Librería Servicio Médico

Author : Lackey / Roth /  Mannhold / Kubinyi / Folkers

Language: English

Finishing : Hardcover, 408 pages

ISBN : 978-3-527-33394-3

Edition Number: 2013

Author Information:

Karen Lackey is currently the founder and Chief Scientific Officer of JanAush, a drug discovery company focused on creating life-saving medicines in inflammation, oncology, and kinase and signal inhibition. She joined Hoffmann-La Roche in 2010 as Vice President and Head of Medicinal Chemistry at the Nutley, NJ (USA) site, where she was responsible for oncology, inflammation, virology and new technologies until the site closure in 2013. In her previous role, she was the Vice President of Chemistry, Molecular Discovery Research for GlaxoSmithKline. Most importantly, she played an active role in the discovery of the dual erbB2/EGFR tyrosine kinase inhibitor, lapatinib, currently marketed as Tykerb. Karen has over 85 publications and patents, principally covering oncology, inflammation, kinase inhibition, gene family molecular design and cellular signaling.

Bruce Roth is currently Vice President of Discovery Chemistry in Genentech Research and Early Development at South San Francisco (USA). Prior to joining Genentech in 2007, he was Vice President of Discovery Chemistry at the Pfizer Global Research and Development Ann Arbor site. Bruce began his career as a medicinal chemist at Warner-Lambert, Parke-Davis in 1982 and is best known as the inventor of Lipitor (atorvastatin calcium), for which he has received numerous awards, including the 2003 American Chemical Society Award for Creative Invention, the 2003 Gustavus J. Esselen Award and the 2013 Perkin Medal. In 2008 he was named one of the American Chemical Society's Heroes in Chemistry.

Description:

Edited by two renowned medicinal chemists who have pioneered the development of personalized therapies in their respective fields, this authoritative analysis of what is already possible is the first of its kind, and the only one to focus on drug development issues.

Numerous case studies from the first generation of "personalized drugs" are presented, highlighting the challenges and opportunities for pharmaceutical development. While the majority of these examples are taken from the field of cancer treatment, other key emerging areas, such as neurosciences and inflammation, are also covered.

With its careful balance of current and future approaches, this handbook is a prime knowledge source for every drug developer, and one that will remain up to date for some time to come.

From the content:
* Discovery of Predictive Biomarkers for Anticancer Drugs
* Discovery and Development of Vemurafenib
* Targeting Basal-Cell Carcinoma
* G-Quadruplexes as Therapeutic Targets in Cancer
* From Human Genetics to Drug Candidates: An Industrial Perspective on LRRK2 Inhibition as a Treatment for Parkinson's Disease
* Therapeutic Potential of Kinases in Asthma
* DNA Damage Repair Pathways and Synthetic Lethality
* Medicinal Chemistry in the Context of the Human Genome

Table Of Contents:

