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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/19381

Title: Novel in vitro and mathematical models for the prediction of chemical toxicity
Authors: Williams, Dominic P.
Shipley, Rebecca
Ellis, Marianne J.
Webb, Steve
Ward, John P.
Gardner, Iain
Creton, Stuart
Issue Date: 2013
Publisher: © Royal Society of Chemistry
Citation: WILLIAMS, D.P. ... et al, 2013. Novel in vitro and mathematical models for the prediction of chemical toxicity. Toxicology Research, 2 (1), pp.40-59
Abstract: The focus of much scientific and medical research is directed towards understanding the disease process and defining therapeutic intervention strategies. Whilst the scientific basis of drug safety has received relatively little attention, despite the fact that adverse drug reactions (ADRs) are a major health concern and a serious impediment to development of new medicines. Toxicity issues account for ~21% drug attrition during drug development and safety testing strategies require considerable animal use. Mechanistic relationships between drug plasma levels and molecular/cellular events that culminate in whole organ toxicity underpins development of novel safety assessment strategies. Current in vitro test systems are poorly predictive of toxicity of chemicals entering the systemic circulation, particularly to the liver. Such systems fall short because of 1) the physiological gap between cells currently used & human hepatocytes existing in their native state, 2) the lack of physiological integration with other cells/systems within organs, required to amplify the initial toxicological lesion into overt toxicity, 3) the inability to assess how low level cell damage induced by chemicals may develop into overt organ toxicity in a minority of patients, 4) lack of consideration of systemic effects. Reproduction of centrilobular & periportal hepatocyte phenotypes in in vitro culture is crucial for sensitive detection of cellular stress. Hepatocyte metabolism/phenotype is dependent on cell position along the liver lobule, with corresponding differences in exposure to substrate, oxygen & hormone gradients. Application of bioartificial liver (BAL) technology can encompass in vitro predictive toxicity testing with enhanced sensitivity and improved mechanistic understanding. Combining this technology with mechanistic mathematical models describing intracellular metabolism, fluid-­‐flow, substrate, hormone and nutrient distribution provides the opportunity to design the BAL specifically to mimic the in vivo scenario. Such mathematical models enable theoretical hypothesis testing, will inform the design of in vitro experiments, and will enable both refinement and reduction of in vivo animal trials. In this way, development of novel mathematical modelling tools will help to focus and direct in vitro and in vivo research, and can be used as a framework for other areas of drug safety science.
Description: This article was published as Open Access and is licensed under a Creative Commons Attribution 3.0 Unported Licence.
Version: Published
DOI: 10.1039/c2tx20031g
URI: https://dspace.lboro.ac.uk/2134/19381
Publisher Link: http://dx.doi.org/10.1039/c2tx20031g
ISSN: 2045-452X
Appears in Collections:Published Articles (Maths)

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