Systems Biology in Drug Discovery and Development (Wiley Series on Technologies for the Pharmaceutical Industry)

"The first book to focus on comprehensive systems biology as applied to drug discovery and development Drawing on real-life examples, Systems Biology in Drug Discovery and Development presents practical applications of systems biology to the multiple phases of drug discovery and development. This book explains how the integration of knowledge from multiple sources, and the models that best represent that integration, inform the drug research processes that are most relevant to the pharmaceutical and biotechnology industries. The first book to focus on comprehensive systems biology and its applications in drug discovery and development, it offers comprehensive and multidisciplinary coverage of all phases of discovery and design, including target identification and validation, lead identification and optimization, and clinical trial design and execution, as well as the complementary systems approaches that make these processes more efficient. It also provides models for applying systems biology to pharmacokinetics, pharmacodynamics, and candidate biomarker identification. Introducing and explaining key methods and technical approaches to the use of comprehensive systems biology on drug development, the book addresses the challenges currently facing the pharmaceutical industry. As a result, it is essential reading for pharmaceutical and biotech scientists, pharmacologists, computational modelers, bioinformaticians, and graduate students in systems biology, pharmaceutical science, and other related fields."-- Résumé de l'éditeur SYSTEMS BIOLOGY IN DRUG DISCOVERY AND DEVELOPMENT 5 CONTENTS 7 PREFACE 13 CONTRIBUTORS 17 PART I: INTRODUCTION TO SYSTEMS BIOLOGY IN APPROACH 21 CHAPTER 1: Introduction to Systems Biology in Drug Discovery and Development 23 SYSTEMS BIOLOGY IN PHARMACOLOGY 23 REFERENCES 25 CHAPTER 2: Methods for In Silico Biology: Model Construction and Analysis 27 2.1. INTRODUCTION 27 2.2. MODEL BUILDING 28 2.3. PARAMETER ESTIMATION 41 2.4. MODEL ANALYSIS 48 2.5. CONCLUSIONS 52 REFERENCES 52 CHAPTER 3: Methods in In Silico Biology: Modeling Feedback Dynamics in Pathways 57 3.1. INTRODUCTION 57 3.2. STATISTICAL MODELING 59 3.3. MATHEMATICAL MODELING 66 3.4. FEEDBACK AND FEEDFORWARD 69 3.5. CONCLUSIONS 76 REFERENCES 76 CHAPTER 4: Simulation of Population Variability in Pharmacokinetics 79 4.1. INTRODUCTION 79 4.2. PBPK MODELING 80 4.3. SIMULATION OF PHARMACOKINETIC VARIABILITY 81 4.4. CONCLUSIONS AND FUTURE DIRECTIONS 99 REFERENCES 100 PART II: APPLICATIONS TO DRUG DISCOVERY 113 CHAPTER 5: Applications of Systems Biology Approaches to Target Identification and Validation in Drug Discovery 115 5.1. INTRODUCTION 115 5.2. TYPICAL DRUG DISCOVERY PARADIGM 117 5.3. INTEGRATED DRUG DISCOVERY 119 5.4. DRIVERS OF THE DISEASE PHENOTYPE: CLINICAL ENDPOINTS AND HYPOTHESES 120 5.5. EXTRACELLULAR DISEASE DRIVERS: MECHANISTIC BIOTHERAPEUTIC MODELS 126 5.6. RELEVANT CELL MODELS FOR CLINICAL ENDPOINTS 129 5.7. INTRACELLULAR DISEASE DRIVERS: SIGNALING PATHWAY QUANTIFICATION 130 5.8. TARGET SELECTION: DYNAMIC