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Synopsis
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.
Tracy Ediger
With this book the author provides a mathematical background for the analysis of drug interactions. Two drugs used together may have purely additive responses if they act independently. However, in many cases the response seen when two drugs are simultaneously administered is not additive, but rather sub-additive or supra-additive (synergistic). This book contains clear explanations of terms and concepts necessary for the statistical and graphical analysis of data generated through the study of drug interactions. As a preliminary foundation, the author begins with an explanation of the isobologram and its uses. The use of dose-response curves to generate ED50 values is also demonstrated, making the book accessible to the nonpharmacologist. The author continues by describing the composite additive line, probit versus logit analysis, and the response surface approach. Throughout the book there is a strong emphasis on the use of statistics, with the final chapter completely devoted to statistics. The book is targeted primarily toward pharmacologists but may be useful for physiologists and physician-scientists as well. The introductory sections would be helpful for beginning pharmacology students, but the book as a whole contains many sections most relevant only to a person actually seeking to graph and interpret these types of data. The book is well referenced, with references at the end of each chapter and an extensive suggested reading list. A companion computer software package was being developed at the time of printing. Additionally, appendixes contain tables of numerical values necessary for the use of statistical and analytical methods described in the text, such as Chisquare values and probit transformation. 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 difference between simple additivity versus drug interactions.