Quantitative Systems Pharmacology

Quantitative Systems Pharmacology as a discipline has matured over the past decade and is being used more frequently in academia and industry; however, dedicated training programs and courses are limited. This book will provide a go-to educational reference for a broad audience with topics including...

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Korporativna značnica: SpringerLink (Online service)
Drugi avtorji: Bradshaw, Erica L. (Editor), Spilker, Mary E. (Editor)
Format: Elektronski eKnjiga
Jezik:angleščina
Izdano: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Izdaja:1st ed. 2025.
Serija:Handbook of Experimental Pharmacology, 289
Teme:
Online dostop:https://doi.org/10.1007/978-3-032-02692-7
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505 0 |a Part 1 Fundamental Modeling -- What Is QSP and Why Does It Exist A Brief History -- Breadth of Pharmacology Modeling Fundamentals of Pharmacokinetics, Pharmacodynamics, and Mechanistic Modeling -- A Framework for Quantitative Systems Pharmacology Model Execution -- Role of data in development and application of Quantitative Systems Pharmacology models -- Integrating QSP and ML to Facilitate Drug Development and Personalized Medicine -- Part 2 Model Development and Application -- Quantitative Systems Pharmacology Development and Application in Neuroscience -- Quantitative Systems Pharmacology Modeling in Immuno Oncology Hypothesis Testing, Dose Optimization, and Efficacy Prediction -- Application of Mechanistic Mathematical Modeling to Toxicology Quantitative Systems Toxicology (QST) -- The Role of Cross Institutional and Interdisciplinary Collaboration in Defining and Executing a Quantitative Systems Pharmacology Strategy -- Part 3 Current Challenges and Future Direction -- Future Directions for Quantitative Systems Pharmacology. 
520 |a Quantitative Systems Pharmacology as a discipline has matured over the past decade and is being used more frequently in academia and industry; however, dedicated training programs and courses are limited. This book will provide a go-to educational reference for a broad audience with topics including: the technology’s history, comparisons to other modeling methods and emerging opportunities to bring methods together, best practice for implementation illustrated by real-world examples, and finally a summary of where the technology is headed in the future. 
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