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Kinase Inhibitor Drugs

RRP $363.99

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<b>A comprehensive resource on case studies of marketed kinase drugs and promising drug trials</b> <p> Since the discovery of protein kinase activity in 1954, the field of protein kinase drug discovery has advanced dramatically. With the ongoing clinical success of the Bcr-Abl kinase inhibitor Gleevec in the treatment of chronic myelogenous leukemia and seven additional marketed kinase inhibitor drugs, researchers have compelling evidence that kinase inhibitors can be highly efficacious in the treatment of diseases caused by aberrant activity of protein kinase. Currently more than 100 protein kinase inhibitors are in clinical development. <p> In one comprehensive volume, the editors, Dr. Rongshi Li and Dr. Jeffrey Stafford, present timely and important case studies of marketed kinase drugs and several of the most advanced kinase inhibitors in clinical trials. <i>Kinase Inhibitor Drugs</i> includes: <ul> <li> <p> Case studies from leading investigators and experts in the field that provide firsthand accounts of kinase inhibitor discovery <li> <p> Current thinking on kinase structure, biochemistry, and signal transduction pathways <li> <p> Information on state-of-the-art technologies and tools such as structure-based and fragment-based drug discovery <li> <p> A lineup of clinical-phase growth factor receptor inhibitors <li> <p> Inhibitors of cell cycle kinases <li> <p> The discovery of allosteric inhibitors of MEK kinase <li> <p> Information on pharmacogenomics and its application to kinase inhibitor clinical development </ul>


Development Of Innovative Drugs Via Modeling With Matlab

RRP $352.99

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The development of innovative drugs is becoming more difficult while relying on empirical approaches. This inspired all major pharmaceutical companies to pursue alternative model-based paradigms. The key question is: How to find innovative compounds and, subsequently, appropriate dosage regimens? Written from the industry perspective and based on many years of experience, this book offers: - Concepts for creation of drug-disease models, introduced and supplemented with extensive MATLAB programs - Guidance for exploration and modification of these programs to enhance the understanding of key principles - Usage of differential equations to pharmacokinetic, pharmacodynamic and (patho-) physiologic problems thereby acknowledging their dynamic nature - A range of topics from single exponential decay to adaptive dosing, from single subject exploration to clinical trial simulation, and from empirical to mechanistic disease modeling. Students with an undergraduate mathematical background or equivalent education, interest in life sciences and skills in a high-level programming language such as MATLAB, are encouraged to engage in model-based pharmaceutical research and development.


Development Of Innovative Drugs Via Modeling With Matlab

RRP $574.99

Click on the Google Preview image above to read some pages of this book!

The development of innovative drugs is becoming more difficult while relying on empirical approaches. This inspired all major pharmaceutical companies to pursue alternative model-based paradigms. The key question is: How to find innovative compounds and, subsequently, appropriate dosage regimens?

Written from the industry perspective and based on many years of experience, this book offers:

- Concepts for creation of drug-disease models, introduced and supplemented with extensive MATLAB programs

- Guidance for exploration and modification of these programs to enhance the understanding of key principles

- Usage of differential equations to pharmacokinetic, pharmacodynamic and (patho-) physiologic problems thereby acknowledging their dynamic nature

- A range of topics from single exponential decay to adaptive dosing, from single subject exploration to clinical trial simulation, and from empirical to mechanistic disease modeling.

Students with an undergraduate mathematical background or equivalent education, interest in life sciences and skills in a high-level programming language such as MATLAB, are encouraged to engage in model-based pharmaceutical research and development.



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