Drug Interaction & Lethality Analysis

1. Auflage 2019
ISBN: 978-0-367-20635-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 168 Seiten, Format (B × H): 174 mm x 246 mm, Gewicht: 470 g

Reihe: Routledge Revivals

First Published in 1988, Drug Interaction and Lethality Analysis offers a well-structured insight into the relationship between the chemicals we use in everyday life and the environment. With an abundance of references and detailed statistics, this book is highly recommended for students of Pharmacology and professionals in their respective fields.

Autoren/Hrsg.

Brunden, Marshall N.

Vidmar, Thomas J.

McKean, Joseph W.

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie

Inhaltsverzeichnis

1. Early Methods Applied to Drug Combination Studies. 2. Optimal Experimental Designs – New Plans for Drug Combination Studies. 3. Design Efficiencies in the Presence of Drug Interaction. 4. A Guide to Developing Experimental Plans. 5. Tests of Hypothesis of Logistic Regression. 6. Diagnostics for Logistic Regression. 7. A Guide to the Application of Logistic Regression in Drug Combination Studies. 8. Robust Logistic Regression. 9. Estimation of the ED50 in Drug Combination Experiments. Appendix 1. Appendix 2. Appendix 3. Appendix 4. Appendix 5. Appendix 6. Appendix 7. Index.

Über Autor(innen)

Marshall N. Bruden, Ph.D., is currently Senior Biostatistician and Chairman of the Biomathematics Section, Department of Biostatistics, The Upjohn Company, Kalamazoo, Michigan. His present duties include the design and analysis of preclinical experiments in collaboration with research projects involving innovative statistical applications. During his career with the Upjohn company, he has been instrumental in the creation of the first data collection with research scientists and with special projects involving innovative statistical applications. During his career with the Upjohn company, he has been instrumental in the creation of the first data collection, analysis, and reporting system within the Department of Pathology and Toxicology. He has contributed to the creation of a number of laboratory screens and assays and in the development and application of mathematical models to various biological systems. Dr. Brunden received his Ph.D. from the university of Michigan, Ann Arbor, in Biostatistics. He is a member of The Biometric Society, The American Statistical Association, and The New York Academy of Sciences. During the course of his career, Dr. Brunden has authored and co-authored 40 papers for both written and oral presentation.

Thomas J. Vidmar, Ph.D., is currently Research Biostatistician in the Biomathematics Section, Department of Biostatistics, The Upjohn Company, Kalamazoo, Michigan. His present duties include collaboration with research scientists in the Design and analysis of experiments leading to the discovery of new and novel pharmaceuticals and new methods to deliver these drugs. Current research interests include robust statistical procedures in bioassay with both continuous and dichotomous data. Dr. Vidmar has authored and coauthored more than 25 scientific papers for both oral presentation and publication. Dr. Vidmar received his Ph.D. from Western Michigan University, Kalamazoo, in Mathematics with a Concentration in Statistics. He is a member of the American Statistical Association. The Biometric Society, and The Mathematical Association of America.

Joseph W. McKean, Ph.D., is currently Associate Professor in the Department of Mathematics and Statistics, Western Michigan University, Kalamazoo. His teaching activities have included courses in graduate and undergraduate statistics, directing doctoral student research, and numerous other department activities. Current research interests include robust statistical procedures and statistical computing. Dr. McKean received his Ph.D. from Pennsylvania State University in Statistics. He is a member of the American Statistical Association, the Biometric Society, The Mathematical Association of America, The Institute of Mathematical Statistics, and Phi Kappa Phi.