Periodic Reporting for period 2 - EU-STANDS4PM (A European standardization framework for data integration and data-driven in silico models for personalized medicine)
Reporting period: 2020-07-01 to 2022-12-31
Currently there are no widely accepted, overarching strategies to harmonize (i) heterogeneous health and disease data and (ii) data-driven in silico approaches for the interpretation of Big Data to enable personalized medicine. In addition, data governance concerning the collection, share, access, storage, use, and re-use of data needs to be further developed and broadly implemented. What is lacking are standardization documents issued through e.g. the European Committee for Standardization, CEN or the International Organization for Standardization, ISO and recommendations for innovative data governance concepts, such as harmonized Data Access Agreements. This would allow for the exploitation of Big Data to develop true medical benefits for an individual patient or stratified patient groups. These exploitations, however, need to be based on a clear framework regarding legal, ethical, policy issues and certification for data-driven in silico models in personalized medicine.
A central task of EU-STANDS4PM was thus to develop harmonized standards as well as recommendations and guidelines for predictive data-driven in silico methodologies applied in personalized medicine with a focus on the following central aspects:
(1) To develop universal standards as well as recommendations for in silico methodologies applied in personalized medicine approaches.
(2) To provide guidance on the legal, ethical and policy considerations arising from data integration for in silico modelling for personalized medicine.
(3) To implement a pilot for an innovative framework for progressive dissemination for data access, sharing, dissemination for future collaborative EU research.
Taken together the above-summarized objectives will have a major impact on:
Collaborative research – Applying universal standards in research practice will improve the quality, reproducibility and sustainability of pre-clinical and translational projects that aim at implementing computational models in clinical routine in the future, e.g. to identify and reconstruct disease-driving mechanisms or to integrate such models in decision support systems for individualized prevention and treatment strategies.
Funders – National funding bodies, as well as the EU-Commission, will have an additional level of quality assurance if the use of normative documents for specific topics in future calls will be made mandatory for applicants. Especially the use of ISO-based normative documents will ensure that public funds are being invested based on international, quality ensured standards for state of the art scientific practice.
A central task of EU-STANDS4PM was thus to develop harmonized standards as well as recommendations and guidelines for predictive data-driven in silico methodologies applied in personalized medicine with a focus on the following central aspects:
(1) To develop universal standards as well as recommendations for in silico methodologies applied in personalized medicine approaches.
(2) To provide guidance on the legal, ethical and policy considerations arising from data integration for in silico modelling for personalized medicine.
(3) To implement a pilot for an innovative framework for progressive dissemination for data access, sharing, dissemination for future collaborative EU research.
Taken together the above-summarized objectives will have a major impact on:
Collaborative research – Applying universal standards in research practice will improve the quality, reproducibility and sustainability of pre-clinical and translational projects that aim at implementing computational models in clinical routine in the future, e.g. to identify and reconstruct disease-driving mechanisms or to integrate such models in decision support systems for individualized prevention and treatment strategies.
Funders – National funding bodies, as well as the EU-Commission, will have an additional level of quality assurance if the use of normative documents for specific topics in future calls will be made mandatory for applicants. Especially the use of ISO-based normative documents will ensure that public funds are being invested based on international, quality ensured standards for state of the art scientific practice.
WP1-Data sources and standards for predictions in personalized medicine:
-An assessment of international databases, collections and registries relevant to personalized medicine was performed.
-A collection of national and EU-case studies for integrating patient derived data, for in silico modelling in personalized medicine was assembled that discusses key topics associated with integrating patient derived data for in silico modelling in personalized medicine.
-An assessment on current projects and their use of data, standards and guidelines, as well as for their needs and gaps in standardisation was performed.
WP2-Integrative data analysis and in silico models in personalized medicine:
-The WP2 White Paper “Towards in silico approaches for personalised medicine – Recommendations for verifying and validating predictive computational models in EU collaborative research” was developed and published.
-The peer reviewed review article “Computational Models for Clinical Applications in Personalized Medicine—Guidelines and Recommendations for Data Integration and Model Validation” (Colin et al. 2022) has been published in the Journal of Personalized Medicine.
-Development of two ISO Technical Specifications (i) “Biotechnology — Computational models in personalised medicine research — Part 1: Guidelines for constructing, verifying and validating models” has been developed and submitted to the corresponding ISO Technical Committee for further development and publication as a normative international standard document.
(ii) — Part 2: Guidelines for implementing computational models in clinical integrated decision support systems” has been developed and submitted to the corresponding ISO Technical Committee for further development and publication as a normative international standard document.
