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Parallelogram based approach for in vivo dose estimation of genotoxic metabolites in humans with relevance to reduction of animal experiments.


ABSTRACT: When employing metabolism studies of genotoxic compounds/metabolites and cancer tests for risk estimation, low exposure doses in humans are roughly extrapolated from high exposure doses in animals. An improvement is to measure the in vivo dose, i.e. area under concentration-time curve (AUC), of the causative genotoxic agent. In the present work, we propose and evaluate a parallelogram based approach for estimation of the AUC of genotoxic metabolites that incorporates in vitro metabolic data and existing knowledge from published in vivo data on hemoglobin (Hb) adduct levels, using glycidamide (GA) as a case study compound that is the genotoxic metabolite of acrylamide (AA). The estimated value of AUC of GA per AUC of AA from the parallelogram approach vs. that from Hb adduct levels measured in vivo were in good agreement; 0.087 vs. 0.23 in human and 1.4 vs. 0.53 in rat, respectively. The described parallelogram approach is simple, and can be useful to provide an approximate estimation of the AUC of metabolites in humans at low exposure levels for which sensitive methods for analyzing the metabolites are not available, as well as aid in reduction of animal experiments for metabolism studies that are to be used for cancer risk assessment.

SUBMITTER: Motwani HV 

PROVIDER: S-EPMC5730592 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Parallelogram based approach for in vivo dose estimation of genotoxic metabolites in humans with relevance to reduction of animal experiments.

Motwani Hitesh V HV   Frostne Cecilia C   Törnqvist Margareta M  

Scientific reports 20171214 1


When employing metabolism studies of genotoxic compounds/metabolites and cancer tests for risk estimation, low exposure doses in humans are roughly extrapolated from high exposure doses in animals. An improvement is to measure the in vivo dose, i.e. area under concentration-time curve (AUC), of the causative genotoxic agent. In the present work, we propose and evaluate a parallelogram based approach for estimation of the AUC of genotoxic metabolites that incorporates in vitro metabolic data and  ...[more]

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