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.

Informationen zum Autor Daniel L. Young, PhD the Director of Computational Biosciences at Theranos Inc., where he leads the development of systems biology approaches to advance and enhance 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 patent applications and one issued patent; and has contributed to over seventy publications. Klappentext 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. Zusammenfassung 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. Inhaltsverzeichnis Part I: Introduction to Systems Biology Approach. Chapter 1. Introduction to systems biology in drug discovery and development. 1.1 Introduction. Chapter 2. Methods for In Silico Biology: Model Construction and Analysis. 2.1 Introduction. 2.2 Model building. 2.3 Parameter estimation. 2.4. Model analysis. 2.5 Conclusions. Chapter 3. Methods in In Silico Biology: Modeling Feedback Dynamics in Pathways. 3.1 Introduction. 3.2 Statistical modeling. 3.3 Mathematical modeling. 3.4 Feedback and feedforward. 3.5 Conclusions. Chapter 4. Simulation of Population Variability in Pharmacokinetics. 4.1 Introduction. 4.2 PBPK modeling. 4.3 Simulation of pharmacokinetic variability. 4.4 Conclusions and future directions. Part II: Applications to Drug Discovery. Chapter 5. Applications of Systems Biology Approaches to Target Identification and Validation in Drug Discovery. 5.1 Introduction. 5.2 Typical drug discovery paradigm. 5.3 Integrated drug discovery. 5.4 Drivers of the disease phenotype: clinical endpoints and hypotheses. 5.5 Extracellular disease drivers: mechanistic biotherapeutic models. 5.6 Relevant cell models for clinical endpoints. 5.7 Intracellular disease drivers: signaling pathway quantification. 5.8 Target selection: dynamic pathway mo...

Klappentext

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.

Inhalt

Part I: Introduction to Systems Biology Approach. Chapter 1. Introduction to systems biology in drug discovery and development.
1.1 Introduction.

Chapter 2. Methods for In Silico Biology: Model Construction and Analysis.
2.1 Introduction.
2.2 Model building.
2.3 Parameter estimation.
2.4. Model analysis.
2.5 Conclusions.

Chapter 3. Methods in In Silico Biology: Modeling Feedback Dynamics in Pathways.
3.1 Introduction.
3.2 Statistical modeling.
3.3 Mathematical modeling.
3.4 Feedback and feedforward.
3.5 Conclusions.

Chapter 4. Simulation of Population Variability in Pharmacokinetics.
4.1 Introduction.
4.2 PBPK modeling.
4.3 Simulation of pharmacokinetic variability.
4.4 Conclusions and future directions.

Part II: Applications to Drug Discovery.

Chapter 5. Applications of Systems Biology Approaches to Target Identification and Validation in Drug Discovery.

5.1 Introduction.
5.2 Typical drug discovery paradigm.
5.3 Integrated drug discovery.
5.4 Drivers of the disease phenotype: clinical endpoints and hypotheses.
5.5 Extracellular disease drivers: mechanistic biotherapeutic models.
5.6 Relevant cell models for clinical endpoints.
5.7 Intracellular disease drivers: signaling pathway quantification.
5.8 Target selection: dynamic pathway modeling.
5.9 Conclusions.

Chapter 6. Lead Identification and Optimization.
6.1 Introduction.
6.2 The systems biology toolkit.
6.3 Conclusions.

Chapter 7. The role of core biological motifs in dose-response modeling: an example with switch-like circuits.
7.1 Introduction: systems perspective in drug discovery.
7.2 Systems biology and toxicology.
7.3 Mechanistic/computational concepts in a molecular/cellular context.
7.4 Response motifs in cell signaling and their role in dose response.
7.5 Discussion and conclusions.

Chapter 8. Mechanism Based Pharmacokinetic-Pharmacodynamic Modeling During Discovery and Early Development.
8.1 Introduction.
8.2 Challenges in drug discovery and development: the need to bring together PK and PD.
8.3 Methodological aspects and concepts.
8.4 Application during lead optimization.
8.5 Application during clinical candidate selection.
8.6 Entry into human (EIH) preparation and translational PK/PD modeling.
8.7 PK/PD for…