| Description |
1 online resource (465 pages) : illustrations |
|
text txt rdacontent |
|
computer c rdamedia |
|
online resource cr rdacarrier |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Front Cover -- Predictive Modeling of Pharmaceutical Unit Operations -- Copyright Page -- Contents -- List of contributors -- Predictive modeling of pharmaceutical unit operations -- Preface -- 1 Modeling of drug product manufacturing processes in the pharmaceutical industry -- 1.1 Introduction -- 1.2 Modeling techniques -- 1.2.1 First principle predictive models -- 1.2.1.1 Discrete element method -- 1.2.1.2 Computational fluid dynamics -- 1.2.1.3 Finite element method -- 1.2.1.4 Hybrid models -- 1.2.1.5 Empirical models -- 1.3 Process modeling in drug product manufacturing -- 1.3.1 Problem statement -- 1.3.2 Modeling technique selection -- 1.3.3 Model development -- 1.3.4 Model verification and validation -- References -- 2 Quality risk management for pharmaceutical manufacturing: The role of process modeling and simulations -- 2.1 Introduction -- 2.2 Quality risk management in pharmaceutical manufacturing -- 2.2.1 Managing risk to quality -- 2.2.2 Utilization of models to support quality risk management -- 2.2.2.1 Sensitivity analysis: a risk assessment tool -- 2.2.2.2 Feasibility analysis: a tool to evaluate risk mitigation strategies -- 2.3 Scientific considerations in model development for quality risk management -- 2.3.1 High-impact models -- 2.3.2 Medium-impact models -- 2.3.3 Low-impact models -- 2.4 Using process models to support quality risk management for emerging technologies -- 2.4.1 Risk assessment case studies for continuous manufacturing -- 2.4.1.1 Continuous direct compression risk assessment: a case study -- 2.4.1.2 End-to-end risk assessment: a case study -- 2.4.2 Risk mitigation case studies for continuous manufacturing -- 2.5 Conclusions -- References -- 3 Powder flow and blending -- 3.1 Critical role of the powder blending step in pharmaceutical manufacturing -- 3.2 Common challenges in powder blending. |
|
3.3 Granular mixing fundamentals -- 3.3.1 Mixing mechanisms -- 3.3.2 Common techniques of mixing powders -- 3.4 Assessment, measurement, and characterization -- 3.4.1 Assessment -- 3.4.2 Measurement -- 3.4.3 Characterization -- 3.5 Modeling techniques for powder mixing -- 3.5.1 Development and usage of computational tools -- 3.5.1.1 Techniques for modeling the underlying physics and processes -- The DEM and its application to granular mixing -- 3.5.1.2 Improvements in the efficiency of solution methods, algorithms, and compute architecture -- 3.5.1.3 Advancement in analysis techniques with commercial and open source software -- 3.5.2 Case study: creating a material model -- 3.6 Summary and outlook -- Acknowledgements -- References -- 4 Dry granulation process modeling -- 4.1 Introduction -- 4.2 Challenges in dry granulation modeling and recent progress -- 4.2.1 Roller compaction technology -- 4.2.2 Theoretical background -- 4.2.3 Common problems of roller compaction and progress -- 4.3 Modeling tools -- 4.3.1 DEM modeling -- 4.3.2 FEM modeling -- 4.3.3 Simulation technique for the roller compaction process -- 4.3.4 Requirements for roller compaction modeling -- 4.4 Experimental validation -- 4.4.1 Heterogeneity of density -- 4.4.2 Heterogeneity of roll pressure -- 4.5 Case studies of model application -- 4.5.1 Case study 1: 2D finite element modeling -- 4.5.1.1 Introduction -- 4.5.1.2 Results and discussion -- 4.5.1.3 Concluding comments -- 4.5.2 Case study 2: 3D finite element modeling -- 4.5.2.1 Introduction -- 4.5.2.2 Results and discussion -- 4.5.2.3 Concluding comments -- 4.6 Conclusions -- References -- 5 Mechanistic modeling of high-shear and twin screw mixer granulation processes -- 5.1 Introduction -- 5.1.1 QbD/Overview/challenges in high-shear granulation modeling -- 5.1.2 High-shear granulation rate processes/underlying mechanisms. |
|
5.1.2.1 Liquid distribution -- 5.1.2.2 Consolidation and growth -- 5.1.2.3 Breakage -- 5.1.3 High-shear granulation equipment -- 5.1.3.1 Vertical high-shear -- 5.1.3.2 Twin screw granulation -- 5.2 Modeling techniques for high-shear wet granulation processes -- 5.2.1 Population balance modeling -- 5.2.2 Granulation kernels -- 5.2.3 Discrete element method -- 5.2.4 Hybrid PBM-DEM techniques -- 5.2.5 Compartmental approach for high-shear wet granulation processes -- 5.2.5.1 Vertical high-shear -- 5.2.5.2 Twin screw -- 5.3 Numerical techniques -- 5.3.1 Monte Carlo solution techniques -- 5.3.2 Lumped-parameter approach for PBM -- 5.3.3 Multidimensional cell-average technique -- 5.3.4 Tensor decomposition method -- 5.4 Application of high-shear wet granulation models -- 5.4.1 Case study of parameter estimation -- 5.4.2 Case study of compartment model of high-shear granulation -- 5.4.3 Case study of PBM-DEM coupling -- 5.5 General discussion and conclusions -- References -- 6 Fluid bed granulation and drying -- 6.1 Introduction -- 6.2 Granulation modeling -- 6.2.1 Granulation conditions -- 6.2.1.1 Granulation under saturated conditions -- 6.2.1.2 Granulation under subsaturated conditions -- 6.2.2 Heat loss -- 6.2.3 Granule properties -- 6.3 Drying modeling -- 6.3.1 Microscopic models -- 6.3.2 Macroscopic models -- 6.4 FluidBeG: an integrated granulation and drying model -- 6.4.1 Model background -- 6.4.2 Case studies -- 6.4.2.1 MK-D: DOE studies and scale-up -- 6.5 Future developments -- References -- 7 Modeling of milling processes via DEM, PBM, and microhydrodynamics -- 7.1 Introduction -- 7.2 Microhydrodynamic modeling of wet media milling -- 7.3 DEM for modeling of dry milling -- 7.4 PBM for process-scale modeling of milling -- 7.4.1 Calibration of the PBM via parameter estimation (the inverse problem). |
|
7.4.2 Applications of the PBM for continuous milling -- 7.5 Multiscale modeling approaches for dry media (ball) milling -- 7.6 Case study: application of the microhydrodynamic model to preparation of drug nanosuspensions -- 7.7 Case study: application of the multiscale DEM-PBM approach to rolling ball milling -- 7.8 Concluding remarks -- Acknowledgments -- References -- 8 Modeling of powder compaction with the drucker-prager cap model -- 8.1 Introduction -- 8.2 The particulate nature of compacts and the modeling of their behavior -- 8.3 Constitutive models -- 8.3.1 Hydrostatic pressure dependence in compaction -- 8.3.2 Drucker-Prager cap (DPC) model -- 8.4 Parameter identification -- 8.4.1 Compaction simulators -- 8.4.2 Standard procedures for parameter extraction -- 8.4.3 Extrapolation to low- and high-relative densities -- 8.4.3.1 High-density extrapolation -- 8.4.3.2 Low-density extrapolation -- 8.5 Finite element modeling -- 8.5.1 Review of the technique -- 8.6 Case studies -- 8.6.1 Model validation -- 8.6.2 Excipient characterization -- References -- 9 Modeling approaches to multilayer tableting -- 9.1 Introduction -- 9.2 Models -- 9.2.1 Theories focusing on understanding layer adhesion/layer strength -- 9.2.1.1 Empirical correlations: use of mixing rules to estimate bilayer tablet strength -- 9.2.1.2 Application of fracture mechanics concepts -- 9.2.2 Theories focusing on understanding the role of material relaxation on delamination -- 9.2.3 Numerical simulation -- 9.3 Conclusions -- References -- 10 Computational modeling of pharmaceutical die filling processes -- 10.1 Introduction -- 10.2 Background of pharmaceutical die filling -- 10.2.1 Powder flow from a shoe -- 10.2.2 Powder packing inside a die -- 10.2.3 Segregation during die filling -- 10.3 Computational setup of die filling -- 10.3.1 Coupled DEM-CFD method. |
|
10.3.2 Numerical model of die filling -- 10.4 Computational analysis of die filling -- 10.4.1 Effect of air on powder flow -- 10.4.2 Suction filling -- 10.4.3 Segregation -- 10.5 Summary -- References -- 11 Modeling tablet film-coating processes -- 11.1 Introduction -- 11.2 Thermodynamic modeling -- 11.2.1 Description and motivation -- 11.2.2 Model framework -- 11.2.2.1 Similarity of tablet bed and exhaust air conditions -- 11.2.3 Model verification and application -- 11.2.3.1 Case study: immediate release film coating of Drug A tablets -- 11.2.3.2 Case study: immediate release film coating of Drug B tablets -- 11.3 Spray atomization modeling -- 11.3.1 Description and motivation -- 11.3.2 Model framework -- 11.3.2.1 Effect of pattern air on liquid breakup -- 11.3.2.2 Materials characterization -- 11.3.3 Model verification and application -- 11.3.4 Global sensitivity analysis -- 11.4 Tablet mixing modeling -- 11.4.1 Introduction -- 11.4.2 Intertablet mixing models -- 11.4.2.1 Description and motivation -- General tablet motion -- 11.4.2.2 Model frameworks -- DEM models -- Monte Carlo models -- Population balance modeling -- Renewal theory modeling -- Hybrid models and suggestions -- 11.4.2.3 Model verification and application -- 11.4.3 Intratablet mixing models -- 11.4.3.1 Description and motivation -- 11.4.3.2 Model frameworks -- DEM models -- Monte Carlo-DEM -- Probabilistic models -- 11.4.3.3 Model verification and application -- 11.5 Prospects for an integrated film-coating process model -- References -- 12 Modeling in pharmaceutical packaging -- 12.1 Introduction -- 12.2 Container WVTR of pharmaceutical packaging -- 12.2.1 Moisture permeation -- 12.2.2 Determination of WVTR -- 12.2.2.1 Single weight gain method for WVTR determination -- 12.2.2.2 Steady-state method for WVTR determination -- 12.2.3 Estimation of container WVTR. |
| Subject |
Pharmaceutical technology.
|
|
Technology, Pharmaceutical |
|
Techniques pharmaceutiques.
|
|
MEDICAL -- Pharmacology.
|
|
Pharmaceutical technology
|
| Added Author |
Pandey, Preetanshu, editor.
|
|
Bharadwaj, Rahul, editor.
|
| ISBN |
9780081001806 (electronic bk.) |
|
0081001800 (electronic bk.) |
|
9780081001806 |
|
9780081001547 |
|
0081001541 |
| Standard No. |
AU@ 000061154792 |
|
AU@ 000062515196 |
|
UKMGB 018091421 |
|