PATHWAY MODELING 137 5.9. CONCLUSIONS 143 REFERENCES 145 CHAPTER 6: Lead Identification and Optimization 155 6.1. INTRODUCTION 155 6.2. THE SYSTEMS BIOLOGY TOOL KIT 159 6.3. CONCLUSIONS 162 REFERENCES 163 CHAPTER 7: Role of Core Biological Motifs in Dose–Response Modeling: An Example with Switchlike Circuits 167 7.1. INTRODUCTION: SYSTEMS PERSPECTIVES IN DRUG DISCOVERY 167 7.2. SYSTEMS BIOLOGY AND TOXICOLOGY 168 7.3. MECHANISTIC AND COMPUTATIONAL CONCEPTS IN A MOLECULAR OR CELLULAR CONTEXT 171 7.4. RESPONSE MOTIFS IN CELL SIGNALING AND THEIR ROLE IN DOSE RESPONSE 172 7.5. DISCUSSION AND CONCLUSIONS 185 REFERENCES 189 CHAPTER 8: Mechanism-Based Pharmacokinetic–Pharmacodynamic Modeling During Discovery and Early Development 195 8.1. INTRODUCTION 195 8.2. CHALLENGES IN DRUG DISCOVERY AND DEVELOPMENT 196 8.3. METHODOLOGICAL ASPECTS AND CONCEPTS 199 8.4. USE OF PK–PD MODELS IN LEAD OPTIMIZATION 203 8.5. USE OF PK–PD MODELS IN CLINICAL CANDIDATE SELECTION 208 8.6. ENTRY-INTO-HUMAN PREPARATION AND TRANSLATIONAL PK–PD MODELING 209 8.7. USE OF PK–PD MODELS IN TOXICOLOGY STUDY DESIGN AND EVALUATION 209 8.8. JUSTIFICATION OF STARTING DOSE, CALCULATION OF SAFETY MARGINS, AND SUPPORT OF PHASE I DESIGN 211 8.9. PHASE I AND BEYOND 213 8.10. SUPPORT OF EARLY FORMULATION DEVELOPMENT 215 8.11. OUTLOOK AND CONCLUSIONS 216 REFERENCES 217 PART III: APPLICATIONS TO DRUG DEVELOPMENT 221 CHAPTER 9: Developing Oncology Drugs Using Virtual Patients of Vascular Tumor Diseases 223 9.1. INTRODUCTION 223 9.2. MODELING ANGIOGENESIS 225 9.3. USE OF RIGOROUS MATHEMATICAL ANALYSIS TO GAIN INSIGHT INTO DRUG DEVELOPMENT 233 9.4. USE OF ANGIOGENESIS MODELS IN THERANOSTICS 240 9.5. USE OF ANGIOGENESIS MODELS IN DRUG SALVAGE 246 9.6. SUMMARY AND CONCLUSIONS 250 REFERENCES 251 CHAPTER 10: Systems Modeling Applied to Candidate Biomarker Identification 259 10.1. INTRODUCTION 259 10.2. BIOMARKER DISCOVERY APPROACHES 265 10.3. EXAMPLES OF SYSTEMS MODELING APPROACHES FOR IDENTIFICATION OF CANDIDATE BIOMARKERS 272 10.4. CONCLUSIONS 280 REFERENCES 280 CHAPTER 11: Simulating Clinical Trials 285 11.1. INTRODUCTION 285 11.2. TYPES OF MODELS USED IN CLINICAL TRIAL DESIGN 292 11.3. SOURCES OF PRIOR INFORMATION FOR DESIGNING CLINICAL TRIALS 296 11.4. ASPECTS OF A TRIAL TO BE DESIGNED AND OPTIMIZED 297 11.5. TRIAL SIMULATION 299 11.6. OPTIMIZING DESIGNS 301 11.7. REAL-WORLD EXAMPLES 303 11.8. CONCLUSIONS 304 REFERENCES 304 PART IV: SYNERGIES WITH OTHER TECHNOLOGIES 307 CHAPTER 12: Pathway Analysis in Drug Discovery 309 12.1. INTRODUCTION: PATHWAY ANALYSIS, DYNAMIC MODELING, AND NETWORK ANALYSIS 309 12.2. SOFTWARE SYSTEMS FOR PATHWAY ANALYSIS 312 12.3. PATHWAY ANALYSIS IN THE MODERN DRUG DEVELOPMENT PIPELINE 313 12.4. CONCLUSIONS 318 REFERENCES 319 CHAPTER 13: Functional Mapping for Predicting Drug Response and Enabling Personalized Medicine 323 13.1. INTRODUCTION 324 13.2. FUNCTIONAL MAPPING 326 13.3. PREDICTIVE MODEL 331 13.4. FUTURE DIRECTIONS 335 REFERENCES 338 CHAPTER 14: Future Outlook for Systems Biology 343 14.1. INTRODUCTION 343 14.2. SYSTEM COMPLEXITY IN BIOLOGICAL SYSTEMS 344 14.3. MODELS FOR QUANTITATIVE INTEGRATION OF DATA 345 14.4. CHANGING