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<p>List of Contributors xv</p> <p>Preface xxi</p> <p><b>1 Introduction to Computational Pharmaceutics 1</b><br /><i>Nannan Wang, Wei Wang, Hao Zhong, and Defang Ouyang</i></p> <p>1.1 Current Pharmaceutical Research 2</p> <p>1.2 What is Computational Pharmaceutics? 5</p> <p>1.3 About This Book 7</p> <p><b>2 Opportunities and Challenges of Artificial Intelligence (AI) in Drug Delivery 10</b><br /><i>Zhuyifan Ye and Defang Ouyang</i></p> <p>2.1 Introduction 12</p> <p>2.2 Machine Learning Algorithms 14</p> <p>2.3 Applications of Machine Learning in Pharmaceutics 22</p> <p>2.4 Applications of Large-Scale Models in Drug Discovery and Development 40</p> <p>2.5 AI in the Clinic and Precision Medicine 44</p> <p>2.6 Opportunities and Challenges 45</p> <p>2.7 Summary 48</p> <p><b>3 Computational Resources in Pharmaceutics 59</b><br /><i>Jie Dong</i></p> <p>3.1 Concept and Overview of Computational Pharmaceutics 60</p> <p>3.2 Databases 62</p> <p>3.3 Computational Platforms/Web Servers 67</p> <p>3.4 Implementation Methods for Databases and Computing Platforms 79</p> <p>3.5 Summary and Outlook 81</p> <p><b>4 Computational Modeling of Dry Powder Inhalation 85</b><br /><i>Jiawei Hu, Ling Zhang, and Chuan-Yu Wu</i></p> <p>4.1 Introduction 86</p> <p>4.2 Discrete Element Methods (DEMs) 87</p> <p>4.3 Modeling of Agglomeration 89</p> <p>4.4 Modeling of De-agglomeration 91</p> <p>4.5 Modeling of Particle Dispersion in DPIs 95</p> <p>4.6 Summary and Perspectives 98</p> <p><b>5 Molecular Modeling in Drug Delivery: Polymer Protective Coatings as Case Study 104</b><br /><i>Alex Bunker and Josef Kehrein</i></p> <p>5.1 Introduction 107</p> <p>5.2 Molecular Dynamics Simulation of Polymers in Drug Delivery 125</p> <p>5.3 Conclusion 163</p> <p><b>6 3D Structural Investigation of Solid Dosage Forms 199</b><br /><i>Xianzhen Yin, Chenxi Huang, Zeying Cao, Li Wu, Tiqiao Xiao, Peter York, and Jiwen Zhang</i></p> <p>6.1 Structure of Solid Dosage Forms and Methods of Investigation -- An Overview 200</p> <p>6.2 Synchrotron Radiation X-ray Computed Microtomography 204</p> <p>6.3 3D Structure Reconstruction Based on SR-μCT 205</p> <p>6.4 3D Visualization and Quantitative Characterization 210</p> <p>6.5 Future Prospects 229</p> <p><b>7 Dissolution Mechanism of Pharmaceuticals and Formulations by Nonequilibrium Thermodynamic Modeling 235</b><br /><i>Yuanhui Ji, Zheng Zhang, Kai Ge, Raphael Paus, and Gabriele Sadowski</i></p> <p>7.1 Introduction 236</p> <p>7.2 Theoretical Basis and Models 238</p> <p>7.3 Experimental Methods 244</p> <p>7.4 Mechanism Analysis and Model Predictions 246</p> <p>7.5 Conclusions and Outlook 261</p> <p><b>8 Physiologically Based Pharmacokinetics 267</b><br /><i>Ruihu Du and Dongyang Liu</i></p> <p>8.1 Definition and History of Physiologically Based Pharmacokinetics 268</p> <p>8.2 Principles and Structures of the Physiologically Based Pharmacokinetics Model 269</p> <p>8.3 Physiologically Based Pharmacokinetics Model in Complex Situations 284</p> <p>8.4 Challenges and Perspectives of the Physiologically Based Pharmacokinetics Model 288</p> <p><b>9 Molecular Modeling in Drug Delivery 293</b><br /><i>Jiawen Wang, Yi Yu, and Youyong Li</i></p> <p>9.1 Introduction 294</p> <p>9.2 Basic Principles of Molecular Dynamic Simulation and Molecular Modeling Methods 300</p> <p>9.3 Molecular Dynamic Simulation of Drug Delivery Strategies with Nanoparticles 303</p> <p>9.4 Summary 320</p> <p><b>10 Integration of Dendrimer-Based Delivery