Legal, ethical, policy issues and certification for data-driven in silico models in personalized medicine:
-A comprehensive analysis of the applicable EU, Council of Europe and international regulation of data protection, biomedical research/clinical trials and patients’ rights relevant for development of in silico modelling was published.
-An Analysis of technically feasible as well as legally and ethically sustainable avenues for harmonization/integration of big data of relevance for personalized medicine into in silico modelling was published.
-Comprehensive recommendations for technically feasible as well as legally and ethically sustainable avenues for harmonization/integration of big data of relevance for personalized medicine into in silico modelling were published.
WP4-Data access, outreach and governance:
-Development and implementation of a hDAA which is fully GDPR compliant and which was released to the public in Aug 2020 on the EGA and EU-STANDS4PM websites and announced on the CORDIS web site on 1st October 2020.
-Implementation of Registered Access including a three-stage registration process for Authentication, Attestation and Authorization, which ensures both user identification and agreement to a general set of responsibilities while considerably simplifying the data access application process.
-Completion of a case study to evaluate Cloud-based Access (CbA) of multi-omics data with the main result that multi-omics data can be made available on academic and commercial cloud-based platforms such as Seven Bridges CGC cloud, Lifebit cloud, Galaxy cloud for easy access and computing without the need to download the data, eliminating the data transfer step.
-The project specific website was launched and informational material about the project, including an animated video, was produced and disseminated.
-A number of dissemination events have been organized and successfully executed
-An assessment of international databases, collections and registries relevant to personalized medicine was performed.
-A collection of national and EU-case studies for integrating patient derived data, for in silico modelling in personalized medicine was assembled that discusses key topics associated with integrating patient derived data for in silico modelling in personalized medicine.
-An assessment on current projects and their use of data, standards and guidelines, as well as for their needs and gaps in standardisation was performed.
WP2-Integrative data analysis and in silico models in personalized medicine:
-The WP2 White Paper “Towards in silico approaches for personalised medicine – Recommendations for verifying and validating predictive computational models in EU collaborative research” was developed and published.
-The peer reviewed review article “Computational Models for Clinical Applications in Personalized Medicine—Guidelines and Recommendations for Data Integration and Model Validation” (Colin et al. 2022) has been published in the Journal of Personalized Medicine.
-Development of two ISO Technical Specifications (i) “Biotechnology — Computational models in personalised medicine research — Part 1: Guidelines for constructing, verifying and validating models” has been developed and submitted to the corresponding ISO Technical Committee for further development and publication as a normative international standard document.
(ii) — Part 2: Guidelines for implementing computational models in clinical integrated decision support systems” has been developed and submitted to the corresponding ISO Technical Committee for further development and publication as a normative international standard document.
Legal, ethical, policy issues and certification for data-driven in silico models in personalized medicine:
-A comprehensive analysis of the applicable EU, Council of Europe and international regulation of data protection, biomedical research/clinical trials and patients’ rights relevant for development of in silico modelling was published.
-An Analysis of technically feasible as well as legally and ethically sustainable avenues for harmonization/integration of big data of relevance for personalized medicine into in silico modelling was published.
-Comprehensive recommendations for technically feasible as well as legally and ethically sustainable avenues for harmonization/integration of big data of relevance for personalized medicine into in silico modelling were published.
WP4-Data access, outreach and governance:
-Development and implementation of a hDAA which is fully GDPR compliant and which was released to the public in Aug 2020 on the EGA and EU-STANDS4PM websites and announced on the CORDIS web site on 1st October 2020.
-Implementation of Registered Access including a three-stage registration process for Authentication, Attestation and Authorization, which ensures both user identification and agreement to a general set of responsibilities while considerably simplifying the data access application process.
-Completion of a case study to evaluate Cloud-based Access (CbA) of multi-omics data with the main result that multi-omics data can be made available on academic and commercial cloud-based platforms such as Seven Bridges CGC cloud, Lifebit cloud, Galaxy cloud for easy access and computing without the need to download the data, eliminating the data transfer step.
-The project specific website was launched and informational material about the project, including an animated video, was produced and disseminated.
-A number of dissemination events have been organized and successfully executed
One of the main impacts of a broad implementation of standardization guidelines to be proposed by EU-STANDS4PM for generating, secure storing, integrating and sharing of data will be the reproducibility of research findings and the ability to compare research results among different scientific, as well as health research communities. This will advance the relevant disciplines and enable rapid exchange of data and knowledge, therefore providing a solid platform for new ideas and research strategies. Within medical research, this will accelerate the detection of novel biomarkers for early detection and monitoring of disease progression and has potential for developing more cost/time efficient, clinical trials guided by the results of rational in silico approaches in personalized medicine.