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T10 PM Advances in Bioaccumulation Assessment
(DIM-1117-798314) BCF Base Line Model and Effect of Mitigating Factors.
Mekenyan, Ovanes1, Dimitrov, Sabcho1, Parkerton, T2, Comber, M3, Bonnell, M4, 1 Laboratory of Mathematical Chemistry, University "Prof. As. Zlatarov", Bourgas, Bulgaria2 Toxicological and Environmental Sciences Division, ExxonMobil Biomedical Sciences, Inc., Annandale, NJ, USA3 ExxonMobil Biomedical Sciences, Machelen, Belgium4 New Chemicals Evaluation Division, New Substances Branch, Environment, Gatineau, Quebec, Canada
ABSTRACT- The base-line modeling concept is based on the assumption of maximum cut off for BCF and set of mitigating factors reducing it. The maximum potential of bioconcentration is assumed to be a result of passive diffusion conditioned by chemical lipofilicity, only. The multi-compartment partitioning model is used as the theoretical justification for this concept. The significance of different mitigating factors associated either with interactions with an organism or bioavailability were investigated. The most important mitigating factor was found to be metabolism. Accordingly, a metabolism simulator for fish liver was used in the model, which has been trained to reproduce fish metabolism based on related mammalian metabolic pathways. It contains 382 Phase I and 48 Phase II metabolic transformations. The probabilities of occurrence of transformations were regressed on the basis of 515 experimental BCF values. Other significant mitigating factors, depending on the chemical structure, e.g. molecular size and ionization are also taken into account in the model. The current structural domain of the model includes a variety of chemical classes such as low molecular chain-like, carbo-monocyclic, carbo-polycyclic heterocyclic organic compounds and pharmacopoeial chemical substances. The results (R2 = 0.84) obtained for a training set of 515 chemicals demonstrate the usefulness of the BCF base line concept. The predictability of the model was evaluated on the basis of 176 chemicals not used in the model building. The correctness of predictions for 59 chemicals identified to belong to the model applicability domain was 80%.
Key words: BCF, passive diffusion, metabolism, ionization
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