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008			220221s2022 xxua o |||| 0|eng d
020			_a9781071619605
024	7		_a10.1007/978-1-0716-1960-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aRM302.5 _b2022 EB
245	0	0	_aIn Silico Methods for Predicting Drug Toxicity _cedited by Emilio Benfenati
250			_a2nd edition 2022
264		1	_aNew York, NY _bSpringer International Publising _c2022
300			_a1 recurso en línea (XIV, 680 páginas) _b244 ilustraciones, 215 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 _v2425
505	0		_aQSAR Methods -- PBPK Modeling to Simulate the Fate of Compounds in Living Organisms -- Pharmacokinetic Tools and Applications -- In Silico Tools and Software to Predict ADMET of New Drug Candidates -- Development of In Silico Methods for Toxicity Prediction in Collaboration between Academia and the Pharmaceutical Industry -- Emerging Bioinformatics Methods and Resources in Drug Toxicology -- In Silico Prediction of Chemically-Induced Mutagenicity: A Weight of Evidence Approach Integrating Information from QSAR Models and Read-Across Predictions -- In Silico Methods for Chromosome Damage -- In Silico Methods for Carcinogenicity Assessment -- In Silico Models for Developmental Toxicity -- 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 Predicting Acute Systemic Toxicity -- In Silico Models for Skin Sensitization and Irritation -- In Silico Models for Hepatotoxicity -- Machine Learning Models for Predicting Liver Toxicity -- Implementation of In Silico Toxicology Protocols in Leadscope -- Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity -- Using VEGAHUB within a Weight-of-Evidence Strategy -- MultiCASE Platform for In Silico Toxicology -- Adverse Outcome Pathways as Versatile Tools in Liver Toxicity Testing -- The Use of In Silico Methods for the Regulatory Toxicological Assessment of Pharmaceutical Impurities -- Computational Modeling of Mixture Toxicity -- In Silico Methods for Ecological Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives -- Increasing the Value of Data within a Large Pharmaceutical Company through In Silico Models.
520			_aThis fully updated book explores all-new and revised protocols involving the use of in silico models, particularly with regard to pharmaceuticals. Divided into five sections, the volume covers the modeling of pharmaceuticals in the body, toxicity data for modeling purposes, in silico models for multiple endpoints, a number of platforms for evaluating pharmaceuticals, as well as an exploration of challenges, both scientific and sociological. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and implementation advice necessary for successful results. Authoritative and comprehensive, In Silico Methods for Predicting Drug Toxicity, Second Edition aims to guide the reader through the correct procedures needed to harness in silico models, a field which now touches a wide variety of research specialties.
988			_aSpringer_Protocols_2022
650		7	_2embne _9168753 _aMedicamentos _xEfectos secundarios
650		7	_2embne _9137892 _aMedicamentos _xToxicidad
776	0	8	_iPrinted edition: _z9781071619599
776	0	8	_iPrinted edition: _z9781071619612
776	0	8	_iPrinted edition: _z9781071619629
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-1960-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2023 _dz _eb _zSI