Application of Modern Toxicology Approaches for Predicting Acute Toxicity for Chemical Defense (2015) / Chapter Skim
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3 Nontesting Approaches Relevant to Prediction of Acute Toxicity and Potency
3 Nontesting Approaches Relevant to Prediction of Acute Toxicity and Potency
Pages 29-50
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From page 29... ...
are used to fill specific data gaps in lieu of experimental testing, to support findings or conclusions in integrated chemical assessments, and to substantiate predictions of various properties for structurally related chemicals. A key assumption that underpins nontesting approaches is that the property of a chemical with respect to how it will interact with a defined biological system is inherent in its molecular structure; thus, similar chemicals should have similar biological activities (the similarity principle)
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, common constituents or chemical classes, similar carbon range numbers, or common precursors or breakdown products. In silico approaches include computational modeling, SAR analysis, analysis of physicochemi cal characteristics, and read-across techniques.
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USE OF PHYSICOCHEMICAL PROPERTIES TO PREDICT PHYSICAL HAZARDS, CHEMICAL REACTIVITY, AND PHARMACOKINETICS Physicochemical data can be used to predict a chemical's physical hazard, reactivity, and pharmacokinetics, including absorption by different exposure routes, distribution in the body, and likely metabolites. Approaches that apply knowledge about a chemical's physicochemical properties to predictive toxicology presume that for a chemical to exert a toxic effect, it typically must be bioavailable to such an extent that it (or its metabolite)
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Use of Physicochemical Properties to Predict Physical Hazard and Chemical Stability or Reactivity Assessing the likely irritant or corrosive effects of a chemical would be a helpful component of a tiered evaluation strategy for predicting acute toxicity.3 In the absence of measured irritant or corrosive data, a handful of (Q) SAR approaches are useful in identifying potential irritants or corrosives.
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In silico approaches have been developed to predict many ADME processes; the sections below focus largely on approaches that are directly relevant for predicting acute toxicity. Absorption: Oral Some physicochemical properties -- such as molecular weight, the number of hydrogenbond donors and acceptors, and logKow -- have been shown to be predictive of oral absorption.
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Absorption: Dermal LogKow, water solubility, and molecular weight are also useful inputs for estimating dermal absorption characteristics of a target substance. QSAR models for predicting the dermal permeability coefficient (Kp)
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Limitations and Need for Improvement Many tools for predicting physicochemical properties that are relevant for the evaluation of chemical disposition and distribution factors are available, but they are limited by their training sets.7 Such tools are generally most applicable for small organic chemicals -- chemicals that have molecular weights of 500 Da or less (that is, not mixtures or polymers)
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Although the chemical domain of concern for DOD goes beyond that of drug-like substances, an understanding of the type of physicochemical properties that can affect adverse outcomes and the range of property values for which the effect is likely to be substantial can offer useful insights for guiding the assessment of acute toxicity of chemicals of interest to DOD. The sections that follow describe in silico approaches that are available or could be developed for predicting acute toxicity that is relevant to DOD's concerns.
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Benzene derivatives Electronegativity, dipole moment, and the presence of nitrogen- Toropov et al. 2008 containing groups were most important in predicting the acute oral toxicity of benzene derivatives.
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identification of toxic fragments. Models Based on Heterogeneous Datasets That Have Not Been Incorporated into Expert Systems Consensus models Use rodent in vivo acute oral data from the National Library of Medicine databases Rodent LD50 (oral)
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a Global hybrid approaches use models derived on the basis of a large heterogeneous dataset that includes chemical and biological information. b Local hybrid approaches aim to derive models that are specific to chemical class or reaction chemistry but will still be applicable to a broad spectrum of chemicals.
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1998) , 50 reference chemicals were tested in 61 cytotoxicity assays in the hope of predicting acute oral LD50s.
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Limitations and Need for Improvement The greatest focus in the literature has been on deriving QSAR models to predict oral rodent LD50s. There are some models for specific chemical classes, but there has been greater interest in exploring the feasibility of deriving global models.
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(2013) used classification and regression-tree analysis of in vitro data from the ACuteTox program to predict acute oral-toxicity categories.
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SAR models that use structural properties or physicochemical properties are available for predicting acute oral LD50s. Few models for predicting inhalation LC50s are available, and none for predicting dermal LD50s was identified.
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Furthermore, DOD should evaluate the applicability, relevance, and reliability of models and tools for predicting physicochemical properties and metabolism. Recommendation: To fill remaining gaps in nontesting approaches, DOD should consider a number of options for further research and development, including extrapolation of oral LD50 to other exposure routes through pharmacokinetic models; development of new (Q)
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2014. Predicting Acute Toxicity Using In Vitro ToxCast HTS Mitochondrial Inhibition Assays.
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2010. Neural computational prediction of oral drug absorption based on CODES 2D descriptors.
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2013. Selection of test methods to be included in a testing strategy to predict acute oral toxicity: An approach based on statistical analy sis of data collected in phase 1 of the ACuteTox project.
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437: Bovine Corneal Opacity and Permeability Test Method for Identifying i) Chemicals Inducing Serious Eye Damage and ii)
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2013. The value of selected in vitro and in silico methods to predict acute oral toxicity in a regulatory context: Results from the European Project ACuteTox.
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2009b. A novel 2-step hierarchical quantitative structure-activity relationship modelling workflow for predicting acute tox icity of chemicals in rodents.
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