Characterisation of data resources for in silico modelling: benchmark datasets for ADME properties.

Introduction: The cost of in vivo and in vitro screening of ADME properties of compounds has motivated efforts to develop a range of in silico models. At the heart of the development of any computational model are the data; high quality data are essential for developing robust and accurate models. The characteristics of a dataset, such as its availability, size, format and type of chemical identifiers used, influence the modelability of the data. Areas covered: This review explores the usefulness of publicly available ADME datasets for researchers to use in the development of predictive models. More than 140 ADME datasets were collated from publicly available resources and the modelability of 31selected datasets were assessed using specific criteria derived in this study. Expert opinion: Publicly available datasets differ significantly in information content and presentation. From a modelling perspective, datasets should be of adequate size, available in a user-friendly format with all chemical structures associated with one or more chemical identifiers suitable for automated processing (e.g. CAS number, SMILES string or InChIKey). Recommendations for assessing dataset suitability for modelling and publishing data in an appropriate format are discussed

Characterization of Emissions from a Desktop 3D Printer

3D printers are currently widely available and very popular among the general public. However, the use of these devices may pose health risks to users, attributable to air-quality issues arising from gaseous and particulate emissions in particular. We characterized emissions from a low-end 3D printer based on material extrusion, using the most common polymers: acrylonitrile-butadiene-styrene (ABS) and polylactic acid (PLA). Measurements were carried out in an emission chamber and a conventional room. Particle emission rates were obtained by direct measurement and modeling, whereas the influence of extrusion temperature was also evaluated. ABS was the material with the highest aerosol emission rate. The nanoparticle emission ranged from 3.7.10(8) to 1.4.10(9) particles per second (# s(-1)) in chamber measurements and from 2.0.10(9) to 4.0.10(9) # s(-1)in room measurements, when the recommended extruder temperature was used. Printing with PLA emitted nanoparticles at the rate of 1.0.10(7) # s(-1) inside the chamber and negligible emissions in room experiments. Emission rates were observed to depend strongly on extruder temperature. The particles' mean size ranged from 7.8 to 10.5 nanometers (nm). We also detected a significant emission rate of particles of 1 to 3nm in size during all printing events. The amounts of volatile organic and other gaseous compounds were only traceable and are not expected to pose health risks. Our study suggests that measures preventing human exposure to high nanoparticle concentrations should be adopted when using low-end 3D printers.Peer reviewe

Identification and Description of the Uncertainty, Variability, Bias and Influence in Quantitative Structure-Activity Relationships (QSARs) for Toxicity Prediction

Improving regulatory confidence in, and acceptance of, a prediction of toxicity from a quantitative structure-activity relationship (QSAR) requires assessment of its uncertainty and determination of whether the uncertainty is acceptable. Thus, it is crucial to identify potential uncertainties fundamental to QSAR predictions. Based on expert review, sources of uncertainties, variabilities and biases, as well as areas of influence in QSARs for toxicity prediction were established. These were grouped into three thematic areas: uncertainties, variabilities, potential biases and influences associated with 1) the creation of the QSAR, 2) the description of the QSAR, and 3) the application of the QSAR, also showing barriers for their use. Each thematic area was divided into a total of 13 main areas of concern with 49 assessment criteria covering all aspects of QSAR development, documentation and use. Two case studies were undertaken on different types of QSARs that demonstrated the applicability of the assessment criteria to identify potential weaknesses in the use of a QSAR for a specific purpose such that they may be addressed and mitigation strategies can be proposed, as well as enabling an informed decision on the adequacy of the model in the considered context

Thresholds of Toxicological Concern for Cosmetics-Related Substances: New Database, Thresholds, and Enrichment of Chemical Space