REQUIREMENTS FOR SYSTEMS APPROACHES DURING DRUG DISCOVERY AND DEVELOPMENT 348 14.5. BETTER MODELS FOR BETTER DECISIONS 350 14.6. ADVANCING PERSONALIZED MEDICINE 354 14.7. IMPROVING CLINICAL TRIALS AND ENABLING MORE COMPLEX TREATMENT APPROACHES 357 14.8. COLLABORATION AND TRAINING FOR SYSTEMS BIOLOGISTS 360 14.9. CONCLUSIONS 362 REFERENCES 363 INDEX 369 Color plate 391 ISBN,9780470261231,(cloth),oBook,ISBN:,9781118016435,ePDF,ISBN:,9781118016411,ePub,ISBN:,9781118016428 John Wiley & Sons, Inc. (US) SYSTEMS BIOLOGY IN DRUG DISCOVERY AND DEVELOPMENT......Page 5 CONTENTS......Page 7 PREFACE......Page 13 CONTRIBUTORS......Page 17 PART I: INTRODUCTION TO SYSTEMS BIOLOGY IN APPROACH......Page 21 SYSTEMS BIOLOGY IN PHARMACOLOGY......Page 23 REFERENCES......Page 25 2.1. INTRODUCTION......Page 27 2.2. MODEL BUILDING......Page 28 2.3. PARAMETER ESTIMATION......Page 41 2.4. MODEL ANALYSIS......Page 48 REFERENCES......Page 52 3.1. INTRODUCTION......Page 57 3.2. STATISTICAL MODELING......Page 59 3.3. MATHEMATICAL MODELING......Page 66 3.4. FEEDBACK AND FEEDFORWARD......Page 69 REFERENCES......Page 76 4.1. INTRODUCTION......Page 79 4.2. PBPK MODELING......Page 80 4.3. SIMULATION OF PHARMACOKINETIC VARIABILITY......Page 81 4.4. CONCLUSIONS AND FUTURE DIRECTIONS......Page 99 REFERENCES......Page 100 PART II: APPLICATIONS TO DRUG DISCOVERY......Page 113 5.1. INTRODUCTION......Page 115 5.2. TYPICAL DRUG DISCOVERY PARADIGM......Page 117 5.3. INTEGRATED DRUG DISCOVERY......Page 119 5.4. DRIVERS OF THE DISEASE PHENOTYPE: CLINICAL ENDPOINTS AND HYPOTHESES......Page 120 5.5. EXTRACELLULAR DISEASE DRIVERS: MECHANISTIC BIOTHERAPEUTIC MODELS......Page 126 5.6. RELEVANT CELL MODELS FOR CLINICAL ENDPOINTS......Page 129 5.7. INTRACELLULAR DISEASE DRIVERS: SIGNALING PATHWAY QUANTIFICATION......Page 130 5.8. TARGET SELECTION: DYNAMIC PATHWAY MODELING......Page 137 5.9. CONCLUSIONS......Page 143 REFERENCES......Page 145 6.1. INTRODUCTION......Page 155 6.2. THE SYSTEMS BIOLOGY TOOL KIT......Page 159 6.3. CONCLUSIONS......Page 162 REFERENCES......Page 163 7.1. INTRODUCTION: SYSTEMS PERSPECTIVES IN DRUG DISCOVERY......Page 167 7.2. SYSTEMS BIOLOGY AND TOXICOLOGY......Page 168 7.3. MECHANISTIC AND COMPUTATIONAL CONCEPTS IN A MOLECULAR OR CELLULAR CONTEXT......Page 171 7.4. RESPONSE MOTIFS IN CELL SIGNALING AND THEIR ROLE IN DOSE RESPONSE......Page 172 7.5. DISCUSSION AND CONCLUSIONS......Page 185 REFERENCES......Page 189 8.1. INTRODUCTION......Page 195 8.2. CHALLENGES IN DRUG DISCOVERY AND DEVELOPMENT......Page 196 8.3. METHODOLOGICAL ASPECTS AND CONCEPTS......Page 199 8.4. USE OF PK–PD MODELS IN LEAD OPTIMIZATION......Page 203 8.5. USE OF PK–PD MODELS IN CLINICAL CANDIDATE SELECTION......Page 208 8.7. USE OF PK–PD MODELS IN TOXICOLOGY STUDY DESIGN AND EVALUATION......Page 209 8.8. JUSTIFICATION OF STARTING DOSE, CALCULATION OF SAFETY MARGINS, AND SUPPORT OF PHASE I DESIGN......Page 211 8.9. PHASE I AND BEYOND......Page 213 8.10. SUPPORT OF EARLY FORMULATION DEVELOPMENT......Page 215 8.11. OUTLOOK AND CONCLUSIONS......Page 216 REFERENCES......Page 217 PART III: APPLICATIONS TO DRUG DEVELOPMENT......Page 221 9.1. INTRODUCTION......Page 223 