• List of Contributors XI
• Foreword XV
• Preface XIX
• A Personal Foreword XXI
• Acronyms XXIII
• 1 Medicinal Chemistry Approaches to Creating Targeted Medicines 1
• Bruce D. Roth and Karen Lackey
• 1.1 Introduction 1
• 1.2 Role of Medicinal Chemistry in Drug Discovery 2
• 1.3 Evolution of Molecular Design for Subsets of Patients 4
• 1.4 Combinations for Effective Therapies 6
• 1.5 Biomarkers in Targeting Patients 9
• 1.6 Emerging Field of Epigenetics 9
• 1.7 Systems Chemical Biology 10
• 1.8 Theranostics and Designing Drug Delivery Systems 12
• 1.9 Rapid Progress in Further Personalizing Medicine Expected 15
• References 18
• 2 Discovery of Predictive Biomarkers for Anticancer Drugs 21
• Richard M. Neve, Lisa D. Belmont, Richard Bourgon, Marie Evangelista, Xiaodong Huang, Maike Schmidt, Robert L. Yauch, and Jeffrey Settleman
• 2.1 Introduction 21
• 2.2 “Oncogene Addiction” as a Paradigm for Clinical Implementation of Predictive Biomarkers 24
• 2.3 Cancer Cell Lines as a Model System for Discovery of Predictive Biomarkers 28
• 2.3.1 Historical Application of Cell Lines in Cancer Research 28
• 2.3.2 Biomarker Discovery Using Cell Line Models 29
• 2.3.3 Cell Lines as Models of Human Cancer 31
• 2.3.4 Challenges and Limitations of Cell Line Models 32
• 2.4 Modeling Drug Resistance to Discover Predictive Biomarkers 33
• 2.5 Discovery of Predictive Biomarkers in the Context of Treatment Combinations 38
• 2.6 Discovery of Predictive Biomarkers for Antiangiogenic Agents 42
• 2.6.1 Challenges 43
• 2.6.2 Pathway Activity as a Predictor of Drug Efficacy 44
• 2.6.3 Predicting Inherent Resistance 45
• 2.6.4 On-Treatment Effects as a Surrogate of Drug Efficacy 45
• 2.6.5 Summary 46
• 2.7 Gene Expression Signatures as Predictive Biomarkers 47
• 2.7.1 Signature Discovery: Unsupervised Clustering 47
• 2.7.2 Diagnostic Development: Supervised Classification 48
• 2.7.3 Summary 50
• 2.8 Current Challenges in Discovering Predictive Biomarkers 51
• 2.8.1 Access to Tumor Cells Is Limited during Treatment 51
• 2.8.2 Drivers and Passengers 53
• 2.8.3 Epigenetic Regulation Adds Another Layer of Complexity 54
• 2.8.4 Many Oncoproteins and Tumor Suppressors Undergo Regulatory Posttranslational Modifications 55
• 2.9 Future Perspective 56
• References 57
• 3 Crizotinib 71
• Jean Cui, Robert S. Kania, and Martin P. Edwards
• 3.1 Introduction 71
• 3.2 Discovery of Crizotinib (PF-02341066) [40] 74
• 3.3 Kinase Selectivity of Crizotinib 77
• 3.4 Pharmacology of Crizotinib [45,46] 78
• 3.5 Human Clinical Efficacies of Crizotinib 80
• 3.6 Summary 83
• References 85
• 4 Discovery and Development of Vemurafenib: First-in-Class Inhibitor of Mutant BRAF for the Treatment of Cancer 91
• Prabha Ibrahim, Jiazhong Zhang, Chao Zhang, James Tsai, Gaston Habets, and Gideon Bollag
• 4.1 Background 91
• 4.2 Discovery and Development of Vemurafenib (PLX4032) 92
• 4.3 Pharmacology 95
• 4.4 Clinical Efficacy and Safety 96
• 4.5 Companion Diagnostic (cobas 4800) Development 96
• 4.6 Synthesis 96
• 4.6.1 Discovery Route(s) 96
• 4.6.2 Process Route 97
• 4.7 Summary 98
• References 98
• 5 Targeting Basal-Cell Carcinoma: Discovery and Development of Vismodegib (GDC-0449), a First-in-Class Inhibitor of the Hedgehog Pathway 101
