Author: | Niels Bindslev | ISBN: | 9781351660570 |
Publisher: | CRC Press | Publication: | February 10, 2017 |
Imprint: | CRC Press | Language: | English |
Author: | Niels Bindslev |
ISBN: | 9781351660570 |
Publisher: | CRC Press |
Publication: | February 10, 2017 |
Imprint: | CRC Press |
Language: | English |
Drug-Acceptor Interactions: Modeling theoretical tools to test and evaluate experimental equilibrium effects suggests novel theoretical tools to test and evaluate drug interactions seen with combinatorial drug therapy. The book provides an in-depth, yet controversial, exploration of existing tools for analysis of dose-response studies at equilibrium or steady state. The book is recommended reading for post-graduate students and researchers engaged in the study of systems biology, networks, and the pharmacodynamics of natural or industrial drugs, as well as for medical clinicians interested in drug application and combinatorial drug therapy. Even people without mathematical skills will be able to follow the pros and cons of reaction schemes and their related distribution equations. Chapter 9 is a hands-on guide for software to plot, fit and analyze one’s own data.
Drug-Acceptor Interactions: Modeling theoretical tools to test and evaluate experimental equilibrium effects suggests novel theoretical tools to test and evaluate drug interactions seen with combinatorial drug therapy. The book provides an in-depth, yet controversial, exploration of existing tools for analysis of dose-response studies at equilibrium or steady state. The book is recommended reading for post-graduate students and researchers engaged in the study of systems biology, networks, and the pharmacodynamics of natural or industrial drugs, as well as for medical clinicians interested in drug application and combinatorial drug therapy. Even people without mathematical skills will be able to follow the pros and cons of reaction schemes and their related distribution equations. Chapter 9 is a hands-on guide for software to plot, fit and analyze one’s own data.