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New Approaches to Drug Discovery

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Attention for Chapter 21: Modeling and Simulation of In Vivo Drug Effects
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Chapter title
Modeling and Simulation of In Vivo Drug Effects
Chapter number 21
Book title
New Approaches to Drug Discovery
Published in
Handbook of experimental pharmacology, January 2015
DOI 10.1007/164_2015_21
Pubmed ID
Book ISBNs
978-3-31-928912-0, 978-3-31-928914-4
Authors

Jörg Lippert, Rolf Burghaus, Lars Kuepfer, Bart Ploeger, Stephan Schaller, Walter Schmitt, Stefan Willmann, Lippert, Jörg, Burghaus, Rolf, Kuepfer, Lars, Ploeger, Bart, Schaller, Stephan, Schmitt, Walter, Willmann, Stefan

Abstract

The concept of a pharmacokinetics-pharmacodynamics (PK/PD) assessment of drug development candidates is well established in pharmaceutical research and development, and PK/PD modeling is common practice in all pharmaceutical companies. A recent analysis (Morgan et al., Drug Discov Today 17(9-10):419-424, 2012) revealed however that insufficient certainty in the integrity of the causal chain of fundamental pharmacological steps from drug dosing through systemic exposure, target tissue exposure, and engagement of molecular target to pharmacological response is still the major driver of failure in phase II of clinical drug development. Despite the rise of molecular biomarkers, ethical, scientific, and practical constraints very often still prevent a direct assessment of each necessary step ultimately leading to an intended drug effect or an unintended adverse reaction. Yet, incomplete investigation of the causality of drug responses is a major risk for translational assessments and the prediction of drug responses in different species or other populations. Mechanism-based modeling and simulation (M&S) offers a means to investigate complex physiological and pharmacological processes and to complement experimental data for non-accessible steps in the pharmacological causal chain. With the help of two examples, it is illustrated, what level of physiological detail, state-of-the-art models can represent, how predictive these models are and how mechanism-based approaches can be combined with empirical correlation-based concepts.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 15%
Student > Bachelor 2 15%
Student > Ph. D. Student 2 15%
Student > Master 1 8%
Researcher 1 8%
Other 0 0%
Unknown 5 38%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 3 23%
Medicine and Dentistry 2 15%
Agricultural and Biological Sciences 1 8%
Neuroscience 1 8%
Chemistry 1 8%
Other 0 0%
Unknown 5 38%