharmaceutical granules: batch versus continuous processing. , 2001, European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V.