Drug Synergism and Dose-Effect Data Analysis (eBook)

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.

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Not since this author's bestselling Manual of Pharmacologic Calculation has there been an available reference for drug data analysis. Incorporating the most relevant parts of that work, Drug Synergism and Dose-Effect Data Analysis focuses on drug combinations and all the quantitative analyses needed to analyze drug combination dose-effect data and to design experiments with two or more compounds. The book contains the statistical methods, the theory, and the computation algorithms needed to analyze single and combination drug data. Numerous examples accompany a presentation that illustrates the calculations and experimental design considerations for modern drug analysis.