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An Introduction to Physical Oncology : How Mechanistic Mathematical Modeling Can Improve Cancer Therapy Outcomes.

Author: Vittorio Cristini; Eugene Koay; Zhihui Wang
Publisher: Boca Raton : CRC Press, 2016.
Series: Chapman & Hall/CRC Mathematical and Computational Biology.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Cristini, Vittorio.
An Introduction to Physical Oncology : How Mechanistic Mathematical Modeling Can Improve Cancer Therapy Outcomes.
Boca Raton : CRC Press, ©2016
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Vittorio Cristini; Eugene Koay; Zhihui Wang
ISBN: 9781315356884 1315356880
OCLC Number: 993114108
Notes: Chapter 6: Clinical Management of Pancreatic Cancer.
Description: 1 online resource (204 pages).
Contents: Cover; Half Title; Title Page; Copyright Page; Table of Contents; List of Figures ; List of Tables ; Preface ; PHYSICAL ONCOLOGY ; RESISTANCE TO CHEMOTHERAPY ; PATIENT-SPECIFIC STRATEGIES ; PHYSICAL SCIENCES-ONCOLOGY CENTERS ; TIMELINESS ; Acknowledgments ; Authors ; Contributors ; Definition of Technical Terms ; Chapter 1: What Should Be Modeled in Cancer ; 1.1 INTRODUCTION ; 1.2 CELL SIGNALING ; 1.2.1 Parameter Space Exploration ; 1.2.2 Modularity and Coarse Graining ; 1.2.3 Retroactivity, Substrate Competition, and Insulation. 1.2.4 Identification and Characterization of Common Dynamics Modules 1.2.5 Targeted Drug Design: Modeling Realistic New Applications to Defeat Cancer ; 1.3 MODELING CANCER: THE GENOTYPE-TO-PHENOTYPE CONUNDRUM ; 1.4 CONCLUSIONS ; Chapter 2: Developing More Successful Cancer Treatments with Physical Oncology ; 2.1 CHEMOTHERAPY ; 2.2 DRUG RESISTANCE ; 2.3 FORMS OF DRUG RESISTANCE AND RELEVANT MODELING STUDIES ; 2.3.1 Genetic Alteration ; 2.3.2 Efflux Pumps ; 2.3.3 Cell Cycles ; 2.3.4 Acidosis ; 2.3.5 Hypoxia ; 2.3.6 Interstitial Fluid Pressure and Electrostatic Charge. 2.3.7 Angiogenesis and Vasculature 2.4 PATIENT-SPECIFIC PHYSICAL PROPERTIES ; 2.4.1 Mass Transport in Tumors ; 2.4.2 Diffusion in Unique Tumor Microenvironments ; 2.4.3 Modeling at Multiple Scales ; 2.5 BRIEF REVIEW OF MATHEMATICAL MODELING OF CANCER TREATMENT ; 2.6 BRIEF REVIEW OF SOME PHYSICAL SCIENCES-ONCOLOGY CENTERS ; 2.7 CONCLUSIONS ; Chapter 3: Mathematical Pathology ; 3.1 BIOLOGY AND TREATMENT OF DUCTAL CARCINOMA IN SITU ; 3.2 NEED FOR MATHEMATICAL PATHOLOGY ; 3.3 MATHEMATICAL MODELING OF DCIS ; 3.3.1 Proliferative Index and Apoptotic Index ; 3.3.2 Diffusion Penetration Length. 3.4 TWO CASE STUDIES 3.4.1 Prediction of Surgical Volume ; 3.4.2 Prediction of Tumor Growth ; 3.5 APPLICATION TO LYMPHOMA GROWTH ; 3.5.1 Investigation of Tumor Heterogeneity in Drug Resistance ; 3.5.2 Implications of Diffusion Barriers and Chemotherapy Design ; 3.6 CONCLUSIONS ; Chapter 4: Mathematical Modeling of Drug Response ; 4.1 CURRENT STATE: CELLULAR, TISSUE, AND ORGAN LEVELS ; 4.2 THE NEED FOR INCORPORATION OF TISSUE-SCALE MODELING ; 4.3 MODELING CONCEPT ; 4.3.1 Modeling of Drug Delivery to Predict Cytotoxicity for MDR versus Drug- Sensitive Cell Lines In Vitro. 4.3.2 Diffusion Barriers: Vital Patient-Specific Chemotherapy Inhibitors 4.3.3 Generalized Model for Predicting Tumor Response to Drug Treatment ; 4.3.4 Application to Prediction of Drug Treatment via Nanocarriers ; 4.3.4.1 In Vivo Experiments ; 4.3.4.2 Model Predictions ; 4.4 CONCLUSIONS ; Chapter 5: Prediction of Chemotherapy Outcome in Patients ; 5.1 INTRODUCTION ; 5.2 MECHANISTIC MODEL ; 5.2.1 Model Development ; 5.2.2 Parameter Values and Model Fitting ; 5.2.3 Prediction and Validation with CT Data ; 5.3 IMPLICATIONS ; 5.4 APPLICATION TO LYMPHOMA ; 5.5 CONCLUSIONS.
Series Title: Chapman & Hall/CRC Mathematical and Computational Biology.

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"The application of concepts and tools from the physical sciences will fundamentally change our understanding of cancer. These novel insights will impact the way we diagnose malignant tumors and, Read more...

 
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