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Part I Discovery, Development and Commercialization of Drug Candidates: Overview and Issues |
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1 Pharmaceutical Industry Performance |
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3 | (24) |
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3 | (6) |
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5 | (2) |
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7 | (1) |
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1.1.3 NMEs and the Degree of Innovation |
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8 | (1) |
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1.2 Drug Discovery and Development Overview |
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9 | (4) |
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1.2.1 Learn and Confirm Cycle |
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9 | (2) |
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1.2.2 Process to Identify Safe and Effective Medicines |
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11 | (2) |
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13 | (3) |
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1.4 Drug Discovery Strategies: How Medicines Are Discovered |
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16 | (4) |
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1.5 Mechanistic Paradox and Precision Medicine |
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20 | (2) |
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22 | (1) |
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23 | (4) |
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2 New Product Planning and the Drug Discovery-Development Interface |
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27 | (14) |
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2.1 Overview and Introduction |
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27 | (2) |
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2.2 Understanding the Disease State |
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29 | (1) |
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30 | (3) |
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33 | (1) |
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2.5 The SWOT Team or How to Look Critically at Your Program |
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33 | (1) |
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2.6 Those Pesky Competitors |
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34 | (1) |
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2.7 How to Have an R&D and Marketing Marriage Made in Heaven |
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35 | (2) |
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2.8 Should R&D and Marketing Collaborate Early or Late? Yes! |
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37 | (1) |
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2.9 R&D and Marketing Are Allies, Not Enemies |
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37 | (1) |
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38 | (3) |
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Part II Druggable Targets, Discovery Technologies and Generation of Lead Molecules |
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3 Target Engagement Measures in Preclinical Drug Discovery: Theory, Methods, and Case Studies |
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41 | (40) |
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41 | (1) |
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42 | (5) |
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3.3 Target Engagement in Vivo |
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47 | (5) |
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3.4 Application to In Vivo Experimental Design |
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52 | (23) |
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3.4.1 Compound Delivery via Pump as a Means to Facilitate Target Validation |
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57 | (2) |
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3.4.2 Designing an Osmotic Pump Study |
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59 | (2) |
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3.4.3 Approaches to Measuring Target Engagement In Vivo |
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61 | (2) |
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3.4.4 The Relationship of TE to Pharmacodynamics |
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63 | (3) |
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3.4.5 Case Studies in Using TE |
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66 | (9) |
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75 | (1) |
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76 | (5) |
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4 In Silico ADME Techniques Used in Early-Phase Drug Discovery |
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81 | (38) |
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4.1 Structure-Based In Silico Models |
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82 | (4) |
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83 | (2) |
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85 | (1) |
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4.2 Ligand-Based In Silico Models and Tools |
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86 | (21) |
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4.2.1 Quantitative Structure-Property Relationship (QSPR) Models |
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86 | (8) |
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4.2.2 ADME QSPR Models Used at Eli Lilly and Company |
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94 | (1) |
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4.2.3 Prospective Validation of ADME QSPR Models at Eli Lilly and Company |
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95 | (2) |
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4.2.4 Trends Between Calculated Physicochemical Properties and ADME Parameters |
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97 | (3) |
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4.2.5 Pharmacophore Modeling |
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100 | (3) |
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4.2.6 Site of Metabolism Prediction |
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103 | (1) |
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4.2.7 SPR/STR Knowledge Extraction Using Matched Molecular Pair Analysis |
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104 | (3) |
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4.3 Integrated and Iterative Use of Models in Early Drug Discovery |
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107 | (2) |
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109 | (1) |
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110 | (9) |
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5 Discover Toxicology: An Early Safety Assessment Approach |
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119 | (46) |
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119 | (1) |
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5.2 Toxicology Target Evaluation and Assessment |
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120 | (3) |
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5.3 Off-Target Assessment |
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123 | (4) |
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5.3.1 In Silico Safety Pharmacology |
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123 | (1) |
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5.3.2 Enzyme Safety Pharmacology |
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124 | (2) |
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126 | (1) |
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5.4 In Silico Preclinical Predictive Modeling |
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127 | (11) |
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5.4.1 Physical and Chemical Properties |
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127 | (2) |
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5.4.2 Structural Risk Assessment |
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129 | (1) |
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5.4.3 Similarity Analyses |
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130 | (2) |
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5.4.4 Substructural Analysis: Identification of Toxicophores |
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132 | (1) |
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5.4.5 In Silico Models for In Vitro Tox Endpoints |
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133 | (2) |
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5.4.6 In Vivo Tox Prediction |
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135 | (2) |