9.2. MODELING ANGIOGENESIS......Page 225 9.3. USE OF RIGOROUS MATHEMATICAL ANALYSIS TO GAIN INSIGHT INTO DRUG DEVELOPMENT......Page 233 9.4. USE OF ANGIOGENESIS MODELS IN THERANOSTICS......Page 240 9.5. USE OF ANGIOGENESIS MODELS IN DRUG SALVAGE......Page 246 9.6. SUMMARY AND CONCLUSIONS......Page 250 REFERENCES......Page 251 10.1. INTRODUCTION......Page 259 10.2. BIOMARKER DISCOVERY APPROACHES......Page 265 10.3. EXAMPLES OF SYSTEMS MODELING APPROACHES FOR IDENTIFICATION OF CANDIDATE BIOMARKERS......Page 272 REFERENCES......Page 280 11.1. INTRODUCTION......Page 285 11.2. TYPES OF MODELS USED IN CLINICAL TRIAL DESIGN......Page 292 11.3. SOURCES OF PRIOR INFORMATION FOR DESIGNING CLINICAL TRIALS......Page 296 11.4. ASPECTS OF A TRIAL TO BE DESIGNED AND OPTIMIZED......Page 297 11.5. TRIAL SIMULATION......Page 299 11.6. OPTIMIZING DESIGNS......Page 301 11.7. REAL-WORLD EXAMPLES......Page 303 REFERENCES......Page 304 PART IV: SYNERGIES WITH OTHER TECHNOLOGIES......Page 307 12.1. INTRODUCTION: PATHWAY ANALYSIS, DYNAMIC MODELING, AND NETWORK ANALYSIS......Page 309 12.2. SOFTWARE SYSTEMS FOR PATHWAY ANALYSIS......Page 312 12.3. PATHWAY ANALYSIS IN THE MODERN DRUG DEVELOPMENT PIPELINE......Page 313 12.4. CONCLUSIONS......Page 318 REFERENCES......Page 319 CHAPTER 13: Functional Mapping for Predicting Drug Response and Enabling Personalized Medicine......Page 323 13.1. INTRODUCTION......Page 324 13.2. FUNCTIONAL MAPPING......Page 326 13.3. PREDICTIVE MODEL......Page 331 13.4. FUTURE DIRECTIONS......Page 335 REFERENCES......Page 338 14.1. INTRODUCTION......Page 343 14.2. SYSTEM COMPLEXITY IN BIOLOGICAL SYSTEMS......Page 344 14.3. MODELS FOR QUANTITATIVE INTEGRATION OF DATA......Page 345 14.4. CHANGING REQUIREMENTS FOR SYSTEMS APPROACHES DURING DRUG DISCOVERY AND DEVELOPMENT......Page 348 14.5. BETTER MODELS FOR BETTER DECISIONS......Page 350 14.6. ADVANCING PERSONALIZED MEDICINE......Page 354 14.7. IMPROVING CLINICAL TRIALS AND ENABLING MORE COMPLEX TREATMENT APPROACHES......Page 357 14.8. COLLABORATION AND TRAINING FOR SYSTEMS BIOLOGISTS......Page 360 14.9. CONCLUSIONS......Page 362 REFERENCES......Page 363 INDEX......Page 369 Color plate......Page 391

The first book to focus on comprehensive systems biology as applied to drug discovery and development

Drawing on real-life examples, Systems Biology in Drug Discovery and Development presents practical applications of systems biology to the multiple phases of drug discovery and development. This book explains how the integration of knowledge from multiple sources, and the models that best represent that integration, inform the drug research processes that are most relevant to the pharmaceutical and biotechnology industries.

The first book to focus on comprehensive systems biology and its applications in drug discovery and development, it offers comprehensive and multidisciplinary coverage of all phases of discovery and design, including target identification and validation, lead identification and optimization, and clinical trial design and execution, as well as the complementary systems approaches that make these processes more efficient. It also provides models for applying systems biology to pharmacokinetics, pharmacodynamics, and candidate biomarker identification.