Technologies with Computational Pharmaceutics and Their Potential in the Era of Nanomedicine 328</b><br /><i>Karnaker Reddy Tupally, Prasenjit Seal, Preeti Pandey, Rink-Jan Lohman, Sean Smith, Defang Ouyang, and Haredra Parekh</i></p> <p>10.1 Introduction 329</p> <p>10.2 Dendrimers as Drug/Gene Delivery Systems and Their Pharmaceutical Applications 331</p> <p>10.3 Computational Aspects of Dendrimer-Based Drug Delivery and Challenges 363</p> <p>10.4 Conclusions 367</p> <p><b>11 Artificial Intelligence and Computational Modeling in Orally Inhaled Drugs 379</b><br /><i>Renjie Li, Hao Miao, Xudong Zhou, Ruiping Zou, and Zhenbo Tong</i></p> <p>11.1 Overview 381</p> <p>11.2 Chronic Respiratory Diseases and Inhaled Therapy 381</p> <p>11.3 Introduction of Computational Methods 383</p> <p>11.4 Applications in R&D of Inhalers and Drug Formulations 386</p> <p>11.5 Applications in the Evaluation of Inhaled Drug Efficacy 389</p> <p>11.6 Applications in the Management of Chronic Respiratory Diseases 394</p> <p>11.7 Challenges and Future 397</p> <p>11.8 Conclusions 399</p> <p><b>12 Digital Formulation Development Using 3D Printing Technology: AI and Modeling 408</b><br /><i>Timothy Tracy, Lei Wu, Senping Cheng, and Xiaoling Li</i></p> <p>12.1 Introduction 409</p> <p>12.2 3D Printing Methods in the Formulation of Pharmaceuticals 411</p> <p>12.3 Novel Tablet Structures Possible with 3D Printing 415</p> <p>12.4 Artificial Intelligence in Formulation Development Using 3D Printing 416</p> <p>12.5 3D Printing Formulation by Design 430</p> <p>12.6 Summary 432</p> <p><b>13 A Review on Research and Application of Expert Systems on Drug Formulation and Process Design 437</b><br /><i>Ruofei Du and Yu Zhang</i></p> <p>13.1 Introduction 437</p> <p>13.2 The Structure of ES 438</p> <p>13.3 Applications 449</p> <p>13.4 Discussions 466</p> <p><b>14 Application of PBPK Modeling in Formulation Development 474</b><br /><i>Bo Liu and Xue Li</i></p> <p>14.1 Introduction 475</p> <p>14.2 Pharmacokinetic (PK) Software for Modeling 476</p> <p>14.3 Modeling Mechanisms for Different Types of Dosage Forms 479</p> <p>14.4 Summary and Conclusion 489</p> <p><b>15 Multiscale Models for Tablet Manufacturing Process Development 493</b><br /><i>Xizhong Chen, Kai Liu, LiGe Wang, Liang Li, and Zheng-Hong Luo</i></p> <p>15.1 Introduction 494</p> <p>15.2 Tablet Manufacturing 496</p> <p>15.3 Computational Modeling 499</p> <p>15.4 Case Studies 506</p> <p>15.5 Summary and Outlook 513</p> <p><b>16 Machine Learning as a Part of Pharmaceutical Product Development 517</b><br /><i>Johan Botker, Jukka Rantanen, and Anders O. Madsen</i></p> <p>16.1 Introduction 518</p> <p>16.2 Pharmaceutical Materials Science 519</p> <p>16.3 Product Design 524</p> <p>16.4 Processing of Pharmaceuticals 526</p> <p>16.5 Analytical Chemistry in a Pharmaceutical Setting 529</p> <p>16.6 Concluding Remarks 530</p> <p><b>17 Big Data Analysis of Patents and Their Applications in Biomedical Research and Development 533</b><br /><i>Jiaqi Xu, Jialu Yuan, Hong Cai, and Yuanjia Hu</i></p> <p>17.1 Introduction 534</p> <p>17.2 Patent Landscape Analysis 536</p> <p>17.3 Mining Chemical Information from Patents 540</p> <p>17.4 Mining Biological Information from Patents 546</p> <p>17.5 Mining Pharmaceutics Information from Patents 553</p> <p>17.6 Practical Operations and Related Issues 556</p> <p>17.7 Outlook 568</p> <p><b>18 Model-informed Drug Development (MIDD) Regarding Regulatory Requirements and Thinking 574</b><br /><i>Wei Wang, Yuzhu Wang, and Defang Ouyang</i></p> <p>18.1 Driving Forces Toward MIDD 576</p> <p>18.2 Regulatory Guidance on Modeling Methods 578</p> <p>18.3 Evolving Thinking on MIDD 582</p> <p>18.4 The Advancement of Pharmacometrics in China 588</p> <p>18.5 Summary 589</p> <p>References 589</p> <p>Index 593</p>