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137 | (1) |
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5.5 Cellular Systems: General Screening and Models of Key Target Organs |
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138 | (12) |
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139 | (1) |
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5.5.2 Focused Cell Screens |
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140 | (1) |
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5.5.3 Liver Injury Cell Models |
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141 | (1) |
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5.5.4 Gastrointestinal Injury Cell Models |
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142 | (1) |
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5.5.5 Heart Injury Cell Models |
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143 | (2) |
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5.5.6 Skeletal Muscle Injury Cell Models |
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145 | (1) |
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5.5.7 Injection Site Irritation |
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145 | (1) |
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5.5.8 Hematopoietic System and Hematopoiesis |
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146 | (2) |
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5.5.9 iPSC-Derived Cell Models |
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148 | (2) |
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5.5.10 Microphysiological Culture Systems |
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150 | (1) |
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5.6 In Vivo Biomarker Screens |
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150 | (3) |
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153 | (2) |
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5.7.1 Multiplex and High-Content Approaches |
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153 | (2) |
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5.8 Organizational Framework for Early Safety Assessment Activities |
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155 | (1) |
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156 | (1) |
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157 | (8) |
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Part III Optimizing Lead Molecules into Drug Candidates |
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6 Integrated Lead Optimization: Translational Models as We Advance Toward the Clinic |
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165 | (66) |
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166 | (2) |
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6.2 Integrated Approaches to Assess and Predict Human Clearance |
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168 | (23) |
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169 | (6) |
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6.2.2 Mechanistic Scaling |
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175 | (8) |
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6.2.3 Mechanistic Prediction of Human Clearance |
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183 | (7) |
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190 | (1) |
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6.3 Integrated Approaches to Assess Drug-Drug Interactions |
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191 | (17) |
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191 | (2) |
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6.3.2 Reversible (Direct) Inhibition |
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193 | (1) |
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6.3.3 Time-Dependent Inhibition |
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193 | (2) |
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6.3.4 Strategies for Mitigating DDI-Related Liabilities |
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195 | (2) |
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6.3.5 In Vitro Assessment of DDI Potential |
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197 | (5) |
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6.3.6 Assessing Clinical DDI Risk |
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202 | (6) |
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208 | (1) |
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6.4 Integrated Approaches to Assess Brain Penetration |
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208 | (11) |
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6.4.1 Pharmacokinetics of Brain Drug Delivery |
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209 | (3) |
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6.4.2 Drug Transporters at the BBB |
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212 | (3) |
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6.4.3 Integrated Approaches in Assessment of Brain Drug Delivery |
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215 | (3) |
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218 | (1) |
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219 | (12) |
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7 Developability Assessment of Clinical Candidates |
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231 | (36) |
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232 | (1) |
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7.2 Components of Developability Assessment |
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233 | (13) |
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7.2.1 Synthetic Complexity of Drug Substance |
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233 | (3) |
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7.2.2 Physicochemical Properties |
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236 | (3) |
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7.2.3 Solid Form Criteria for Developability |
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239 | (3) |
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7.2.4 Solid Form Selection for Absorption Enhancement |
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242 | (3) |
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7.2.5 Integrated Developability Risk Assessment and Feedback to Discovery Teams |
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245 | (1) |
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7.2.6 Clinical and Commercial Formulations |
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245 | (1) |
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7.3 Drug Product Performance |
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246 | (3) |
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7.3.1 Product Performance Criteria in the Context of PK-PD |
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246 | (1) |
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7.3.2 Solubility and In Vitro Dissolution |
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247 | (2) |
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249 | (6) |
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7.4.1 Basic Principles and Commonly Used Tools |
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249 | (3) |
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7.4.2 Absorption Parameters from Modeling |
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252 | (3) |
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7.5 Toxicology Formulation |
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255 | (1) |
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7.6 Developability Summary |
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256 | (2) |
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7.6.1 Drug Substance and Drug Product Parameters |
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256 | (1) |
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7.6.2 Patient-Centered Design Parameters |
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257 | (1) |
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7.6.3 Business Parameters |
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257 | (1) |
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7.7 Case Studies/Illustrative Hypothetical Scenarios |
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258 | (4) |
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7.7.1 mTOR Inhibitors Rapamune® (Sirolimus) and Afinitor® (Everolimus) |
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258 | (1) |
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7.7.2 BEZ-235 (PI3K/mTOR Inhibitor) |
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259 | (1) |
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7.7.3 BRAF Inhibitors (Vemurafenib: Zelboraf) |
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260 | (2) |
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262 | (1) |