A new dataset of cosmetics-related chemicals for the Threshold of Toxicological Concern (TTC) approach has been compiled, comprising 552 chemicals with 219, 40, and 293 chemicals in Cramer Classes I, II, and III, respectively. Data were integrated and curated to create a database of No-/Lowest-Observed-Adverse-Effect Level (NOAEL/LOAEL) values, from which the final COSMOS TTC dataset was developed. Criteria for study inclusion and NOAEL decisions were defined, and rigorous quality control was performed for study details and assignment of Cramer classes. From the final COSMOS TTC dataset, human exposure thresholds of 42 and 7.9 μg/kg-bw/day were derived for Cramer Classes I and III, respectively. The size of Cramer Class II was insufficient for derivation of a TTC value. The COSMOS TTC dataset was then federated with the dataset of Munro and colleagues, previously published in 1996, after updating the latter using the quality control processes for this project. This federated dataset expands the chemical space and provides more robust thresholds. The 966 substances in the federated database comprise 245, 49 and 672 chemicals in Cramer Classes I, II and III, respectively. The corresponding TTC values of 46, 6.2 and 2.3 μg/kg-bw/day are broadly similar to those of the original Munro dataset

Cross-Sector Review of Drivers and Available 3Rs Approaches for Acute Systemic Toxicity Testing

Acute systemic toxicity studies are carried out in many sectors in which synthetic chemicals are manufactured or used and are among the most criticized of all toxicology tests on both scientific and ethical grounds. A review of the drivers for acute toxicity testing within the pharmaceutical industry led to a paradigm shift whereby in vivo acute toxicity data are no longer routinely required in advance of human clinical trials. Based on this experience, the following review was undertaken to identify (1) regulatory and scientific drivers for acute toxicity testing in other industrial sectors, (2) activities aimed at replacing, reducing, or refining the use of animals, and (3) recommendations for future work in this area

Response of sediment bacterial community to triclosan in subtropical freshwater benthic microcosms

The response of sediment bacterial communities in subtropical freshwater benthic microcosms to sediment-associated triclosan (TCS; 28 d exposure) was analysed using Illumina high-throughput sequencing. This study highlights the interactive effects of TCS and the presence of benthic macroinvertebrates (Limnodrilus hoffmeisteri and Viviparidae bellamya) on sediment bacterial communities. Our results show that TCS alone significantly altered the taxonomic composition and decreased alpha diversity of sediment bacterial communities at concentrations ≥80 μg TCS/g dry weight (dw) sediment (sed). Regarding dominant phyla, TCS significantly reduced the relative abundance of Bacteroidetes and Firmicutes at these concentrations, whereas the relative abundance of Chloroflexi and Cyanobacteria increased. In the presence of benthic macroinvertebrates, the sediment bacterial community was affected by 8 μg TCS/g dw sed as well. However, the presence of benthic macroinvertebrates did not cause measurable changes to bacterial community in unspiked (i.e., control) sediment. These results indicate that TCS alone would not alter the sediment bacterial community at environmentally relevant concentrations (up till 8 μg/g dw sed), but may have an effect in combination with the presence of benthic macroinvertebrates. Therefore, we recommend to include benthic macroinvertebrates when assessing the response of sediment bacterial communities during exposure to environmental stress such as organic contaminants.</p

Smoke toxicity of rainscreen façades

The toxic smoke production of four rainscreen façade systems were compared during large-scale fire performance testing on a reduced height BS 8414 test wall. Systems comprising 'non-combustible' aluminium composite material (ACM) with polyisocyanurate (PIR), phenolic foam (PF) and stone wool (SW) insulation, and polyethylene-filled ACM with PIR insulation were tested. Smoke toxicity was measured by sampling gases at two points - the exhaust duct of the main test room and an additional 'kitchen vent', which connects the rainscreen cavity to an occupied area. Although the toxicity of the smoke was similar for the three insulation products with non-combustible ACM, the toxicity of the smoke flowing from the burning cavity through the kitchen vent was greater by factors of 40 and 17 for PIR and PF insulation respectively, when compared to SW. Occupants sheltering in a room connected to the vent are predicted to collapse, and then inhale a lethal concentration of asphyxiant gases. This is the first report quantifying fire conditions within the cavity and assessing smoke toxicity within a rainscreen façade cavity. [Abstract copyright: Copyright © 2020 Elsevier B.V. All rights reserved.