Periodic Reporting for period 3 - OPTIMA (Optimal treatment for patients with solid tumours in Europe through Artificial intelligence)
Okres sprawozdawczy: 2023-10-01 do 2024-09-30
OPTIMA is a multi-stakeholder-led consortium with the vision that each and every patient should have access to the most up-to-date individualised treatments and to innovative therapies. In that perspective, we will design, develop and deliver the first interoperable and GDPR compliant European real-world oncology data and evidence generation platform, along with decision support toolsets for prostate, lung and breast cancer. By designing this platform from the onset based on the needs of the clinicians and patients in an inclusive and sustainable way, OPTIMA aims to strengthen shared decision-making based on innovative data and AI-driven technology and tools.
To achieve our vision, we have united the key partners from other data-driven European wide oncology initiatives (PIONEER, EHDEN, HARMONY) in our project along with Europe's leading clinicians in the fields of breast, prostate and lung cancer that all have leading roles in medical societies such as ERS, ESMO, and EAU. At the core of the OPTIMA project are the major guideline offices of the three indications, whilst the project is further strengthened by patient advocacy groups, well-known academic partners and 6 SMEs as partners covering the needed expertise to implement OPTIMA successfully. The platform will build on existing open source solutions such as the OMOP-CDM, tranSMART and OHDSI ATLAS whilst developing novel AI models based on federated learning to facilitate knowledge discovery. At the start of the project, we will already have access to datasets covering over 200M people in Europe, along with data from high quality patient cohorts for AI model building. Moreover, the platform will be hosted in-kind on existing infrastructure provided by Helmholtz Institute in Germany. Finally, OPTIMA envisions sustainability of its platform through a value-based approach with various business models for commercial users.
To achieve our vision, we have united the key partners from other data-driven European wide oncology initiatives (PIONEER, EHDEN, HARMONY) in our project along with Europe's leading clinicians in the fields of breast, prostate and lung cancer that all have leading roles in medical societies such as ERS, ESMO, and EAU. At the core of the OPTIMA project are the major guideline offices of the three indications, whilst the project is further strengthened by patient advocacy groups, well-known academic partners and 6 SMEs as partners covering the needed expertise to implement OPTIMA successfully. The platform will build on existing open source solutions such as the OMOP-CDM, tranSMART and OHDSI ATLAS whilst developing novel AI models based on federated learning to facilitate knowledge discovery. At the start of the project, we will already have access to datasets covering over 200M people in Europe, along with data from high quality patient cohorts for AI model building. Moreover, the platform will be hosted in-kind on existing infrastructure provided by Helmholtz Institute in Germany. Finally, OPTIMA envisions sustainability of its platform through a value-based approach with various business models for commercial users.
WP1: Project Management – WP1 actively monitors the progress and identifies and mitigates any potential risks for the project. WP1 also delivered the periodic reports and organises annual face-to-face consortium meetings.
WP2: Informed consent, general requirement analysis, governance, and regulation – The WP has assessed the legal and ethical framework of the project, as well as the data protection impact, which serve as important prerequisites for any further work within the OPTIMA project. The Art. 26/28 agreements have been drafted and signed by all beneficiaries. WP2 has supported in drafting the regulatory plan for OPTIMA and is now finalising the external data sharing agreements.
WP3: Guideline-based decision support tool – The WP has identified and prioritised critical research questions through Delphi surveys with key opinion leaders and stakeholders, and selected typical case presentations for prostate, breast and lung cancer, which will serve as the basis for the development of the guideline-based decision support tool. Currently, WP3 is further developing the GBDST to include lung and breast cancer and preparing for an in silico trial to assess guideline adherence.
WP4: Platform technical and infrastructural requirement analysis – The WP has created an initial data management plan, provided an updated version of the data management plan, assessed the requirements and specifications of the platform, and worked on the development environment. Several versions of the platform have been developed and released in collaboration with the other technical WPs.
WP5: Platform implementation and evaluation – The WP has identified the user personas and have implemented several successive versions of the platform in the technical testing sites and clinical sites. WP5 is evaluating the platform on an ongoing basis. The WP will continuously search for additional sites where new versions can be tested.
WP6: (Non)interventional study data and real-world data gathering, preparation and integration – The WP has been mapping potential datasets, designed the architecture of federated nodes and decided on the common data model approach used. This WP has developed a fingerprinting questionnaire to assess the data governance, helped in the design of the architecture of the federated notes, assessed the security of data AI-models, organized trainings on semi-automated tools for OMOP-mapping, and decided on a strategy to convert datasets from the consortium partners into OMOP. Recently, WP6 developed the OPTIMA data catalogue.
