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008 160915s2014 gw | s |||| 0|eng d
020 _a9783642397653
_9978-3-642-39765-3
024 7 _a10.1007/978-3-642-39765-3
_2doi
035 _ato000544670
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aRM1-950
072 7 _aMMG
_2bicssc
072 7 _aMED071000
_2bisacsh
082 0 4 _a615
_223
100 1 _aGieschke, Ronald.
_eauthor.
_9452330
245 1 0 _aDevelopment of Innovative Drugs via Modeling with MATLAB
_helectronic resource
_bA Practical Guide /
_cby Ronald Gieschke, Daniel Serafin.
260 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2014.
300 _aXV, 399 p. 192 illus., 112 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 _aBackground 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 _aThe 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 _amedicine.
_9566220
650 0 _aToxicology.
_9302218
650 0 _aPharmaceutical technology.
_9410704
650 0 _aComputer simulation.
_9304569
650 0 _aBiology
_xData processing.
_9305000
650 1 4 _aBiomedicine.
_9566246
650 2 4 _aPharmacology/Toxicology.
_9302222
650 2 4 _aPharmaceutical Sciences/Technology.
_9329108
650 2 4 _aSimulation and Modeling.
_9304570
650 2 4 _aComputer Appl. in Life Sciences.
_9305001
700 1 _aSerafin, Daniel.
_eauthor.
_9452331
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-39765-3
912 _aZDB-2-SBL
999 _c402369