Evaluating Synergy

Design and analyze drug combination studies with statistical precision

Identifying synergistic drug combinations requires rigorous statistical methodology to distinguish true interactions from simple additivity. Evaluating Synergy: Statistical Design and Analysis of Drug Combination Studies presents modern methods for optimally designing and analyzing combination studies in cancer, antiviral, and other therapeutic areas. Written by biostatisticians and a physician-scientist with decades of drug development experience, this book integrates statistical theory with practical pharmacology.

The book covers quantitative analysis of dose-effect data and experimental designs for two-drug, three-drug, and multi-drug combinations using systems biology pathway information. Readers gain a practical pipeline for identifying promising combinations through limited experimentation and single-drug data. Case studies demonstrate how efficient experimental design identified synergistic combinations in preclinical models that informed clinical protocols and led to meaningful patient benefit.

Readers will also find:

• Statistical theory, methods, and computational algorithms for analyzing multidrug combinations, supported by an accompanying website featuring R code and datasets
• Detailed guidance on distinguishing simple additivity from true drug interactions and interpreting their biological and clinical significance
• Experimental design approaches for validating selected combinations in both in vivo studies and early-stage clinical trials across therapeutic areas
• Applications to herbal formulation design in phytomedicine and traditional Chinese medicine using systems biology and pathway information
• Real-world examples showing how preclinical findings translated to clinical development, including a cancer trial demonstrating significant patient benefit

Designed for scientists in translational research, statisticians in drug development, and researchers in biostatistics and pharmacology, Evaluating Synergy serves as both a practical reference and an upper-graduate and graduate-level textbook. Readers need only a foundation in introductory statistics and linear regression.