Periodic Reporting for period 5 - eTRANSAFE (Enhacing TRANslational SAFEty Assessment through Integrative Knowledge Management)
Période du rapport: 2021-09-01 au 2023-02-28
The eTRANSAFE project aimed to improve the efficiency of translational safety assessment during the drug discovery and development pipeline. The specific objectives are:
1. Identification and analysis of differences in the mechanisms of toxicity between different species, to increase the ability of preclinical computational, in vitro and in vivo studies to predict clinical outcomes.
2. To use the knowledge gained by use of these analyses to redesign preclinical testing and have an impact on animal welfare, as well as time and cost reductions in drug development.
3. To develop a sustainable business plan for promoting the wide adoption of the eTRANSAFE tools and methodologies, ensuring long-term success beyond the grant period.
In order to achieve these objectives, the eTRANSAFE project has focused on 4 key areas: Data, Analysis, System Architecture and Influence/Integration
Data:
1. To implement a toolkit for importing, managing and exporting preclinical data in SEND format and complementing the standard SEND format with additional safety information not currently captured in current SEND files.
2. To apply technological and organisational procedures for optimising IPR protection for the data provided by EFPIA companies (including an experienced partner acting as “honest broker”).
3. To achieve seamless integration of information by federation of data repositories and interoperability services.
Analysis:
1. To build multi-stage and multi-scale models based on quantitative Adverse Outcome Pathway (AOP) networks for hazard prediction.
2. To integrate PBPK models to predict exposure and provide risk assessment.
3. To develop and implement tools supporting the identification and analysis of differences in the mechanisms of toxicity between different species, to increase the ability of preclinical studies to predict clinical outcomes.
System Architecture:
1. To establish strategies and tools (including ontologies), for the gathering, QC and integration of data (private and public; preclinical and clinical) relevant for translational safety assessment.
2. To implement a highly flexible and adaptive information technology architecture, suitable for running in internal and external computing environments, able to be easily adapted to evolving user requirements and technological progress.
3. To apply a modular software design supporting the independent development of computational tools as self-contained components and their delivery as integrated and customisable applications.
4. To develop an ecosystem of applications for exploiting the aforementioned data infrastructure, including methods and tools for read-across, visualisation and analysis, biomarkers discovery, translational analysis and predictive modelling.
5. To implement iterative software development strategies involving the end users in the design and testing of the applications from very early stages.
Influence:
1. To establish synergies with other key projects in the field.
2. To create and mobilise a network of stakeholders and contributors through the setup of forums for scientific discussion and clear mechanisms for channelling contributions.
3. To liaise with regulators and other authorities for the elaboration of data sharing guidelines.
1. Identification and analysis of differences in the mechanisms of toxicity between different species, to increase the ability of preclinical computational, in vitro and in vivo studies to predict clinical outcomes.
2. To use the knowledge gained by use of these analyses to redesign preclinical testing and have an impact on animal welfare, as well as time and cost reductions in drug development.
3. To develop a sustainable business plan for promoting the wide adoption of the eTRANSAFE tools and methodologies, ensuring long-term success beyond the grant period.
In order to achieve these objectives, the eTRANSAFE project has focused on 4 key areas: Data, Analysis, System Architecture and Influence/Integration
Data:
1. To implement a toolkit for importing, managing and exporting preclinical data in SEND format and complementing the standard SEND format with additional safety information not currently captured in current SEND files.
2. To apply technological and organisational procedures for optimising IPR protection for the data provided by EFPIA companies (including an experienced partner acting as “honest broker”).
3. To achieve seamless integration of information by federation of data repositories and interoperability services.
Analysis:
1. To build multi-stage and multi-scale models based on quantitative Adverse Outcome Pathway (AOP) networks for hazard prediction.
2. To integrate PBPK models to predict exposure and provide risk assessment.
3. To develop and implement tools supporting the identification and analysis of differences in the mechanisms of toxicity between different species, to increase the ability of preclinical studies to predict clinical outcomes.
System Architecture:
1. To establish strategies and tools (including ontologies), for the gathering, QC and integration of data (private and public; preclinical and clinical) relevant for translational safety assessment.
2. To implement a highly flexible and adaptive information technology architecture, suitable for running in internal and external computing environments, able to be easily adapted to evolving user requirements and technological progress.
3. To apply a modular software design supporting the independent development of computational tools as self-contained components and their delivery as integrated and customisable applications.
4. To develop an ecosystem of applications for exploiting the aforementioned data infrastructure, including methods and tools for read-across, visualisation and analysis, biomarkers discovery, translational analysis and predictive modelling.
5. To implement iterative software development strategies involving the end users in the design and testing of the applications from very early stages.
Influence:
1. To establish synergies with other key projects in the field.
2. To create and mobilise a network of stakeholders and contributors through the setup of forums for scientific discussion and clear mechanisms for channelling contributions.
3. To liaise with regulators and other authorities for the elaboration of data sharing guidelines.
The highlights of the project include:
- Development of the revolutionary eTRANSAFE ToxHub platform, and its software pieces, which brings together preclinical and clinical databases in an integrative data infrastructure, combined with innovative computational and visualisation tools.
- The sustainability of ToxHub and other project results has been ensured through a two-fold approach, comprehending both public and private intake of project assets.
- Close to 200 dissemination activities, of which 44 are peer-reviewed articles.
- Development of project guidelines for sharing of preclinical safety data between industry/academia and guidelines for safety model validation.
