Development of Innovative Drugs via Modeling with MATLAB A Practical Guide /

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? Wr...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Gieschke, Ronald (Συγγραφέας), Serafin, Daniel (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Gieschke, Ronald.  |e author. 
245 1 0 |a Development of Innovative Drugs via Modeling with MATLAB  |h [electronic resource] :  |b A Practical Guide /  |c by Ronald Gieschke, Daniel Serafin. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2014. 
300 |a XV, 399 p. 192 illus., 112 illus. in color.  |b online resource. 
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505 0 |a Background of pharmacologic modeling -- First example of a computational model -- Differential equations in MATLAB -- Pharmacologic modeling -- Drug-disease modeling -- Population analyses -- Clinical trial simulation -- Graphics-based modeling -- Outlook -- Appendix A: Hints to MATLAB programs -- Appendix B: Solution to exercises. 
520 |a 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. 
650 0 |a Medicine. 
650 0 |a Pharmacology. 
650 0 |a Pharmaceutical technology. 
650 0 |a Computer simulation. 
650 0 |a Bioinformatics. 
650 0 |a Computational biology. 
650 1 4 |a Biomedicine. 
650 2 4 |a Pharmacology/Toxicology. 
650 2 4 |a Pharmaceutical Sciences/Technology. 
650 2 4 |a Simulation and Modeling. 
650 2 4 |a Computer Appl. in Life Sciences. 
700 1 |a Serafin, Daniel.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642397646 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-39765-3  |z Full Text via HEAL-Link 
912 |a ZDB-2-SBL 
950 |a Biomedical and Life Sciences (Springer-11642)