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New Technologies for Toxicity Testing. 1st ed. 2012

種類:
電子ブック
責任表示:
edited by Michael Balls, Robert D. Combes, Nirmala Bhogal
出版情報:
New York, NY : Springer New York : Imprint: Springer, 2012
著者名:
シリーズ名:
Advances in Experimental Medicine and Biology ; 745
ISBN:
9781461430551 [1461430550]  CiNii Books  Calil
注記:
Current Developments in Cell Culture Technology -- Embryonic Stem Cells in Safety Pharmacology and Toxicology -- Trends in Cell Culture Technology -- Tissue Engineering in the Development of Replacement Technologies -- Toxicity Testing of Nanomaterials -- Physiologically‑Based Pharmacokinetic (PBPK) Models in Toxicity Testing and Risk Assessment -- In Silico Methods for Toxicity Prediction -- Luminescent Quantum Dots for Molecular Toxicology -- Engineering Quasi‑Vivo® In‑Vitro Organ Models -- ECVAM and New Technologies for Toxicity Testing -- Medium to High Throughput Screening: Microfabricat ion and Chip‑Based Technology -- The Use of Genomics in Model In Vitro Systems -- The Use of Integrated and Intelligent Testing Strategies in the Prediction of Toxic Hazard and in Risk Assessment.
The central theme running through this volume on New Technologies for Toxicity Testing is the development and application of advanced techniques for cell and tissue culture, as well as new markers and endpoints of toxicity, as alternatives to the traditional paradigm of relying on data from laboratory animal tests to undertake labelling and risk assessment. Of course, many of the techniques and methods described in this volume are in the early stages of development, and much work will be needed to ensure their further improvement, optimisation and validation. However, we are confident that this will be achieved and that, just as with the in vitro assays that were validated and granted regulatory acceptance over the last decade, these, and many other new, advanced methods, will likewise become part of the toxicologist’s improved toolbox for coping with increasingly stringent and numerous regulatory requirements and test chemicals, while placing less reliance on traditional testing paradigms.
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