Not since this author's bestselling Manual of Pharmacologic Calculation-long out of print-has there been a reference available for drug data analysis, and even that work did not deal with drug combinations. Although pharmacologists and most other scientists know what synergism is, mainstream textbooks tend to neglect it as a quantitative topic. Few researchers are familiar with the quantitative methodology needed to differentiate synergistic responses from the simply additive responses expected from drug combinations or a single drug's interaction with endogenous chemicals.
In Drug Synergism and Dose-Effect Data Analysis, noted pharmacologist, mathematician, and author Ronald J. Tallarida finally brings these methods to light. Drawing on statistical theory and methods but keeping the special needs of the pharmacologist in mind, he begins his treatment with dose-response relations, the statistical analysis of the data, and the models that describe them. He also offers the only modern presentation of probit and logit analysis and provides detailed calculation methods not found in typical statistics books.
Numerous examples accompany a presentation that clearly illustrates the calculations and experimental design considerations for modern drug analysis. You'll find the conceptual background, the algorithms, and new research developments. In short, Drug Synergism and Dose-Effect Data Analysis has everything you need to perform, with confidence, the quantitative analysis of dose response data.
Table of Contents
Combinations of Chemicals
Linear Regression: A Further Discussion
Calculations for Combination Drug Analysis.
The Composite Additive Curve
Quantal Dose-Response Data: Probit and Logit Analysis
Analysis of Drug Combinations over a Range of Drug Ratios
Analysis of a Single Dose Combination
Different Experimental Designs
Response Surface Analysis of Drug Combinations
Nonlinear Regression Analysis
Statistical Concepts and Tests of Hypotheses
"This is a well-organized, practical guide for the analysis of drug interactions and contains the historical and statistical information necessary to choose an analysis method and understand the significance of differences between simple additivity versus drug interactions."
- Chosen among Doody's Reviews 250 Best Books of 2000!