<p><b>Edited by </b> <p><b>Dr. Defang Ouyang</b> is Associate Professor, Institute of Chinese Medical Sciences and Faculty of Health Sciences, University of Macau. With more than twenty years of experience in academia and industry, Dr. Ouyang has pioneered the integration of multi-scale modeling, Artificial Intelligence, and Big Data techniques in the field of drug delivery. He developed six approved patents and published two books, several book chapters, and over 100 refereed journal papers.

<p><b>Provides an extensive and up-to-date overview of the theory and application of computational pharmaceutics in the drug development process</b> <p><i>Exploring Computational Pharmaceutics - AI and Modeling in Pharma 4.0</i> introduces a variety of current and emerging computational techniques for pharmaceutical research. Bringing together experts from academia, industry, and regulatory agencies, this edited volume also explores the current state, key challenges, and future outlook of computational pharmaceutics while encouraging development across all sectors of the field. Throughout the text, the authors discuss a wide range of essential topics, from molecular modeling and process simulation to intelligent manufacturing and quantitative pharmacology. <p>Building upon <i>Exploring Computational Pharmaceutics - AI and Modeling in Pharma 4.0</i>, this new edition provides a multi-scale perspective that reveals the physical, chemical, mathematical, and data-driven details of pre-formulation, formulation, process, and clinical studies, in addition to <i>in vivo </i>prediction in the human body and precision medicine in clinical settings. Detailed chapters address both conventional dosage forms and the application of computational technologies in advanced pharmaceutical research, such as dendrimer-based delivery systems, liposome and lipid membrane research, and inorganic nanoparticles. <p>A major contribution to the development and promotion of computational pharmaceutics, this important resource: <ul><li>Discusses the development track, achievements, and prospects of computational pharmaceutics</li> <li>Presents multidisciplinary research to help physicists, chemists, mathematicians, and computer scientists locate problems in the field of drug delivery</li> <li>Covers a wide range of technologies, including complex formulations for water-insoluble drugs, protein/peptide formulations, nanomedicine, and gene delivery systems</li> <li>Focuses on the application of cutting-edge computational technologies and intelligent manufacturing of emerging pharmaceutical technologies</li> <li>Includes a systematic overview of computational pharmaceutics and Pharma 4.0 to assist non-specialist readers</li></ul> <p>Covering introductory, advanced, and specialist topics, <i>Exploring Computational Pharmaceutics - AI and Modeling in Pharma 4.0 </i>is an invaluable resource for computational chemists, computational analysts, pharmaceutical chemists, process engineers, process managers, and pharmacologists, as well as computer scientists, medicinal chemists, clinical pharmacists, material scientists, and nanotechnology specialists working in the field.

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