BookShobha N. Bhattachar, John S. Morrison, Daniel R. Mudra, David M. Bender, editors.
Summary: Tackling translational medicine with a focus on the drug discovery development-interface, this book integrates approaches and tactics from multiple disciplines, rather than just the pharmaceutical aspect of the field. The authors of each chapter address the paradox between the molecular understanding of diseases, drug discovery, and drug development. Laying out the detailed trends from various fields, different chapters are dedicated to target engagement, toxicological safety assessments, and the compelling relationship of optimizing early clinical studies with design strategies. The book also highlights the importance of balancing the three pillars: sufficient efficacy, acceptable safety and appropriate pharmacokinetics, all of which are crucial to successful efforts in discovery and development. With discussions regarding the combined approaches of molecular research, personalized medicine, pre-clinical and clinical development, as well as targeted therapies--this compendium is a flexible fit, perfect for professionals in the pharmaceutical industry and related academic fields.
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.