Exposure-Response Modeling: A Comprehensive Guide to Statistical Approaches and Practical Implementation

Written by renowned applied statistician Jixian Wang, this book is a treasure trove of knowledge on exposure-response modeling, covering a wide range of topics from traditional pharmacokinetic-pharmacodynamic (PKPD) modeling to innovative applications in drug development and beyond.

Explore the Latest Methods and Techniques in Exposure-Response Modeling

This book delves into advanced statistical approaches, including:

• Measurement error models for sequential modeling
• Fitting models with exposure and response driven by complex dynamics
• Survival analysis with dynamic exposure history
• Bayesian analysis and model-based Bayesian decision analysis
• Causal inference to eliminate confounding biases
• Exposure-response modeling with response-dependent dose/treatment adjustments for personalized medicine and treatment adaptation

Real-World Applications in Various Fields

The book showcases numerous examples of exposure-response modeling in:

• Experimental toxicology
• Clinical pharmacology
• Epidemiology
• Drug safety

These examples demonstrate the practical application of exposure-response modeling, helping readers to solve real-world problems and understand complex concepts.

Implementing Novel Methods with Ease

The book provides SAS and R codes, enabling readers to test and implement the approaches in their own scenarios, making it an invaluable resource for applied statisticians, modelers, researchers, and students.

This comprehensive guide not only provides a systematic treatment of concepts and methodology but also offers a wealth of information on how to implement new approaches, making it an essential read for anyone working in the field of exposure-response modeling.