Resources & Training

Abstract:
The OpenRiskNet case studies (originally outlined in Deliverable 1.3) were developed to demonstrate the modularised application of interoperable and interlinked workflows. These workflows were designed to address specific aspects required to inform on the potential of a compound to be toxic to humans and to eventually perform a risk assessment analysis. While each case study targets a specific area including data collection, kinetics modelling, omics data and Quantitative Structure Activity Relationships (QSAR), together they address a more complete risk assessment framework. Additionally, the modules here are fine-tuned for the utilisation and application of new approach methodologies (NAMs) in order to accelerate the replacement of animals in risk assessment scenarios. These case studies guided the selection of data sources and tools for integration and acted as examples to demonstrate the OpenRiskNet achievements to improve the level of the corresponding APIs with respect to harmonisation of the API endpoints, service description and semantic annotation.

Abstract:
This case-study demonstrates and documents the use of a web interface to physiologically-based pharmacokinetic models for forward and reverse dosimetry calculations. Forward calculations compute internal concentrations from given exposure doses. Reverse calculations compute exposure doses from internal concentrations or measured biomarker levels (e.g., urine concentration data). The result of those calculations can be used in risk assessments to help with in vitro to in vivo extrapolations or interspecies extrapolations. Three tools have been developed for this case-study at NTUA and have been integrated into the OpenRiskNet infrastructure through the Jaqpot web-based computational platform. More specifically, the popular high-throughput toxicokinetic (httk) R package and the PKSim software tool for whole-body physiologically based pharmacokinetic modeling were integrated, but we also developed infrastructure for developing and deploying user-defined model. For each of these three web tools, simulations are performed and results are presented for reference chemicals or drugs, namely Imazalil for the httk model, Diazepam and Chlorpyrifos for showcasing the In-house R PBPK workflow and Theophylline for the PKSim model. The exposure scenarios chosen are in the range of corresponding environmental or therapeutic levels.

Abstract:
OpenRiskNet (https://openrisknet.org/) is a 3-year project funded by the EU within Horizon 2020 EINFRA-22-2016 Programme, with the main objective to develop an open e-infrastructure providing data and software resources and services to a variety of industries requiring risk assessment (e.g. chemicals, cosmetic ingredients, pharma or nanotechnologies). The infrastructure is built on virtual research environments (VREs), which can be deployed to workstations as well as public and in-house cloud infrastructures. Services providing data, data analysis, modelling and simulation tools for risk assessment are integrated into the e-infrastructure and can be combined into workflows using harmonised and interoperable application programming interfaces (APIs) (https://openrisknet.org/e-infrastructure/services/). For complete risk assessment and safe-by-design studies, OpenRiskNet e-infrastructure functionality is combined via a variety of incorporated services demonstrated within a set of case studies (see figure 1). The case studies present real-world settings such as data curation, systems biology approaches for grouping compounds, read-across applications using chemical and biological similarity, and identification of areas of concern based only on alternative methods (non-animal testing) approaches. OpenRiskNet is working with a network of partners, organised within an Associated Partners Programme, aiming to strengthen the working ties to other organisations developing relevant solutions or tools.

Abstract:
The aim of this study is to benchmark two Bayesian software tools, namely Stan and GNU MCSim, that use different Markov chain Monte Carlo (MCMC) methods for the estimation of physiologically based pharmacokinetic (PBPK) model parameters. The software tools were applied and compared on the problem of updating the parameters of a Diazepam PBPK model, using time-concentration human data. Both tools produced very good fits at the individual and population levels, despite the fact that GNU MCSim is not able to consider multivariate distributions. Stan outperformed GNU MCSim in sampling efficiency, due to its almost uncorrelated sampling. However, GNU MCSim exhibited much faster convergence and performed better in terms of effective samples produced per unit of time.

Abstract:
OpenRiskNet case studies are used to test and evaluate solutions provided by the project to the predictive toxicology and risk assessment community, especially regarding the usability of the developed Application Programming Interfaces (APIs) and the interoperability layer. These case studies will demonstrate the capabilities to satisfy the requirements of the different stakeholder groups, including researchers, risk assessors and regulators and present real-world applications such as systems biology approaches for grouping compounds, read-across applications using chemical and biological similarity, and identifying areas of concern based on in vitro and in silico approaches for compounds lacking any previous knowledge from animal experiments (ab initio case).

Abstract:
OpenRiskNet (https://openrisknet.org/) is an EU funded infrastructure project with the main objective to develop an open e-infrastructure providing resources and services to a variety of industries requiring risk assessment, including chemicals, cosmetic ingredients, drugs and nanomaterials. The OpenRiskNet approach is to work on different case studies to test and evaluate requirements to overcome the fragmentation of data and tools and to provide solutions improving the harmonization of data, usability and interoperability of application programming interfaces (APIs) and the deployment into virtual infrastructure. The cases present real-world settings such as systems biology approaches for grouping compounds, read-across applications using chemical and biological similarity, and identifying areas of concern based only on alternative methods approaches. We discuss our progress on the OpenRiskNet goal of harmonizing data and metadata within APIs that can be added to already existing analysis and modeling services and data warehouses. We also demonstrate how these APIs can easily be used towards the generation of full risk assessment workflows either using scripting languages or workflow managers. Finally, we show the first approaches to make these APIs semantically rich by annotating data with human- and computer-readable data schemata. OpenRiskNet has initiated the Associated Partners Programme strengthening the working ties between the OpenRiskNet members and other organizations within the scientific community.

Abstract:
OpenRiskNet (https://openrisknet.org/) is an EU funded infrastructure project with the main objective to develop an open e-infrastructure providing resources and services to a variety of industries requiring risk assessment, including chemicals, cosmetic ingredients, drugs and nanomaterials. The OpenRiskNet approach is to work on different case studies to test and evaluate requirements to overcome the fragmentation of data and tools and to provide solutions improving the harmonization of data, usability and interoperability of application programming interfaces (APIs) and the deployment into virtual infrastructure. The cases present real-world settings such as systems biology approaches for grouping compounds, read-across applications using chemical and biological similarity, and identifying areas of concern based only on alternative methods approaches.