• James C. Marsters Jr. and Harvey Wong
• 5.1 Introduction 101
• 5.2 Hedgehog and Basal-Cell Carcinoma 102
• 5.3 Cyclopamine as an SMO Antagonist 102
• 5.4 Small-Molecule Inhibitors of SMO 103
• 5.5 Preclinical Characterization of Vismodegib 107
• 5.5.1 Plasma Protein Binding and Blood Plasma Partitioning 107
• 5.5.2 In Vitro and Exploratory In Vivo Metabolism of Vismodegib 108
• 5.5.3 Drug–Drug Interaction Potential 109
• 5.5.4 Preclinical Pharmacokinetics 109
• 5.5.5 Predicted Human Pharmacokinetics 110
• 5.5.6 Summary 112
• 5.6 Vismodegib Clinical Experience in Phase I 112
• References 114
• 6 G-Quadruplexes as Therapeutic Targets in Cancer 117
• Stephen Neidle
• 6.1 Introduction 117
• 6.2 Quadruplex Fundamentals 117
• 6.3 Genomic Quadruplexes 119
• 6.4 Quadruplexes in Human Telomeres 120
• 6.5 Quadruplexes as Anticancer Targets – Evidence fromIn Vivo Studies 123
• 6.6 Native Quadruplex Structures 125
• 6.7 Quadruplex–Small-Molecule Structures 130
• 6.8 Developing Superior Quadruplex-Binding Ligands 130
• 6.9 Conclusions 134
• References 136
• 7 Identifying Actionable Targets in Cancer Patients 147
• David Uehling, Janet Dancey, Andrew M.K. Brown, John McPherson, and Rima Al-awar
• 7.1 Introduction and Background 147
• 7.2 Overview of Genomic Sequencing and Its Impact on the Identification of Actionable Mutations 149
• 7.3 Actionable Targets by Clinical Molecular Profiling: the OICR/PMH Experience 157
• 7.4 Some Experiences of Other Clinical Oncology Molecular Profiling Studies 163
• 7.5 Identifying Secondary and Novel Mutations through Molecular Profiling 165
• 7.6 Understanding and Targeting Resistance Mutations: a Challenge and an Opportunity for NGS 166
• 7.6.1 Identification and Treatment Strategies for Actionable Secondary Resistance Mutations 169
• 7.6.2 Toward the Identification of Actionable Primary Resistance Mutations 173
• 7.7 Concluding Remarks and Future Perspectives 175
• References 178
• 8 DNA Damage Repair Pathways and Synthetic Lethality 183
• Simon Ward
• 8.1 Introduction 183
• 8.2 DNA Damage Response 184
• 8.3 Synthetic Lethality 185
• 8.4 Lead Case Study: PARP Inhibitors 188
• 8.4.1 Introduction 188
• 8.4.2 Discovery of PARP Inhibitors 189
• 8.4.3 Clinical Development of PARP Inhibitors 190
• 8.4.4 Future for PARP Inhibitors 192
• 8.5 Additional Case Studies 194
• 8.5.1 MLH1/MSH2 194
• 8.5.2 p53-ATM 197
• 8.5.3 Chk1-DNA Repair 197
• 8.5.4 DNA-PK – mTOR 197
• 8.5.5 DNA Ligases 198
• 8.5.6 WEE1 198
• 8.5.7 APE1 198
• 8.5.8 MGMT 199
• 8.5.9 RAD51 199
• 8.6 Screening for Synthetic Lethality 199
• 8.6.1 RAS 202
• 8.6.2 VHL 202
• 8.6.3 MRN 203
• 8.7 Contextual Synthetic Lethality Screening 203
• 8.8 Cancer Stem Cells 204
• 8.9 Conclusions and Future Directions 204
• References 205
• 9 Amyloid Chemical Probes and Theranostics: Steps Toward Personalized Medicine in Neurodegenerative Diseases 211
• Maria Laura Bolognesi
• 9.1 Introduction 211
• 9.2 Amyloid Plaques as the Biomarker in AD 212
• 9.3 Detecting Amyloid Plaques in Patients: from Alois Alzheimer to Amyvid and Beyond 214
• 9.4 Same Causes, Same Imaging Agents? 218
• 9.5 Theranostics in AD 219
• 9.6 Conclusions and Perspectives 220
• References 222
