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Effects of mixing in pharmaceutical product design
S16
e u r o p e a n j o u r n a l o f p h a r m a c e u t i c a l s c i e n c e s 3 4 S ( 2 0 0 8 ) S7–S24
L22
L23
Effects of mixing in pharmaceutical product design
PAT—Optimal prediction of properties by means of tailormade modelling of spectroscopic/chromatographic profiles
Jerzy Bałdyga Faculty of Chemical and Process Engineering, Warsaw University of Technology, Poland
Olav M. Kvalheim 1,∗ , Reidar Arneberg 2 , Brian Marquardt 3 1
Department of Chemistry, University of Bergen, Norway Pattern Recognition Systems AS, Bergen, Norway 3 Center for Process Analytical Chemistry (CPAC), University of Washington, Seattle, USA 2
The product design procedure consists of defining needs that the product should fulfil, generating and selecting ideas to meet these needs, defining product properties and finally deciding how the product should be manufactured in commercial quantities. In this presentation, the author is interested in the last problem, namely in such process design and choice of equipment that matches the desired product specification. Solution of these problems requires rather complex procedures that are based on inverse analysis and scale up methods that include both detailed mathematical modelling and experiments. In what follows two fundamental product design problems are considered: improving reaction selectivity by clever mixing and designing mixing strategy to control particle size distribution (PSD). In the pharmaceutical industry, many chemical reactions leading to desirable intermediate and end-products are accompanied by side reactions producing undesired byproducts. By-products decrease reaction yield and complicate product separation. To improve selectivity, the competition between reactions can be enhanced, one can, for example, either add a homogeneous catalyst that increases the rate of desired reaction or an inhibitor that decreases the rate of side reactions. This creates again separation problems, moreover, when the rate constant of desired reaction is increased, its rate becomes controlled by mixing, rather than by the reaction kinetics. Competition is then between the mixing-controlled desired reaction and the slower side-reactions. The problem of reactive mixing arises, and it is solved in this work using hierarchy of methods, starting from a simple time scale analysis, using then mechanistic models, and finally implementing mechanistic models to CFD. Examples of CFD simulations and related experimental data for test reactions are presented to illustrate proposed methodology. In many pharmaceutical applications, particles with strictly defined size distribution (PSD) and morphology are required. For example, efficient systemic delivery using inhalation requires aerosol particles to be designed with an aerodynamic diameter between 1 and 5 m to maximize deposition in the alveolar region, whereas the aerodynamic diameter depends on the geometric particle size and the particle dynamic shape factor. At this point, the aim of presentation is to show methods for prediction of PSD when supercritical fluids are used to precipitate particles; more traditional processes (milling, traditional crystallization and precipitation) are briefly considered for comparison as well. doi:10.1016/j.ejps.2008.02.037
On-line prediction of properties is crucial for surviving in today’s competitive market with tightened margins and demanding customers. In this lecture, we present approaches to improve on-line predictions both in the modelling step and by selecting appropriate analyzers. The manufacturer can utilize the improved prediction to reduce raw material cost in the production process. doi:10.1016/j.ejps.2008.02.038 L24 Co-crystals: An emerging approach to improving properties of pharmaceutical solids ¨ aki, ¨ Sabiruddin Mirza ∗ , Jyrki Heinam Inna Miroshnyk, Jouko Yliruusi Division of Pharmaceutical Technology, Faculty of Pharmacy, University of Helsinki, Finland The ability to deliver the drug to the patient in a safe, efficacious and cost-effective manner depends largely on the physicochemical properties of the active pharmaceutical ingredient (API) in the solid state. This provides a significant driving force for inventing new approaches to designing pharmaceutical solid materials with specific physicochemical properties. In the last years, crystal engineering of APIs through co-crystallization has gained an increased interest as a means of optimizing the physical properties and/or stability of solid dosage forms (Almarsson et al., 2004). Co-crystals can be defined as crystalline complexes of two or more neutral molecular constituents bound together in the crystal lattice through non-covalent interactions (primarily hydrogen bonding). The formation of pharmaceutical co-crystals involves incorporation of a given API with another pharmaceutically acceptable molecule in the crystal lattice. The resulting multi-component crystalline phase will posses a distinct physicochemical profile as compared to that of the parent API. Potentially enhanced solubility and thus bioavailability and/or physical stability of APIs via co-crystallization (Blagden et al., 2007) are of utmost practical interest. Cocrystallization can be performed, for instance, by evaporation of a heteromeric solution, co-grinding the components, sublimation, growth from the melt or slurry technique. The key benefits associated with co-crystallization approach to modifying properties of pharmaceutical solids are the theoretical capability of all types of drug molecules, including weakly ionizable and non-ionizable, to form co-crystals, and the existence of numerous, potential counter-molecules, including food additives, preservatives, pharmaceutical excipients as well as other APIs, for co-crystal synthesis (Vishweshwar et al.,
