Systems Biology in Drug Discovery and Development

by Young, Daniel L.; Michelson, Seth

• ISBN13: 9780470261231
• ISBN10: 0470261234
• Edition: 1st
• Format: Hardcover
• Copyright: 2011-10-18
• Publisher: Wiley

Summary

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.

Author Biography

Daniel L. Young, Phd, is the Director of Computational Biosciences at Theranos Inc., where he leads the development of systems biology approaches to advances and entrance drug discovery and development and the optimal delivery of healthcare. He has written over twenty publications in the field of systems biology. Seth Michelson, PhD, is the Director of Nonclinical Biostatistics at Genomic Health, Inc. inventor or co-inventor for fourteen patient applications and one issued patient, and has contributed to over severity publications.

Table of Contents

Preface	p. xi
Contributors	p. xv
Introduction to Systems Biology in Approach
Introduction to Systems Biology in Drug Discovery and Development	p. 3
Systems Biology in Pharmacology	p. 3
References	p. 5
Methods for In Silico Biology: Model Construction and Analysis	p. 7
Introduction	p. 7
Model Building	p. 8
Parameter Estimation	p. 21
Model Analysis	p. 28
Conclusions	p. 32 References
Methods in In Silico Biology: Modeling Feedback Dynamics in Pathways	p. 37
Introduction	p. 37
Statistical Modeling	p. 39
Mathematical Modeling	p. 46
Feedback and Feedforward	p. 49
Conclusions	p. 56
References	p. 56
Simulation of Population Variability in Pharmacokinetics	p. 59
Introduction	p. 59
PBPK Modeling	p. 60
Simulation of Pharmacokinetic Variability	p. 61
Conclusions and Future Directions	p. 79
References	p. 80
Applications to Drug Discovery
Applications of Systems Biology Approaches to Target Identification and Validation in Drug Discovery	p. 95
Introduction	p. 95
Typical Drug Discovery Paradigm	p. 97
Integrated Drug Discovery	p. 99
Drivers of the Disease Phenotype: Clinical Endpoints and Hypotheses	p. 100
Extracellular Disease Drivers: Mechanistic Biotherapeutic Models	p. 106
Relevant Cell Models for Clinical Endpoints	p. 109
Intracellular Disease Drivers: Signaling Pathway Quantification	p. 110
Target Selection: Dynamic Pathway Modeling	p. 117
Conclusions	p. 123
References	p. 125
Lead Identification and Optimization	p. 135
Introduction	p. 135
The Systems Biology Tool Kit	p. 139
Conclusions	p. 142
References	p. 143
Role of Core Biological Motifs in Dose-Response Modeling: An Example with Switchlike Circuits	p. 147
Introduction: Systems Perspectives in Drug Discovery	p. 147
Systems Biology and Toxicology	p. 148
Mechanistic and Computational Concepts in a Molecular or Cellular Context	p. 151
Response Motifs in Cell Signaling and Their Role in Dose Response	p. 152
Discussion and Conclusions	p. 165
References	p. 169
Mechanism-Based Pharmacokinetic-Pharmacodynamic Modeling During Discovery and Early Development	p. 175
Introduction	p. 175
Challenges in Drug Discovery and Development	p. 176
Methodological Aspects and Concepts	p. 179
Use of PK-PD Models in Lead Optimization	p. 183
Use of PK-PD Models in Clinical Candidate Selection	p. 188
Entry-into-Human Preparation and Translational PK-PD Modeling	p. 189
Use of PK-PD Models in Toxicology Study Design and Evaluation	p. 189
Justification of Starting Dose, Calculation of Safety Margins, and Support of Phase I Design	p. 191
Phase I and Beyond	p. 193
Support of Early Formulation Development	p. 195
Outlook and Conclusions	p. 196
References	p. 197
Applications to Drug Development
Developing Oncology Drugs Using Virtual Patients of Vascular Tumor Diseases	p. 203
Introduction	p. 203
Modeling Angiogenesis	p. 205
Use of Rigorous Mathematical Analysis to Gain Insight into Drug Development	p. 213
Use of Angiogenesis Models in Theranostics	p. 220
Use of Angiogenesis Models in Drug Salvage	p. 226
Summary and Conclusions	p. 230
References	p. 231
Systems Modeling Applied to Candidate Biomarker Identification	p. 239
Introduction	p. 239
Biomarker Discovery Approaches	p. 245
Examples of Systems Modeling Approaches for Identification of Candidate Biomarkers	p. 252
Conclusions	p. 260
References	p. 260
Simulating Clinical Trials	p. 265
Introduction	p. 265
Types of Models Used in Clinical Trial Design	p. 272
Sources of Prior Information for Designing Clinical Trials	p. 276
Aspects of a Trial to Be Designed and Optimized	p. 277
Trial Simulation	p. 279
Optimizing Designs	p. 281
Real-World Examples	p. 283
Conclusions	p. 284
References	p. 284
Synergies with other Technologies
Pathway Analysis in Drug Discovery	p. 289
Introduction: Pathway Analysis, Dynamic Modeling, and Network Analysis	p. 289
Software Systems for Pathway Analysis	p. 292
Pathway Analysis in the Modern Drug Development Pipeline	p. 293
Conclusions	p. 298
References	p. 299
Functional Mapping for Predicting Drug Response and Enabling Personalized Medicine	p. 303
Introduction	p. 304
Functional Mapping	p. 306
Predictive Model	p. 311
Future Directions	p. 315
References	p. 318
Future Outlook for Systems Biology	p. 323
Introduction	p. 323
System Complexity in Biological Systems	p. 324
Models for Quantitative Integration of Data	p. 325
Changing Requirements for Systems Approaches During Drug Discovery and Development	p. 328
Better Models for Better Decisions	p. 330
Advancing Personalized Medicine	p. 334
Improving Clinical Trials and Enabling More Complex Treatment Approaches	p. 337
Collaboration and Training for Systems Biologists	p. 340
Conclusions	p. 342
References	p. 343
Index	p. 349
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