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Targeted Cancer Treatment in Silico Small Molecule Inhibitors and Oncolytic Viruses

Title
Targeted Cancer Treatment in Silico [electronic resource] : Small Molecule Inhibitors and Oncolytic Viruses / by Natalia L. Komarova, Dominik Wodarz.
ISBN
9781461483014
Publication
New York, NY : Springer New York : Imprint: Birkhäuser, 2014.
Physical Description
1 online resource (XV, 227 p.) 71 illus., 26 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This monograph provides the first in-depth study of how mathematical and computational approaches can be used to advance our understanding of cancer therapies and to improve treatment design and outcome. Over the past century, the search for a cancer cure has been a primary occupation of medical researchers. So far, it has led to a wide range of treatment techniques, including surgery, chemo- and radiotherapy, antiangiogenic drugs, and most recently, small molecule inhibitors and oncolytic viruses. Each treatment tends to have a certain effectiveness in a specific class of patients, but it is often unclear what exactly causes it to succeed or fail. Recent technological advances have given rise to an ever increasing pool of data and information that highlight the complexity underlying the cancers and their response to treatment. Next to experimental and clinical research, mathematical and computational approaches are becoming an indispensible tool to understand this complexity. Targeted Cancer Treatment in Silico is organized into two parts, corresponding to two types of targeted cancer treatment: small molecule inhibitors and oncolytic viruses. In each part, the authors provide a brief overview of the treatment’s biological basis and present the mathematical methods most suitable for modeling it. Additionally, they discuss how these methods can be applied to answer relevant questions about treatment mechanisms and propose modifications to treatment approaches that may potentially increase success rates. The book is intended for both the applied mathematics and experimental oncology communities, as mathematical models are becoming an increasingly important supplement to laboratory biology in the fight against cancer. Written at a level that generally requires little technical background, it will be a valuable resource for scientists and graduate students alike, and can also serve as an upper-division undergraduate or graduate textbook.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
September 26, 2018
Series
Modeling and simulation in science, engineering & technology.
Modeling and Simulation in Science, Engineering and Technology,
Contents
Background and Scope of the Book
Part I Treatment of Cancer with Small Molecule Inhibitors
An Introduction to Small Molecule Inhibitors and Chronic Myeloid Leukemia
Basic Dynamics of Chronic Myeloid Leukemia During Imatinib Treatment
Stochastic Modeling of Cellular Growth, Treatment, and Resistance Generation
Evolutionary Dynamics of Drug Resistant Mutants in Targeted Treatment of CML
Effect of Cellular Quiescence on the Evolution of Drug Resistance in CML
Combination Therapies: Short term versus Long term Strategies
Cross Resistance: Treatment and Modeling
Mathematical Modeling of Cyclic Cancer Treatments
Part II Treatment of Cancer with Oncolytic Viruses
Introduction to Oncolytic Viruses
Basic Dynamics of Oncolytic Viruses
Mitotic Virus Transmission and Immune Responses
Axiomatic Approaches to Oncolytic Virus Modeling
Spatial Oncolytic Virus Dynamics
Oncolytic Viruses and the Eradication of Drug-resistant Tumor Cells.
Also listed under
Wodarz, Dominik.
SpringerLink (Online service)
Citation

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