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262 | (5) |
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8 Lead Optimization, Preclinical Toxicology |
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267 | (30) |
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268 | (7) |
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8.2 The LO Toxicology Workflow |
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275 | (18) |
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8.2.1 Early-Stage LO Toxicology Activities |
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275 | (3) |
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8.2.2 Mid-Stage LO Toxicology Activities |
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278 | (9) |
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8.2.3 Late-Stage LO Toxicology Activities |
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287 | (4) |
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8.2.4 Additional LO Toxicology Activities |
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291 | (2) |
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8.3 Communications with the Development Team |
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293 | (1) |
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294 | (3) |
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Part IV Early Clinical Development of Drug Candidates |
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9 Design of Clinical Studies in Early Development |
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297 | (20) |
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297 | (1) |
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9.2 Key Cross Pharmaceutical Industry Initiatives |
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298 | (8) |
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9.2.1 US Food and Drug Administration (FDA) Critical Path Initiative |
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298 | (2) |
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9.2.2 The Pharmacological Audit Trail (PhAT) |
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300 | (2) |
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9.2.3 National Institutes of Health (NIH) Bench-To-Bedside (B2B) Initiative |
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302 | (1) |
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9.2.4 Translational Medicine Paradigms |
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302 | (2) |
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9.2.5 The Biopharmaceutics Risk Assessment Roadmap (BioRAM) |
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304 | (1) |
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9.2.6 Other Related Pharmaceutical Industry Initiatives |
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305 | (1) |
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9.3 Early Development Themes to Address Better Clinical Outcomes |
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306 | (6) |
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9.3.1 Biomarker and Diagnostics Identification and Co-Development |
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306 | (2) |
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9.3.2 Early Focus on Predictive Model Development as a Key Success Factor |
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308 | (1) |
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9.3.3 Application of Early Adaptive Clinical Design Strategies |
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309 | (2) |
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9.3.4 Use of Fully Integrated Information Technology (IT) and Knowledge Management (KM) Systems as a Key Success Factor |
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311 | (1) |
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312 | (1) |
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312 | (5) |
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10 Design of Clinical Formulations in Early Development |
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317 | (24) |
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10.1 Introduction to Early Clinical Studies |
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317 | (3) |
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10.2 First-In-Human (FIH) Phase I Clinical Formulation Design |
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320 | (3) |
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10.2.1 Simplified Manufactured Dosage Forms |
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321 | (1) |
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10.2.2 Traditional Manufactured Solid Dosage Forms |
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321 | (1) |
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10.2.3 Extemporaneously Prepared Dosage Forms |
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322 | (1) |
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10.3 Understanding Modified Release Formulations in Early Clinical Studies |
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323 | (6) |
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10.3.1 General Considerations |
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323 | (2) |
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10.3.2 Ideal Drug Candidate for Modified Release Formulations |
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325 | (1) |
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10.3.3 Strategic Considerations in Modified Release Deployment |
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325 | (4) |
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10.3.4 Translation of Modified Release Options from Early to Later Development |
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329 | (1) |
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10.4 First-In-Human Case Studies |
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329 | (3) |
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10.4.1 Study A: Powder in Capsule |
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330 | (1) |
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10.4.2 Study B: Enabled Formulation |
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330 | (1) |
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10.4.3 Study C: Particle Size Evaluation |
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331 | (1) |
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10.4.4 Study D: EP-Osmotic Capsule (Adapted from Ref. 7) |
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331 | (1) |
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10.4.5 Study E: Modified Release (Adapted from Ref. 7) |
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331 | (1) |
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10.5 Formulation Design Following First-In-Human Studies |
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332 | (5) |
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10.5.1 General Considerations |
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332 | (4) |
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10.5.2 Other Specific Considerations |
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336 | (1) |
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337 | (1) |
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338 | (3) |
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11 Translational Research: Preclinical to Healthy Volunteer to Patient |
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341 | (32) |
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11.1 Introduction to Clinical Pharmacology Studies |
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341 | (6) |
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11.1.1 Preliminary Clinical Development Plan and First-In-Human Study Design |
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342 | (3) |
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11.1.2 Research Goals and Study Design of Phase 1 Clinical Pharmacology Studies |
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345 | (2) |
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11.1.3 Data Analysis and Interpretation |
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347 | (1) |
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11.2 Drug-Drug Interactions |
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347 | (1) |
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11.3 Pharmacokinetics in the Patient |
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348 | (1) |
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11.4 Biomarkers in Clinical Development |
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349 | (4) |
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11.4.1 Biomarkers of Bone Health |
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349 | (2) |
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11.4.2 Biomarkers in Inflammatory Diseases |