e u r o p e a n j o u r n a l o f p h a r m a c e u t i c a l s c i e n c e s 3 4 S ( 2 0 0 8 ) S7–S24
L22
L23
Effects of mixing in pharmaceutical product design
PAT—Optimal prediction of properties by means of tailormade modelling of spectroscopic/chromatographic profiles
Jerzy Bałdyga Faculty of Chemical and Process Engineering, Warsaw University of Technology, Poland
Olav M. Kvalheim 1,∗ , Reidar Arneberg 2 , Brian Marquardt 3 1
Department of Chemistry, University of Bergen, Norway Pattern Recognition Systems AS, Bergen, Norway 3 Center for Process Analytical Chemistry (CPAC), University of Washington, Seattle, USA 2
The product design procedure consists of defining needs that the product should fulfil, generating and selecting ideas to meet these needs, defining product properties and finally deciding how the product should be manufactured in commercial quantities. In this presentation, the author is interested in the last problem, namely in such process design and choice of equipment that matches the desired product specification. Solution of these problems requires rather complex procedures that are based on inverse analysis and scale up methods that include both detailed mathematical modelling and experiments. In what follows two fundamental product design problems are considered: improving reaction selectivity by clever mixing and designing mixing strategy to control particle size distribution (PSD). In the pharmaceutical industry, many chemical reactions leading to desirable intermediate and end-products are accompanied by side reactions producing undesired byproducts. By-products decrease reaction yield and complicate product separation. To improve selectivity, the competition between reactions can be enhanced, one can, for example, either add a homogeneous catalyst that increases the rate of desired reaction or an inhibitor that decreases the rate of side reactions. This creates again separation problems, moreover, when the rate constant of desired reaction is increased, its rate becomes controlled by mixing, rather than by the reaction kinetics. Competition is then between the mixing-controlled desired reaction and the slower side-reactions. The problem of reactive mixing arises, and it is solved in this work using hierarchy of methods, starting from a simple time scale analysis, using then mechanistic models, and finally implementing mechanistic models to CFD. Examples of CFD simulations and related experimental data for test reactions are presented to illustrate proposed methodology. In many pharmaceutical applications, particles with strictly defined size distribution (PSD) and morphology are required. For example, efficient systemic delivery using inhalation requires aerosol particles to be designed with an aerodynamic diameter between 1 and 5 m to maximize deposition in the alveolar region, whereas the aerodynamic diameter depends on the geometric particle size and the particle dynamic shape factor. At this point, the aim of presentation is to show methods for prediction of PSD when supercritical fluids are used to precipitate particles; more traditional processes (milling, traditional crystallization and precipitation) are briefly considered for comparison as well. doi:10.1016/j.ejps.2008.02.037
On-line prediction of properties is crucial for surviving in today’s competitive market with tightened margins and demanding customers. In this lecture, we present approaches to improve on-line predictions both in the modelling step and by selecting appropriate analyzers. The manufacturer can utilize the improved prediction to reduce raw material cost in the production process. doi:10.1016/j.ejps.2008.02.038 L24 Co-crystals: An emerging approach to improving properties of pharmaceutical solids ¨ aki, ¨ Sabiruddin Mirza ∗ , Jyrki Heinam Inna Miroshnyk, Jouko Yliruusi Division of Pharmaceutical Technology, Faculty of Pharmacy, University of Helsinki, Finland The ability to deliver the drug to the patient in a safe, efficacious and cost-effective manner depends largely on the physicochemical properties of the active pharmaceutical ingredient (API) in the solid state. This provides a significant driving force for inventing new approaches to designing pharmaceutical solid materials with specific physicochemical properties. In the last years, crystal engineering of APIs through co-crystallization has gained an increased interest as a means of optimizing the physical properties and/or stability of solid dosage forms (Almarsson et al., 2004). Co-crystals can be defined as crystalline complexes of two or more neutral molecular constituents bound together in the crystal lattice through non-covalent interactions (primarily hydrogen bonding). The formation of pharmaceutical co-crystals involves incorporation of a given API with another pharmaceutically acceptable molecule in the crystal lattice. The resulting multi-component crystalline phase will posses a distinct physicochemical profile as compared to that of the parent API. Potentially enhanced solubility and thus bioavailability and/or physical stability of APIs via co-crystallization (Blagden et al., 2007) are of utmost practical interest. Cocrystallization can be performed, for instance, by evaporation of a heteromeric solution, co-grinding the components, sublimation, growth from the melt or slurry technique. The key benefits associated with co-crystallization approach to modifying properties of pharmaceutical solids are the theoretical capability of all types of drug molecules, including weakly ionizable and non-ionizable, to form co-crystals, and the existence of numerous, potential counter-molecules, including food additives, preservatives, pharmaceutical excipients as well as other APIs, for co-crystal synthesis (Vishweshwar et al.,