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|a RS199.C63.P743 2017
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|a 615.19000000000005
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|a UAMI
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|a Pandey, Preetanshu.
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|a Predictive Modeling of Pharmaceutical Unit Operations.
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|a Kent :
|b Elsevier Science,
|c 2016.
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|a 1 online resource (465 pages)
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
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|a Print version record.
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|a 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.
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|a 1.3.2 Modeling technique selection1.3.3 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.
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|a 2.3 Scientific considerations in model development for quality risk management2.3.1 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.
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|a 3.1 Critical role of the powder blending step in pharmaceutical manufacturing3.2 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.
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|a 3.5.1.2 Improvements in the efficiency of solution methods, algorithms, and compute architecture3.5.1.3 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.
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|a 4.3.3 Simulation technique for the roller compaction process.
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|a The use of modeling and simulation tools is rapidly gaining prominence in the pharmaceutical industry covering a wide range of applications. This book focuses on modeling and simulation tools as they pertain to drug product manufacturing processes, although similar principles and tools may apply to many other areas. Modeling tools can improve fundamental process understanding and provide valuable insights into the manufacturing processes, which can result in significant process improvements and cost savings. With FDA mandating the use of Quality by Design (QbD) principles during manufacturing, reliable modeling techniques can help to alleviate the costs associated with such efforts, and be used to create in silico formulation and process design space. This book is geared toward detailing modeling techniques that are utilized for the various unit operations during drug product manufacturing. By way of examples that include case studies, various modeling principles are explained for the nonexpert end users. A discussion on the role of modeling in quality risk management for manufacturing and application of modeling for continuous manufacturing and biologics is also included. Explains the commonly used modeling and simulation tools Details the modeling of various unit operations commonly utilized in solid dosage drug product manufacturing Practical examples of the application of modeling tools through case studies Discussion of modeling techniques used for a risk-based approach to regulatory filings Explores the usage of modeling in upcoming areas such as continuous manufacturing and biologics manufacturingBullet points.
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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|a Drugs
|x Coatings.
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|a Pharmaceutical industry.
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|a Drug Industry
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|a Drugs
|x Coatings.
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|a Médicaments
|x Enrobages.
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|a Industrie pharmaceutique.
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|a Drugs
|x Coatings
|2 fast
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|a Pharmaceutical industry
|2 fast
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|a Bharadwaj, Rahul.
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|i has work:
|a Predictive modeling of pharmaceutical unit operations (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCXMqrbmgQFgRQx9GBmbgTd
|4 https://id.oclc.org/worldcat/ontology/hasWork
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776 |
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|i Print version:
|a Pandey, Preetanshu.
|t Predictive Modeling of Pharmaceutical Unit Operations.
|d Kent : Elsevier Science, ©2016
|z 9780081001547
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856 |
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|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=4697993
|z Texto completo
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|a ProQuest Ebook Central
|b EBLB
|n EBL4697993
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|a 92
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