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Young D. Systems Biology in Drug Discovery and Development 2011
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The first book to focus on comprehensive systems biology as applied to drug discovery and developmentDrawing 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.
Introduction to Systems Biology Approach
Introduction to systems biology in drug discovery and development
Introduction
Methods for In Silico Biology Model Construction and Analysis
Introduction
Model building
Parameter estimation
Model analysis
Conclusions
Methods in In Silico Biology Modeling Feedback Dynamics in Pathways
Introduction
Statistical modeling
Mathematical modeling
Feedback and feedforward
Conclusions
Simulation of Population Variability in Pharmacokinetics
Introduction
PBPK modeling
Simulation of pharmacokinetic variability
Conclusions and future directions
Applications to Drug Discovery
Applications of Systems Biology Approaches to Target Identification and Validation in Drug Discovery
Introduction
Typical drug discovery paradigm
Integrated drug discovery
Drivers of the disease phenotype clinical endpoints and hypotheses
Extracellular disease drivers mechanistic biotherapeutic models
Relevant cell models for clinical endpoints
Intracellular disease drivers signaling pathway quantification
Target selection dynamic pathway modeling
Conclusions
Lead Identification and Optimization
Introduction
The systems biology toolkit
Conclusions
The role of core biological motifs in dose-response modeling an example with switch-like circuits
Introduction systems perspective in drug discovery
Systems biology and toxicology
Mechanistic/computational concepts in a molecular/cellular context
Response motifs in cell signaling and their role in dose response
Discussion and conclusions
Mechanism Based Pharmacokinetic-Pharmacodynamic Modeling During Discovery and Early Development
Introduction
Challenges in drug discovery and development the need to bring together PK and PD
Methodological aspects and concepts
Application during lead optimization
Application during clinical candidate selection
Entry into human (EIH) preparation and translational PK/PD modeling
PK/PD for toxicology study design and evaluation
Justification of starting dose, calculation of safety margins, and support of phase I design
Phase I and beyond
Support of early formulation development
Outlook and conclusions
Applications to Drug Development
Developing Oncology Drugs Using Virtual Patients of Vascular Tumor Diseases
Introduction
Modeling angiogenesis
Use of rigorous mathematical analysis for gaining insight on drug development
Use of angiogenesis models in theranostics
Use of angiogenesis models in drug salvage the virtual patient technology
Summary and conclusions
Systems Modeling Applied to Candidate Biomarker Identification
Introduction
Biomarker discovery approaches
Examples of systems modeling approaches for identification of candidate biomarkers
Conclusions
Simulating Clinical Trials
Introduction
Types of models used in clinical trial design
Sources of prior information for designing clinical trials
Aspects of a trial to be designed and optimized
Trial simulation
Optimizing designs
Real world examples
Conclusions
Synergies with other technologies
Pathway Analysis in Drug Discovery
Introduction pathway analysis, dynamic modeling, and network analysis
Software systems for pathway analysis
Pathway analysis in modern drug development pipeline
Conclusions
Functional mapping for predicting drug response and enabling personalized medicine
Introduction
Functional mapping
Predictive modeling
Future directions
Future Outlook of Systems Biology
Introduction
Systems complexity in biological systems
Models for quantitative integration of data
Changing requirements for systems approaches during drug discovery and development
Better models for better decisions
Advancing personalized medicine
Improving clinical trials and enabling more complex treatment approaches
Collaboration and training for systems biologists
Conclusions

Young D. Systems Biology in Drug Discovery and Development 2011.pdf10.37 MiB