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351 | (2) |
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11.5 Case Study: Development of Bazedoxifene for the Prevention and/or Treatment of Postmenopausal Osteoporosis |
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353 | (5) |
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11.5.1 In Vivo Pharmacology: Effects of Bazedoxifene on Bone Repair in Monkeys and Rats |
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354 | (1) |
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11.5.2 Preclinical Pharmacokinetics |
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354 | (1) |
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11.5.3 Translation to Clinical Evidence of Efficacy |
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355 | (2) |
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11.5.4 Translation of Preclinical to Clinical Evidence of Safety |
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357 | (1) |
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358 | (1) |
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11.6 Case Study: Development of Bapineuzumab for the Treatment of Alzheimer's Disease |
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358 | (8) |
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11.6.1 In Vivo Pharmacology |
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359 | (1) |
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11.6.2 Preclinical/Clinical Comparison of Pharmacokinetics |
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360 | (1) |
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11.6.3 Preclinical/Clinical Evidence of Efficacy |
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361 | (2) |
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11.6.4 Evidence of Safety |
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363 | (2) |
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365 | (1) |
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11.6.6 Exposure-Response Analyses |
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365 | (1) |
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366 | (1) |
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366 | (1) |
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367 | (6) |
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12 Regulatory Aspects at the Drug Discovery Development Interface |
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373 | (18) |
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374 | (1) |
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12.2 US FDA Regulatory Expectations and Guidelines for a Phase 1 FIH Clinical Study |
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374 | (2) |
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12.3 The Drug Development Plan |
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376 | (1) |
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12.4 Development Target Product Profile |
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377 | (3) |
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12.5 The Investigational New Drug (IND) Application |
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380 | (7) |
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12.5.1 Pre-Investigational New Drug (PIND) Submission Meeting |
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380 | (1) |
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381 | (1) |
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381 | (4) |
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385 | (1) |
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386 | (1) |
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387 | (4) |
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Part V Evolution of the Drug Discovery/Development Paradigm |
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13 Alternate Routes of Administration |
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391 | (30) |
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13.1 Opportunities for Non-oral Routes of Administration (RoAs) |
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392 | (5) |
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13.1.1 Challenges to Oral Delivery |
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393 | (1) |
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13.1.2 The Needs of the Patient, Caregiver, and Payer in Drug Product Design |
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394 | (1) |
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13.1.3 Non-Oral Product Opportunities |
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394 | (3) |
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13.2 Selecting Alternate Routes of Administration |
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397 | (15) |
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13.2.1 Non-injectable Routes of Administration (RoAs) |
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398 | (9) |
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13.2.2 Injectable Drug Delivery |
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407 | (5) |
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13.3 Self-Administration of Therapy by Patients |
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412 | (4) |
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13.3.1 Prefilled Syringes (PFSs) |
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412 | (1) |
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413 | (1) |
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414 | (1) |
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414 | (1) |
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13.3.5 Needle-Free Injectors |
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415 | (1) |
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13.4 Vision for the Future |
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416 | (1) |
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416 | (5) |
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14 Outlook for the Future |
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421 | (28) |
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422 | (1) |
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14.2 Causes of Poor Productivity in the Pharmaceutical Industry |
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423 | (3) |
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14.2.1 Poor Drug Candidate Development "Effectiveness" |
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425 | (1) |
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14.2.2 Poor Drug Candidate Development "Efficiency" |
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425 | (1) |
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14.3 Key Challenges to Improving Productivity |
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426 | (3) |
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14.3.1 Scientific Knowledge Gaps |
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426 | (1) |
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14.3.2 Decision-Making in a Resource-Constrained and Uncertain Environment |
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427 | (1) |
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14.3.3 Incompatible Stakeholder Interests |
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428 | (1) |
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14.4 How the Productivity Problem Has typically Been Addressed |
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429 | (4) |
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14.4.1 Consolidations and Adopting "Best Practices" |
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429 | (1) |
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14.4.2 Partnerships and Collaborations |
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430 | (2) |
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14.4.3 The Results of Productivity Improvement Efforts |
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432 | (1) |
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14.5 Pathway to a More Successful Future |
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433 | (6) |
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14.5.1 Bridging Knowledge Gaps |
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434 | (1) |
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14.5.2 Improving Drug Candidate Selection |
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435 | (1) |
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14.5.3 Better Risk Assessment and Management |
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436 | (1) |
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14.5.4 Aligning Stakeholder Interests |
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437 | (2) |
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439 | (1) |
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440 | (9) |
Index |
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449 | |