Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and infor- mation, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advance- ment of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.
DOCUMENT
For almost fifteen years, the availability and regulatory acceptance of new approach methodologies (NAMs) to assess the absorption, distribution, metabolism and excretion (ADME/biokinetics) in chemical risk evaluations are a bottleneck. To enhance the field, a team of 24 experts from science, industry, and regulatory bodies, including new generation toxicologists, met at the Lorentz Centre in Leiden, The Netherlands. A range of possibilities for the use of NAMs for biokinetics in risk evaluations were formulated (for example to define species differences and human variation or to perform quantitative in vitro-in vivo extrapolations). To increase the regulatory use and acceptance of NAMs for biokinetics for these ADME considerations within risk evaluations, the development of test guidelines (protocols) and of overarching guidance documents is considered a critical step. To this end, a need for an expert group on biokinetics within the Organisation of Economic Cooperation and Development (OECD) to supervise this process was formulated. The workshop discussions revealed that method development is still required, particularly to adequately capture transporter mediated processes as well as to obtain cell models that reflect the physiology and kinetic characteristics of relevant organs. Developments in the fields of stem cells, organoids and organ-on-a-chip models provide promising tools to meet these research needs in the future.
MULTIFILE
The methodology should be a uniform approach that also is flexible enough to accommodate all combinations that make up the different solutions in 6 OPs. For KPIs A and B this required the use of sub-KPIs to differentiate the effects of each (individual and combination of) implemented solutions and prevent double counting of results. This approach also helped to ensure that all 6 OPs use a common way and scope to calculate the various results. Consequently, this allowed the project to capture the results per OP and the total project in one ‘measurement results’ template. The template is used in both the individual OP reports and the ‘KPI Results: Baseline & Final results’ report where all results are accumulated; each instance providing a clear overview of what is achieved. This report outlines the details of the methodology used and applied. It is not just meant to provide a clarification of the results of the project, but is also meant to allow others who are embarking on adopting similar solutions for the purpose of CO2 reduction, becoming more energy autonomous or avoid grid stress or investments to learn about and possibly use the same methodology.
DOCUMENT
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
The projectThe overarching goal of DIGNITY, DIGital traNsport In and for socieTY, is to foster a sustainable, integrated and user-friendly digital travel eco-system that improves accessibility and social inclusion, along with the travel experience and daily life of all citizens. The project delves into the digital transport eco-system to grasp the full range of factors that might lead to disparities in the uptake of digitalised mobility solutions by different user groups in Europe. Analysing the digital transition from both a user and provider’s perspective, DIGNITY looks at the challenges brought about by digitalisation, to then design, test and validate the DIGNITY approach, a novel concept that seeks to become the ‘ABCs for a digital inclusive travel system’. The approach combines proven inclusive design methodologies with the principles of foresight analysis to examine how a structured involvement of all actors – local institutions, market players, interest groups and end users – can help bridge the digital gap by co-creating more inclusive mobility solutions and by formulating user-centred policy frameworks.The objectivesThe idea is to support public and private mobility providers in conceiving mainstream digital products or services that are accessible to and usable by as many people as possible, regardless of their income, social situation or age; and to help policy makers formulate long-term strategies that promote innovation in transport while responding to global social, demographic and economic changes, including the challenges of poverty and migration.The missionBy focusing on and involving end-users throughout the process of designing policies, products, or services, it is possible to reduce social exclusion while boosting new business models and social innovation. The end result that DIGNITY is aiming for is an innovative decision support tool that can help local and regional decision-makers formulate digitally inclusive policies and strategies, and digital providers design more inclusive products and services.The approachThe DIGNITY approach combines analysis with concrete actions to make digital mobility services inclusive over the long term. The approach connects users’ needs and requirements with the provision of mobility services, and at the same time connects those services to the institutional framework. It is a multi-phase process that first seeks to understand and bridge the digital gap, and then to test, evaluate and fine-tune the approach, so that it can be applied in other contexts even after the project’s end.Partners: ISINNOVA (Italy), Mobiel 21 (Belgium), Universitat Politechnica deCatalunya Spain), IZT (Germany), University of Cambridge (UK), Factualconsulting (Spain), Barcelona Regional Agencia (Spain), City of Tilburg(Netherlands), Nextbike (Germany), City of Ancona (Italy), MyCicero (Italy),Conerobus (Italy), Vlaams Gewest (Belgium)
This PD project explores alternative approaches to audiovisual technologies in art and creative practices by reimagining and reinventing marginalized and decommodified devices through Media Archaeology, artistic experimentation, and hands-on technical reinvention. This research employs Media Archaeology to uncover “obsolete” yet artistically relevant technologies and hands-on technical reinvention to adapt these tools for contemporary creative practices. It seeks to develop experimental self-built devices that critically engage with media materiality, exploring alternative aesthetic possibilities through practice-based investigations into the cultural and historical dimensions of media technologies. These developments provide artists with new creative possibilities beyond mainstream commercial standardized tools and infrastructures. A key component of this project is collaborative innovation with artist-run analog film communities, such as Filmwerkplaats. By fostering knowledge exchange and artistic experimentation, this research ensures that reinvented tools remain relevant to both analog film communities and contemporary media art practices. The intended outcomes directly benefit two key groups: • Artist-run film labs gain sustainable methods for evolving their practices, reducing dependence on scarce, out-of-production equipment. • Digital-native artists are introduced to alternative methods for engaging with analog processes and media materiality, expanding their creative toolkit. This collaboration also strengthens art and design education by embedding alternative technological perspectives and research methodologies into curricula, providing students and practitioners with resourceful, sustainable approaches to working with technology. It advocates for a more diverse educational paradigm that incorporates media-technological history and critical reflection on the ideologies of linear technological progress. Ultimately, this research fosters critical discourse on media culture, challenges the dominance of corporate proprietary systems, and promotes innovation, redefining the relationship between creativity and technology.