WP7: Artificial intelligence knowledge base implementation – The WP has investigated the use of synthetic data, assessed available AI/ML models, explored options for federated learning and started the work around NLP. WP7 has developed an overview of the state of the art for AI models in the three cancer types investigated in OPTIMA and has started the development of a prototype AI model relevant to answer research questions that can benefit from automatic analysis of imaging data. WP7 has also provided input to assess the impact of AI both for answering the research questions as well as business cases for the sustainability of OPTIMA. In terms of infrastructure, collection of AI models and a working CI/CD environment are now set up. WP7 has developed several AI models, which are in the process of being quality assessed.
WP8: Dissemination and communication – focuses on dissemination and communication of the project’s aims, approach and results, strengthening stakeholder engagement. The WP has established the house-style, developed templates and manages OPTIMA social media accounts. WP8 have created a network with relevant stakeholders and are creating new communication materials on an ongoing basis.
WP9: Exploitation and sustainability of the results – aims to build a sound and solid business strategy to exploit and commercialize the platform and the guideline decision support tool beyond the grant period. The WP has conducted interviews to assess scientific requirements, benchmarked potential business models and defined models for commercialization. WP9 has collaborated with the other WPs and conducted workshops and held meetings to further define a sustainable model for OPTIMA.
WP2: Informed consent, general requirement analysis, governance, and regulation – The WP has assessed the legal and ethical framework of the project, as well as the data protection impact, which serve as important prerequisites for any further work within the OPTIMA project. The Art. 26/28 agreements have been drafted and signed by all beneficiaries. WP2 has supported in drafting the regulatory plan for OPTIMA and is now finalising the external data sharing agreements.
WP3: Guideline-based decision support tool – The WP has identified and prioritised critical research questions through Delphi surveys with key opinion leaders and stakeholders, and selected typical case presentations for prostate, breast and lung cancer, which will serve as the basis for the development of the guideline-based decision support tool. Currently, WP3 is further developing the GBDST to include lung and breast cancer and preparing for an in silico trial to assess guideline adherence.
WP4: Platform technical and infrastructural requirement analysis – The WP has created an initial data management plan, provided an updated version of the data management plan, assessed the requirements and specifications of the platform, and worked on the development environment. Several versions of the platform have been developed and released in collaboration with the other technical WPs.
WP5: Platform implementation and evaluation – The WP has identified the user personas and have implemented several successive versions of the platform in the technical testing sites and clinical sites. WP5 is evaluating the platform on an ongoing basis. The WP will continuously search for additional sites where new versions can be tested.
WP6: (Non)interventional study data and real-world data gathering, preparation and integration – The WP has been mapping potential datasets, designed the architecture of federated nodes and decided on the common data model approach used. This WP has developed a fingerprinting questionnaire to assess the data governance, helped in the design of the architecture of the federated notes, assessed the security of data AI-models, organized trainings on semi-automated tools for OMOP-mapping, and decided on a strategy to convert datasets from the consortium partners into OMOP. Recently, WP6 developed the OPTIMA data catalogue.
WP7: Artificial intelligence knowledge base implementation – The WP has investigated the use of synthetic data, assessed available AI/ML models, explored options for federated learning and started the work around NLP. WP7 has developed an overview of the state of the art for AI models in the three cancer types investigated in OPTIMA and has started the development of a prototype AI model relevant to answer research questions that can benefit from automatic analysis of imaging data. WP7 has also provided input to assess the impact of AI both for answering the research questions as well as business cases for the sustainability of OPTIMA. In terms of infrastructure, collection of AI models and a working CI/CD environment are now set up. WP7 has developed several AI models, which are in the process of being quality assessed.
WP8: Dissemination and communication – focuses on dissemination and communication of the project’s aims, approach and results, strengthening stakeholder engagement. The WP has established the house-style, developed templates and manages OPTIMA social media accounts. WP8 have created a network with relevant stakeholders and are creating new communication materials on an ongoing basis.
WP9: Exploitation and sustainability of the results – aims to build a sound and solid business strategy to exploit and commercialize the platform and the guideline decision support tool beyond the grant period. The WP has conducted interviews to assess scientific requirements, benchmarked potential business models and defined models for commercialization. WP9 has collaborated with the other WPs and conducted workshops and held meetings to further define a sustainable model for OPTIMA.
Our vision is that every patient should have access to the most up-to-date individualised treatments and to innovative therapies. By strengthening shared decision-making based on dynamic computer-interpretable guidelines (CIGs), innovative broad data access and AI-driven technology and tools, we envision revolutionizing oncology care in Europe. This vision is realized by building the first interoperable and GDPR-compliant real-world-oncology data and evidence generation platform based on the needs of the clinicians and patients, and a comprehensive decision support toolsets based on national and international guidelines with approved regular updates of guideline recommendations underpinned by evidence from advanced statistical analysis and AI. Our ambition is to scale up OPTIMA to a pan-European level collaborating with national and international medical societies’ guidelines addressing a paradigm shift in clinical research and treatment towards a more personalised medicine approach ensuring that each patient receives the best individualised treatment. We envision that the integration of individual patient data will enable personalised decisions in near real time while continuously enhancing the quality and capabilities of the platform provided.