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Table of Contents
Preface; Contents; Contributors; About the Editors; Part I: Discovery, Development and Commercialization of Drug Candidates: Overview and Issues; Chapter 1: Pharmaceutical Industry Performance; 1.1 Introduction; 1.1.1 Definitions; 1.1.2 Unmet Need; 1.1.3 NMEs and the Degree of Innovation; 1.2 Drug Discovery and Development Overview; 1.2.1 Learn and Confirm Cycle; 1.2.2 Process to Identify Safe and Effective Medicines; 1.3 How Medicines Work; 1.4 Drug Discovery Strategies: How Medicines Are Discovered; 1.5 Mechanistic Paradox and Precision Medicine; 1.6 Opportunities; References
Chapter 2: New Product Planning and the Drug Discovery-Development Interface2.1 Overview and Introduction; 2.2 Understanding the Disease State; 2.3 Customer Needs; 2.4 Does Science Matter?; 2.5 The SWOT Team or How to Look Critically at Your Program; 2.6 Those Pesky Competitors; 2.7 How to Have an RandD and Marketing Marriage Made in Heaven; 2.8 Should RandD and Marketing Collaborate Early or Late? Yes!; 2.9 RandD and Marketing Are Allies, Not Enemies; References; Part II: Druggable Targets, Discovery Technologies and Generation of Lead Molecules
Chapter 3: Target Engagement Measures in Preclinical Drug Discovery: Theory, Methods, and Case Studies3.1 Introduction; 3.2 Basic Concepts; 3.3 Target Engagement in Vivo; Box 1. Derivation of Eq. (3.5) for Irreversible Inhibitors; 3.4 Application to In Vivo Experimental Design; 3.4.1 Compound Delivery via Pump as a Means to Facilitate Target Validation; 3.4.2 Designing an Osmotic Pump Study; 3.4.3 Approaches to Measuring Target Engagement In Vivo; 3.4.4 The Relationship of TE to Pharmacodynamics; 3.4.5 Case Studies in Using TE
3.4.5.1 Application of TE in a Program Exploring Insulin-Degrading Enzyme as a Potential Target for Insulin Sensitization [70]3.4.5.2 Use of TE to Establish Clinical Candidate Performance Characteristics for Aggrecanase Inhibitors as Disease-Modifying ...; 3.5 Conclusion; References; Chapter 4: In Silico ADME Techniques Used in Early-Phase Drug Discovery; 4.1 Structure-Based In Silico Models; 4.1.1 Molecular Docking; 4.1.2 Molecular Dynamics; 4.2 Ligand-Based In Silico Models and Tools; 4.2.1 Quantitative Structure-Property Relationship (QSPR) Models; 4.2.1.1 Data Set Selection and Curation
4.2.1.2 Training Set Selection4.2.1.3 Molecular Descriptors; 4.2.1.4 QSPR Model Training/Building; 4.2.1.5 QSPR Model Evaluation; 4.2.1.6 Interpretation of Model Prediction; 4.2.2 ADME QSPR Models Used at Eli Lilly and Company; 4.2.3 Prospective Validation of ADME QSPR Models at Eli Lilly and Company; 4.2.4 Trends Between Calculated Physicochemical Properties and ADME Parameters; 4.2.5 Pharmacophore Modeling; 4.2.6 Site of Metabolism Prediction; 4.2.7 SPR/STR Knowledge Extraction Using Matched Molecular Pair Analysis; 4.3 Integrated and Iterative Use of Models in Early Drug Discovery
Chapter 2: New Product Planning and the Drug Discovery-Development Interface2.1 Overview and Introduction; 2.2 Understanding the Disease State; 2.3 Customer Needs; 2.4 Does Science Matter?; 2.5 The SWOT Team or How to Look Critically at Your Program; 2.6 Those Pesky Competitors; 2.7 How to Have an RandD and Marketing Marriage Made in Heaven; 2.8 Should RandD and Marketing Collaborate Early or Late? Yes!; 2.9 RandD and Marketing Are Allies, Not Enemies; References; Part II: Druggable Targets, Discovery Technologies and Generation of Lead Molecules
Chapter 3: Target Engagement Measures in Preclinical Drug Discovery: Theory, Methods, and Case Studies3.1 Introduction; 3.2 Basic Concepts; 3.3 Target Engagement in Vivo; Box 1. Derivation of Eq. (3.5) for Irreversible Inhibitors; 3.4 Application to In Vivo Experimental Design; 3.4.1 Compound Delivery via Pump as a Means to Facilitate Target Validation; 3.4.2 Designing an Osmotic Pump Study; 3.4.3 Approaches to Measuring Target Engagement In Vivo; 3.4.4 The Relationship of TE to Pharmacodynamics; 3.4.5 Case Studies in Using TE
3.4.5.1 Application of TE in a Program Exploring Insulin-Degrading Enzyme as a Potential Target for Insulin Sensitization [70]3.4.5.2 Use of TE to Establish Clinical Candidate Performance Characteristics for Aggrecanase Inhibitors as Disease-Modifying ...; 3.5 Conclusion; References; Chapter 4: In Silico ADME Techniques Used in Early-Phase Drug Discovery; 4.1 Structure-Based In Silico Models; 4.1.1 Molecular Docking; 4.1.2 Molecular Dynamics; 4.2 Ligand-Based In Silico Models and Tools; 4.2.1 Quantitative Structure-Property Relationship (QSPR) Models; 4.2.1.1 Data Set Selection and Curation
4.2.1.2 Training Set Selection4.2.1.3 Molecular Descriptors; 4.2.1.4 QSPR Model Training/Building; 4.2.1.5 QSPR Model Evaluation; 4.2.1.6 Interpretation of Model Prediction; 4.2.2 ADME QSPR Models Used at Eli Lilly and Company; 4.2.3 Prospective Validation of ADME QSPR Models at Eli Lilly and Company; 4.2.4 Trends Between Calculated Physicochemical Properties and ADME Parameters; 4.2.5 Pharmacophore Modeling; 4.2.6 Site of Metabolism Prediction; 4.2.7 SPR/STR Knowledge Extraction Using Matched Molecular Pair Analysis; 4.3 Integrated and Iterative Use of Models in Early Drug Discovery