• 10 From Human Genetics to Drug Candidates: An Industrial Perspective on LRRK2 Inhibition as a Treatment for Parkinson’s Disease 227
• Haitao Zhu, Huifen Chen, William Cho, Anthony A. Estrada, and Zachary K. Sweeney
• 10.1 Introduction 227
• 10.2 Biochemical Studies of LRRK2 Function 229
• 10.3 Cellular Studies of LRRK2 Function 230
• 10.4 Animal Models of LRRK2 Function 233
• 10.5 Clinical Studies of LRRK2-Associated PD and Future Prospects 234
• 10.6 Small-Molecule Inhibitors of LRRK2 236
• 10.7 Structural Models of the LRRK2 Kinase Domain 237
• 10.8 Strategies Used to Identify LRRK2 Kinase Inhibitors (Overview) 238
• 10.9 Conclusions 246
• References 247
• 11 Therapeutic Potential of Kinases in Asthma 255
• Dramane Lainé, Matthew Lucas, Francisco Lopez-Tapia, and Stephen Lynch
• 11.1 Introduction 255
• 11.2 Mitogen-Activated Protein Kinases 256
• 11.2.1 p38 257
• 11.2.2 JNK 259
• 11.2.3 ERK 260
• 11.3 Nonreceptor Protein Tyrosine Kinases 261
• 11.3.1 Syk 261
• 11.3.2 Lck 263
• 11.3.3 JAK 264
• 11.3.4 ITK 265
• 11.3.5 Btk 266
• 11.4 Receptor Tyrosine Kinases 266
• 11.4.1 EGFR 267
• 11.4.2 c-Kit 268
• 11.4.3 PDGFR 269
• 11.4.4 VEGFR 270
• 11.5 Phosphatidylinositol-3 Kinases 270
• 11.6 AGC Kinases 272
• 11.6.1 PKC 272
• 11.6.2 ROCK 273
• 11.7 IkB Kinase 275
• 11.8 Other Kinases 276
• 11.8.1 SphK 276
• 11.8.2 GSK-3b 277
• 11.9 Conclusions: Future Directions 278
• References 279
• 12 Developing Targeted PET Tracers in the Era of Personalized Medicine 289
• Sandra M. Sanabria Bohorquez, Nicholas van Bruggen, and Jan Marik
• 12.1 Imaging and Pharmacodynamics Biomarkers in Drug Development 289
• 12.2 General Considerations for Development of 11C- and 18F-labeled PET Tracers 292
• 12.3 Radiolabeling Compounds with 11C 294
• 12.3.1 Preparation of 11C and Basic Reactive Intermediates 294
• 12.3.2 11C-Methylations, Formation of 11C__X Bond (X¼O, N, S) 295
• 12.3.3 11C-Methylations, Formation of 11C__C Bond 297
• 12.3.4 Reactions with 11CO2 299
• 12.3.5 Reactions with 11CO 301
• 12.3.6 Reactions with H11 CN 303
• 12.4 Radiolabeling Compounds with 18F 304
• 12.4.1 Formation of C__18F Bond, Nucleophilic Substitutions 304
• 12.4.2 Aliphatic Nucleophilic 18F-Fluorination 306
• 12.4.3 Aromatic Nucleophilic 18F-Fluorination 309
• 12.4.4 Electrophilic 18F-Fluorination 313
• 12.4.5 Formation of 18F-Al, Si, B Bond 314
• 12.5 PET Imaging in the Clinic, Research, and Drug Development 315
• 12.5.1 PET in Oncology 315
• 12.5.2 PET Neuroimaging 317
• 12.5.3 PET in Cardiology 319
• 12.6 PET Tracer Kinetic Modeling for Quantification of Tracer Uptake 320
• 12.7 Concluding Remarks 325
• References 325
• 13 Medicinal Chemistry in the Context of the Human Genome 343
• Andreas Brunschweiger and Jonathan Hall
• 13.1 Introduction 343
• 13.2 Drugs Targeting Kinases 344
• 13.3 Drugs Targeting Phosphatases 347
• 13.4 In silico-Based Lead Discovery in the GPCR Family 348
• 13.5 Targeting Epigenetic Regulation: Histone Demethylases 350
• 13.6 Targeting Epigenetic Regulation: Histone Deacetylases 351
• 13.7 A Family-Wide Approach to Poly(ADP-Ribose) Polymerases 352
• 13.8 Future Drug Target Superfamilies: Ubiquitination and Deubiquitination 353
• 13.9 Summary and Outlook 354
• References 355
• Index 365

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