Introducing and explaining key methods and technical approaches to the use of comprehensive systems biology on drug development, the book addresses the challenges currently facing the pharmaceutical industry. As a result, it is essential reading for pharmaceutical and biotech scientists, pharmacologists, computational modelers, bioinformaticians, and graduate students in systems biology, pharmaceutical science, and other related fields.

"The first book to focus on comprehensive systems biology as applied to drug discovery and development Drawing on real-life examples, Systems Biology in Drug Discovery and Development presents practical applications of systems biology to the multiple phases of drug discovery and development. This book explains how the integration of knowledge from multiple sources, and the models that best represent that integration, inform the drug research processes that are most relevant to the pharmaceutical and biotechnology industries. The first book to focus on comprehensive systems biology and its applications in drug discovery and development, it offers comprehensive and multidisciplinary coverage of all phases of discovery and design, including target identification and validation, lead identification and optimization, and clinical trial design and execution, as well as the complementary systems approaches that make these processes more efficient. It also provides models for applying systems biology to pharmacokinetics, pharmacodynamics, and candidate biomarker identification. Introducing and explaining key methods and technical approaches to the use of comprehensive systems biology on drug development, the book addresses the challenges currently facing the pharmaceutical industry. As a result, it is essential reading for pharmaceutical and biotech scientists, pharmacologists, computational modelers, bioinformaticians, and graduate students in systems biology, pharmaceutical science, and other related fields."-- Résumé de l'éditeur This is the first comprehensive systems biology book to focus on its applications in drug discovery and development. Using real-world examples, the book shows how systems biology can be used to enhance pharmaceutical research and drug development. It highlights essential components of drug discovery like target identification and validation and complementary systems approaches like text-mining, large multi-context datasets and regression modeling. It also provides models for treatment personalization and methods for applying systems biology to pharmacokinetics, pharmacodynamics, and candidate biomarker indentification. Introducing key methods and technical approaches the book addresses the challenges currently facing the drug industry This is the first comprehensive systems biology book to focus on its applications in drug discovery and development. It covers all phases of drug discovery and development, discussing their interaction with systems biology. Using real-world examples, the book shows how systems biology can enhance pharmaceutical research.