A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

The EU one-stop-shop collection of publicly available information on COVID-19 in vitro diagnostic medical devices

The JRC COVID-19 In Vitro Diagnostic Devices and Test Methods Database, aimed to collect in a single place all publicly available information on performance of CE-marked in vitro diagnostic medical devices (IVDs) as well as in house laboratory-developed devices and related test methods for COVID-19, is here presented. The database, manually curated and regularly updated, has been developed as a follow-up to the Communication from the European Commission “Guidelines on in vitro diagnostic tests and their performance” of 15 April 2020 and is freely accessible at https://covid-19-diagnostics.jrc.ec.europa.eu/.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

Artificial Intelligence for chemical risk assessment

As the basis for managing the risks of chemical exposure, the Chemical Risk Assessment (CRA) process can impact a substantial part of the economy, the health of hundreds of millions of people, and the condition of the environment. However, the number of properly assessed chemicals falls short of societal needs due to a lack of experts for evaluation, interference of third party interests, and the sheer volume of potentially relevant information on the chemicals from disparate sources. In order to explore ways in which computational methods may help overcome this discrepancy between the number of chemical risk assessments required on the one hand and the number and adequateness of assessments actually being conducted on the other, the European Commission's Joint Research Centre organised a workshop on Artificial Intelligence for Chemical Risk Assessment (AI4CRA). The workshop identified a number of areas where Artificial Intelligence could potentially increase the number and quality of regulatory risk management decisions based on CRA, involving process simulation, supporting evaluation, identifying problems, facilitating collaboration, finding experts, evidence gathering, systematic review, knowledge discovery, and building cognitive models. Although these are interconnected, they are organised and discussed under two main themes: scientific-technical process and social aspects and the decision making process.

Review of micro- and nanoplastic contamination in the food chain

Whereas the dramatic environmental impact of plastic waste rightfully receives considerable attention by scientists, policy makers and public in general, the human health impact of micro- and nanoplastics contamination of our food and beverages remains largely unknown. Indeed, most studies aim at understanding the environmental impact rather than the human health impact of a possible exposure to micro- and nanoplastics. In addition, these papers generally lack a methodological, standardised approach. Furthermore, some studies focus on the damage to and contamination level of animal species collected from the wild environment, and others investigate the rate and biology of microplastic uptake of animals fed with microplastics in laboratory. This review aims at understanding human exposure. Since there is, with few exceptions, no evidence available on the presence of micro- and nanoplastics in a normal diet, this study takes an indirect approach and analyses peer-reviewed publications since 2010 that document the presence of micro- and nanoplastics in those animals (more than 200 species) and food products that are part of the human food chain and that may thus contribute directly or indirectly to the uptake of micro- and nanoplastics via the human diet. It also addresses the question of the definitions, the methodologies and the quality criteria applied to obtain the reported results. This review suggests that, beyond a few estimations and comparisons, precise data to assess the exact exposure of humans to micro- and nanoplastics through their diet cannot be produced until standardised methods and definitions are available.

Evaluation of some screening methods for the analysis of contaminants in recycled polyethylene terephthalate flakes

A range of different analytical techniques were used to test recycled polyethylene terephthalate (PET) flakes for potential chemical contaminants. The techniques used were headspace gas chromatography coupled to mass spectrometry (GC-MS), liquid extraction followed by GC-MS, supercritical-fluid extraction followed by GC-MS, and migration testing followed by elemental analysis using inductively coupled plasma mass spectroscopy (ICP-MS). The PET samples were 50 representative samples taken from 600 that had been collected throughout Europe and which had been screened for potential contaminants using a single technique of high-temperature GC-MS. Six of the 50 samples tested had been spiked with a selection of model contaminants, three samples were virgin PET flakes and two of the samples were from supercleaning processes. All samples were analysed 'blind' in this exercise. The qualitative results showed that most of the contaminants came from the first use, being flavour-aroma compounds from soft drinks. The quantitative analysis found concentrations under a few mg kg(-1) in the polymer, except for the spiked samples. Element migrations were low and only calcium, silicon and sodium had median migrations above 50 microg l(-1). This in-depth analysis of recycled PET flakes did not identify any significant contaminants that had not already been detected by the high-temperature static GC-MS screening method, thus demonstrating its utility.