- Development of a strategy for EFPIA legacy preclinical data donation and of data transformation rules for non-SEND legacy preclinical study data to SEND-like data format
- Collection of legacy, SEND, off-target and withdrawn drugs data as well as clinical data
- Development of an annotated textmining corpus and PreToxTM textmining tool
- Development of the Study Report (SR) Domain concept, a critical target structure for holding Text Mining results, and the creation of an Editor desktop application for creating /reviewing / editing study SR-Domain files.
- Development of the Rosetta Stone concept for bridging the gap between preclinical and clinical data vocabularies, by aligning and harmonising different terminologies through ontology mapping
- Development of the Flame modelling framework, allowing to implement models and tools as self-contained modules which can be integrated within the software platform.
The tools developed in the project have been incorporated into the R&D pipeline of most of the participating companies.
The public project results can be found at: https://cordis.europa.eu/project/id/777365/results and https://etransafe.eu/publicly-accessible-results/
- Development of the revolutionary eTRANSAFE ToxHub platform, and its software pieces, which brings together preclinical and clinical databases in an integrative data infrastructure, combined with innovative computational and visualisation tools.
- The sustainability of ToxHub and other project results has been ensured through a two-fold approach, comprehending both public and private intake of project assets.
- Close to 200 dissemination activities, of which 44 are peer-reviewed articles.
- Development of project guidelines for sharing of preclinical safety data between industry/academia and guidelines for safety model validation.
- Development of a strategy for EFPIA legacy preclinical data donation and of data transformation rules for non-SEND legacy preclinical study data to SEND-like data format
- Collection of legacy, SEND, off-target and withdrawn drugs data as well as clinical data
- Development of an annotated textmining corpus and PreToxTM textmining tool
- Development of the Study Report (SR) Domain concept, a critical target structure for holding Text Mining results, and the creation of an Editor desktop application for creating /reviewing / editing study SR-Domain files.
- Development of the Rosetta Stone concept for bridging the gap between preclinical and clinical data vocabularies, by aligning and harmonising different terminologies through ontology mapping
- Development of the Flame modelling framework, allowing to implement models and tools as self-contained modules which can be integrated within the software platform.
The tools developed in the project have been incorporated into the R&D pipeline of most of the participating companies.
The public project results can be found at: https://cordis.europa.eu/project/id/777365/results and https://etransafe.eu/publicly-accessible-results/
The overall goal of eTRANSAFE was to develop and implement a new generation of operational approaches and computational applications for a more efficient drug safety assessment. The results and expected impacts include:
Development of the ToxHub platform which drastically improves the predictivity, feasibility and reliability of translational safety assessment during the drug development process.
Contribution to the application of the 3Rs (Replacement, Reduction, Refinement) principles for more ethical use of animals in research:
- Development of a Virtual Control Group concept that could help to replace up to 25% of the animals currently used in toxicity studies by means of data sharing.
- Collaboration with NC3Rs as a data provider for the CRACK IT Challenge: https://nc3rs.org.uk/crackit/virtual-second-species
- Development of Model verification guidelines.
Three white papers have been published on data/model FAIRification for sustainability and research reproducibility:
- Guidelines for FAIR sharing of preclinical safety and off-target pharmacology data. ALTEX. 2021;38(2):187-197.
- eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain. F1000Res. 2022;11:ELIXIR-287.
- Making in silico predictive models for toxicology FAIR. Regul Toxicol Pharmacol. 2023;140:105385.
The project has also accomplished the aim of converting historical data into the SEND format as well as to collect, organize and standardize a large body of SEND data sets, allowing larger analysis of preclinical data across pharma archives with the aim of delivering a holistic, integrated preclinical data platform that facilitates the development of translational models and read across, thus improving the power of translational analysis. This, along with the collection of clinical data, allowing the cross analysis of both data types, implies an enormous step towards enhancing drug safety assessment.
Lastly, a common project paper entitled eTRANSAFE: data science to empower translational safety assessment was published in the journal Nature Reviews Drug Discovery (https://pubmed.ncbi.nlm.nih.gov/37316648/) providing an overview on how data sharing by the pharma industry within eTRANSAFE has helped to enhance translational drug safety assessment.
Development of the ToxHub platform which drastically improves the predictivity, feasibility and reliability of translational safety assessment during the drug development process.
Contribution to the application of the 3Rs (Replacement, Reduction, Refinement) principles for more ethical use of animals in research:
- Development of a Virtual Control Group concept that could help to replace up to 25% of the animals currently used in toxicity studies by means of data sharing.
- Collaboration with NC3Rs as a data provider for the CRACK IT Challenge: https://nc3rs.org.uk/crackit/virtual-second-species
- Development of Model verification guidelines.
Three white papers have been published on data/model FAIRification for sustainability and research reproducibility:
- Guidelines for FAIR sharing of preclinical safety and off-target pharmacology data. ALTEX. 2021;38(2):187-197.
- eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain. F1000Res. 2022;11:ELIXIR-287.
- Making in silico predictive models for toxicology FAIR. Regul Toxicol Pharmacol. 2023;140:105385.
The project has also accomplished the aim of converting historical data into the SEND format as well as to collect, organize and standardize a large body of SEND data sets, allowing larger analysis of preclinical data across pharma archives with the aim of delivering a holistic, integrated preclinical data platform that facilitates the development of translational models and read across, thus improving the power of translational analysis. This, along with the collection of clinical data, allowing the cross analysis of both data types, implies an enormous step towards enhancing drug safety assessment.
Lastly, a common project paper entitled eTRANSAFE: data science to empower translational safety assessment was published in the journal Nature Reviews Drug Discovery (https://pubmed.ncbi.nlm.nih.gov/37316648/) providing an overview on how data sharing by the pharma industry within eTRANSAFE has helped to enhance translational drug safety assessment.