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008			160616s2016 xxu| s |||| 0|eng d
020			_a9781493936090
024	7		_a10.1007/978-1-4939-3609-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aIn Silico Methods for Predicting Drug Toxicity _cedited by Emilio Benfenati.
250			_a1st edition 2016
264		1	_aNew York, NY _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XI, 534 páginas) _b193 ilustraciones, 156 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v1425
505	0		_aQSAR Methods -- In Silico 3D-Modelling of Binding Activities -- Modeling Pharmacokinetics -- Modeling ADMET -- In Silico Prediction of Chemically-Induced Mutagenicity: How to Use QSAR Models and Interpret Their Results -- In Silico Methods for Carcinogenicity Assessment -- VirtualToxLab: Exploring the Toxic Potential of Rejuvenating Substances Found in Traditional Medicines -- In Silico Model for Developmental Toxicity: How to Use QSAR Models and Interpret Their Results -- In Silico Models for Repeated Dose Toxicity (RDT): Prediction of the No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) for Drugs -- In Silico Models for Acute Systemic Toxicity -- In Silico Models for Hepatotoxicity -- In Silico Models for Ecotoxicity of Pharmaceuticals -- Use of Read-Across Tools -- Adverse Outcome Pathways as Tools to Assess Drug-Induced Toxicity -- A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure -- In Silico Study of In Vitro GPCR Assays by QSAR Modeling -- Taking Advantage of Databases -- QSAR Models at the United States FDA/NCTR -- A Round Trip from Medicinal Chemistry to Predictive Toxicology -- The Use of In Silico Models Within a Large Pharmaceutical Company -- The Consultancy Activity on In Silico Models for Genotoxic Prediction of Pharmaceutical Impurities.
520			_aThis detailed volume explores in silico methods for pharmaceutical toxicity by combining the theoretical advanced research with the practical application of the tools. Beginning with a section covering sophisticated models addressing the binding to receptors, pharmacokinetics and adsorption, metabolism, distribution, and excretion, the book continues with chapters delving into models for specific toxicological and ecotoxicological endpoints, as well as broad views of the main initiatives and new perspectives which will very likely improve our way of modelling pharmaceuticals. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that is key for achieving successful research results. Authoritative and practical, In Silico Methods for Predicting Drug Toxicity offers the advantage of incorporating data and knowledge from different fields, such as chemistry, biology, -omics, and pharmacology, to achieve goals in this vital area of research.
700	1		_aBenfenati, Emilio _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9781493936076
776	0	8	_iPrinted edition: _z9781493936083
776	0	8	_iPrinted edition: _z9781493980932
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-4939-3609-0 _z(usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Protocols_2016
999			_c235749 _d235749