21 research outputs found

    Toxicokinetic Triage for Environmental Chemicals

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    Toxicokinetic (TK) models link administered doses to plasma, blood, and tissue concentrations. High-throughput TK (HTTK) performs in vitro to in vivo extrapolation to predict TK from rapid in vitro measurements and chemical structure-based properties. A significant toxicological application of HTTK has been “reverse dosimetry,” in which bioactive concentrations from in vitro screening studies are converted into in vivo doses (mg/kg BW/day). These doses are predicted to produce steady-state plasma concentrations that are equivalent to in vitro bioactive concentrations. In this study, we evaluate the impact of the approximations and assumptions necessary for reverse dosimetry and develop methods to determine whether HTTK tools are appropriate or may lead to false conclusions for a particular chemical. Based on literature in vivo data for 87 chemicals, we identified specific properties (eg, in vitro HTTK data, physico-chemical descriptors, and predicted transporter affinities) that correlate with poor HTTK predictive ability. For 271 chemicals we developed a generic HT physiologically based TK (HTPBTK) model that predicts non-steady-state chemical concentration time-courses for a variety of exposure scenarios. We used this HTPBTK model to find that assumptions previously used for reverse dosimetry are usually appropriate, except most notably for highly bioaccumulative compounds. For the thousands of man-made chemicals in the environment that currently have no TK data, we propose a 4-element framework for chemical TK triage that can group chemicals into 7 different categories associated with varying levels of confidence in HTTK predictions. For 349 chemicals with literature HTTK data, we differentiated those chemicals for which HTTK approaches are likely to be sufficient, from those that may require additional data

    Human embryonic stem cell-derived test systems for developmental neurotoxicity: a transcriptomics approach

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    Developmental neurotoxicity (DNT) and many forms of reproductive toxicity (RT) often manifest themselves in functional deficits that are not necessarily based on cell death, but rather on minor changes relating to cell differentiation or communication. The fields of DNT/RT would greatly benefit from in vitro tests that allow the identification of toxicant-induced changes of the cellular proteostasis, or of its underlying transcriptome network. Therefore, the 'human embryonic stem cell (hESC)- derived novel alternative test systems (ESNATS)' European commission research project established RT tests based on defined differentiation protocols of hESC and their progeny. Valproic acid (VPA) and methylmercury (MeHg) were used as positive control compounds to address the following fundamental questions: (1) Does transcriptome analysis allow discrimination of the two compounds? (2) How does analysis of enriched transcription factor binding sites (TFBS) and of individual probe sets (PS) distinguish between test systems? (3) Can batch effects be controlled? (4) How many DNA microarrays are needed? (5) Is the highest non-cytotoxic concentration optimal and relevant for the study of transcriptome changes? VPA triggered vast transcriptional changes, whereas MeHg altered fewer transcripts. To attenuate batch effects, analysis has been focused on the 500 PS with highest variability. The test systems differed significantly in their responses (\20 % overlap). Moreover, within one test system, little overlap between the PS changed by the two compounds has been observed. However, using TFBS enrichment, a relatively large 'common response' to VPA and MeHg could be distinguished from 'compound-specific' responses. In conclusion, the ESNATS assay battery allows classification of human DNT/RT toxicants on the basis of their transcriptome profiles.EU/FP7/ESNATSDFGDoerenkamp-Zbinden Foundatio

    Fingerprinting of neurotoxic compounds using a mouse embryonic stem cell dual luminescence reporter assay

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    Human glycemic response curves after intake of carbohydrate foods are accurately predicted by combining in vitro gastrointestinal digestion with in silico kinetic modeling

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    Background: Frequent high blood glucose concentrations are associated with increased risks of metabolic diseases. Knowledge about the glycemic response after food intake is essential in relation to human health. The American Association of Cereal Chemists recommends the development of reliable in vitro methods for standardized assessment of the human glycemic response after intake of carbohydrates. Aim: To realize a cost-efficient in vitro–in silico technology to predict reliably the human glycemic concentration curve after intake of different carbohydrate products or meals. Methods: We developed and validated a combined technology based on in vitro mastication of foods, digestion of the carbohydrates, availability for absorption of glycemic saccharides, and (based on these in vitro data as input) in silico prediction of glycemic response curves in humans. Results: The predicted curves were compared with human clinical data for 22 different food products. The results showed a correlation coefficient for glucose iAUC0–120 and glucose Cmax of 0.89 and 0.94, respectively. Also the shape of the curves and tmax were very similar for 18 out of 22 products, while 4 products showed an ‘early’ in vitro tmax compared to the human data. Conclusion: Based on the demonstrated accuracy and predictive quality, this in vitro–in silico technology can be used for the testing of food products on their glycemic response under standardized conditions and may stimulate the production of (s)low carbs for the prevention of metabolic diseases

    Fingerprinting of neurotoxic compounds using a mouse embryonic stem cell dual luminescence reporter assay

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    Identification of neurotoxic drugs and environmental chemicals is an important challenge. However, only few tools to address this topic are available. The aim of this study was to develop a neurotoxicity/developmental neurotoxicity (DNT) test system, using the pluripotent mouse embryonic stem cell line CGR8 (ESCs). The test system uses ESCs at two differentiation stages: undifferentiated ESCs and ESC-derived neurons. Under each condition, concentration-response curves were obtained for three parameters: activity of the tubulin alpha 1 promoter (typically activated in early neurons), activity of the elongation factor 1 alpha promoter (active in all cells), and total DNA content (proportional to the number of surviving cells). We tested 37 compounds from the ESNATS test battery, which includes polypeptide hormones, environmental pollutants (including methylmercury), and clinically used drugs (including valproic acid and tyrosine kinase inhibitors). Different classes of compounds showed distinct concentration-response profiles. Plotting of the lowest observed adverse effect concentrations (LOAEL) of the neuronal promoter activity against the general promoter activity or against cytotoxicity, allowed the differentiation between neurotoxic/DNT substances and non-neurotoxic controls. Reporter activity responses in neurons were more susceptible to neurotoxic compounds than the reporter activities in ESCs from which they were derived. To relate the effective/toxic concentrations found in our study to relevant in vivo concentrations, we used a reverse pharmacokinetic modeling approach for three exemplary compounds (teriflunomide, geldanamycin, abiraterone). The dual luminescence reporter assay described in this study allows high-throughput, and should be particularly useful for the prioritization of the neurotoxic potential of a large number of compounds
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