A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)

Zhao, Chunyan; Boriani, Elena; Chana, Antonio; Roncaglioni, Alessandra; Benfenati, Emilio

doi:10.1016/j.chemosphere.2008.09.033

Cited by 98 publications

(69 citation statements)

References 27 publications

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“…2D). As a solvation connectivity index, X 0sol could be considered as the entropy of solvation, which indicates dispersion interactions in solutions (Zhao et al, 2008). Our results showed that both non-polar interactions, as indicated by N m and electrostatic-like forces provided by acidic groups, might predominate in the stimulation effect.…”

Section: Quantitative Structure-activity Relationship Of Pfaasmentioning

confidence: 75%

Synergistic effects of perfluoroalkyl acids mixtures with J-shaped concentration–responses on viability of a human liver cell line

Hu¹,

Li²,

Wang³

et al. 2014

Chemosphere

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Section: Quantitative Structure-activity Relationship Of Pfaasmentioning

confidence: 75%

Synergistic effects of perfluoroalkyl acids mixtures with J-shaped concentration–responses on viability of a human liver cell line

Hu¹,

Li²,

Wang³

et al. 2014

Chemosphere

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“…In the evaluation of the BCF, the current uncertainty within experimental results from in vivo tests is between 0.40 and 0.75 log units (Zhao et al, 2008). A more recent study identified 0.6 as the typical uncertainty (lombardo et al, 2010).…”

Section: Uncertainty Levels In Experimental In Vivo Results For Bcfmentioning

confidence: 99%

Using toxicological evidence from QSAR models in practice

Benfenati

2013

ALTEX

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Summary Leading QSAR models provide supporting documentation in addition toIn three case studies, we explore the information provided by the ePISuite, t.e.S.t., and VeGA platforms for evaluating the bioconcentration factor (BCF) for three example compounds. We address the central practical challenges of how to determine whether a toxicity prediction for a compound is reliable, as well as how to discuss the predictions and supporting information so that the evidence and reasoning can be understood, reviewed, and potentially accepted by others. This investigation is the first inter-laboratory and cross-institutional review exercise on the reliability of QSAR results in the evaluation of an animal model. As far as we know, it is the first exercise of this nature.In sections 2-6 below, we start by explaining the rationale for this exercise: why the practical case-by-case use of QSAR models is an important focus for investigative review, especially in light of the eU regulatory demands from ReACH. We then describe the methods of this investigation, including the significance of the three example compounds as case studies, the features of the QSAR platforms used, and, finally, the issue of reliability for experimental BCF results and predictions.taking each compound as a separate case study, we describe the BCF predictions offered by each QSAR platform and the range of information provided to support those predictions. We discuss and illustrate the use of this information by toxicologists to reach a decision on the reliability of the prediction. We then discuss the decisions on reliability made by the 28 participants and the comments they made about their decisions. Having

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“…Bioconcentration factor describes the accumulation of a given chemical in organisms arising by uptake from water only and is generally determined under laboratory conditions, whereas the bioaccumulation factor (BAF) represents accumulation from both water and diet and is derived from in situ observations. The BCF concept was originally developed for hydrophobic organic substances and several quantitative structure-activity relationship (QSAR) techniques were proposed to predict BCF from chemical descriptors of hydrophobicity such as octanolwater partition coefficients [6][7][8]. Simple passive diffusion across the lipid biomembranes is believed to be the key process for the accumulation of neutral hydrophobic substances in biota, which ensures that BCF is independent of exposure concentrations [9].…”

Section: Introductionmentioning

confidence: 99%

Regression approaches to derive generic and fish group‐specific probability density functions of bioconcentration factors for metals

Tanaka

Ciffroy

Stenberg

et al. 2010

Enviro Toxic and Chemistry

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In the framework of environmental multimedia modeling studies dedicated to environmental and health risk assessments of chemicals, the bioconcentration factor (BCF) is a parameter commonly used, especially for fish. As for neutral lipophilic substances, it is assumed that BCF is independent of exposure levels of the substances. However, for metals some studies found the inverse relationship between BCF values and aquatic exposure concentrations for various aquatic species and metals, and also high variability in BCF data. To deal with the factors determining BCF for metals, we conducted regression analyses to evaluate the inverse relationships and introduce the concept of probability density function (PDF) for Cd, Cu, Zn, Pb, and As. In the present study, for building the regression model and derive the PDF of fish BCF, two statistical approaches are applied: ordinary regression analysis to estimate a regression model that does not consider the variation in data across different fish family groups; and hierarchical Bayesian regression analysis to estimate fish group-specific regression models. The results show that the BCF ranges and PDFs estimated for metals by both statistical approaches have less uncertainty than the variation of collected BCF data (the uncertainty is reduced by 9%-61%), and thus such PDFs proved to be useful to obtain accurate model predictions for environmental and health risk assessment concerning metals.

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A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)

Cited by 98 publications

References 27 publications

Synergistic effects of perfluoroalkyl acids mixtures with J-shaped concentration–responses on viability of a human liver cell line

Synergistic effects of perfluoroalkyl acids mixtures with J-shaped concentration–responses on viability of a human liver cell line

Using toxicological evidence from QSAR models in practice

Regression approaches to derive generic and fish group‐specific probability density functions of bioconcentration factors for metals

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