Definition of Design Spaces Using Mechanistic Models and Geometric Projections of Probability Maps

Following a model-centric strategy in the development of a manufacturing process for a new medicine empowers the simultaneous study of a large number of process parameters, which is large enough to exceed the capability of a graphic representation of the interactions across them. This work presents a discussion regarding the identification, description, and communication of multidimensional design spaces of high order. It introduces the reader to mathematical tools developed by the process systems engineering community that become relevant in the challenge to replace graphics as a means to describe and communicate a design space. Concepts like process flexibility are discussed and illustrated. The paper also introduces geometric projection as a way to capture and describe the shape of the design space in an easier form (than that of the complete mechanistic model) that can be communicated to the regulator. An assessment is presented regarding the key elements communicated by a graphical representation of ...

[1]  K. K. Hii,et al.  Catalysis in flow: Operando study of Pd catalyst speciation and leaching , 2014 .

[2]  Jérôme Mantanus,et al.  Design space approach in the optimization of the spray-drying process. , 2012, European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V.

[3]  Naseem A. Charoo,et al.  Quality by design approach for formulation development: a case study of dispersible tablets. , 2012, International journal of pharmaceutics.

[4]  John Lepore,et al.  PQLI Design Space , 2008, Journal of Pharmaceutical Innovation.

[5]  Manfred Morari,et al.  Flexibility and resiliency of process systems , 1983 .

[6]  Mengchen Liu,et al.  A survey on information visualization: recent advances and challenges , 2014, The Visual Computer.

[7]  R. Tan,et al.  Quality by Design (QbD)-Based Crystallization Process Development for the Polymorphic Drug Tolbutamide , 2011 .

[8]  Flavio Manenti,et al.  Kinetic models analysis , 2009 .

[9]  Aili Cheng,et al.  Finding Design Space and a Reliable Operating Region Using a Multivariate Bayesian Approach with Experimental Design , 2009 .

[10]  Rafiqul Gani,et al.  Active pharmaceutical ingredient (API) production involving continuous processes--a process system engineering (PSE)-assisted design framework. , 2012, European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V.

[11]  T. Tuttle,et al.  Towards a quantitative understanding of palladium metal scavenger performance: an electronic structure calculation approach. , 2014, Dalton transactions.

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

[13]  Diane J Burgess,et al.  Quality by Design approach to spray drying processing of crystalline nanosuspensions. , 2014, International journal of pharmaceutics.

[14]  Shekhar Viswanath,et al.  Model-Based Scale-up and Design Space Determination for a Batch Reactive Distillation with a Dean–Stark Trap , 2013 .

[15]  Stephanie Phillips,et al.  Final Analysis: The Use of Metal Scavengers for Recovery of Palladium Catalyst from Solution , 2010 .

[16]  Dimitris Hatziavramidis,et al.  Design Space Approach for Pharmaceutical Tablet Development , 2014 .

[17]  Pedro Hernandez-Abad,et al.  Quality by design case study: an integrated multivariate approach to drug product and process development. , 2009, International journal of pharmaceutics.

[18]  Andrew Prpich,et al.  Drug product modeling predictions for scale-up of tablet film coating - A quality by design approach , 2010, Comput. Chem. Eng..

[19]  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 .

[20]  P. S. Puri,et al.  Additive excess free energy models for predicting gas solubilities in mixed solvents , 1974 .

[21]  R. Battino,et al.  The Solubility of Oxygen and Ozone in Liquids , 1983 .

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

[23]  P. Kerkhof,et al.  Modeling chromatographic columns non-equilibrium packed-bed adsorption with non-linear adsorption isotherms. , 2004, Journal of chromatography. A.

[24]  Thomas L. Dean,et al.  Neural Networks and Neuroscience-Inspired Computer Vision , 2014, Current Biology.

[25]  Carlo Castagnoli,et al.  Application of Quality by Design Principles for the Definition of a Robust Crystallization Process for Casopitant Mesylate , 2010 .

[26]  I. Ciofini,et al.  Mechanism of the palladium-catalyzed homocoupling of arylboronic acids: key involvement of a palladium peroxo complex. , 2006, Journal of the American Chemical Society.

[27]  Eero P. Simoncelli,et al.  Metamers of the ventral stream , 2011, Nature Neuroscience.

[28]  Ignacio E. Grossmann,et al.  Optimization strategies for flexible chemical processes , 1983 .

[29]  V. D. Dimitriadis,et al.  Flexibility Analysis of Dynamic Systems , 1995 .

[30]  Cynthia A. Oksanen,et al.  Process modeling and control in drug development and manufacturing , 2010, Comput. Chem. Eng..

[31]  C. Floudas,et al.  Active constraint strategy for flexibility analysis in chemical processes , 1987 .

[32]  Ignacio E. Grossmann,et al.  Evolution of concepts and models for quantifying resiliency and flexibility of chemical processes , 2014, Comput. Chem. Eng..

[33]  Jose E. Tabora,et al.  Modeling-Based Approach Towards Quality by Design for the Ibipinabant API Step , 2012 .

[34]  K. K. Hii,et al.  Speciation of Pd(OAc)2 in ligandless Suzuki–Miyaura reactions , 2012 .