STRATA-FIT

Lead Beneficiary: Universitair Medisch Centrum Utrecht (UMCU)
WP1 is responsible for the project management and coordination of the project. This WP includes the overall executive, legal, financial, ethical, data, innovation, intellectual property, gender & inclusion and administrative management of the project. The Project Coordinator (Prof. Jaap van Laar, UMCU), the vice-coordinator (Dr Paco Welsing, UMCU), the Executive Board (consisting of the WP leaders and (vice) coordinator) and the ultimate decision-making General Assembly is supported by the Management Support Team. Such a team includes a professional and dedicated Project Manager for the full duration of the project and a Central Data Manager overseeing the compliance of data processing with local guidelines.

Lead Beneficiary: Karolinska Institutet (KI)
All clinical centres in STRATA-FIT either act as principal investigators for RA registry studies, have already or will obtain physical or analytical access to large complementary real-world (e.g. clinical practice based) and RA data sources. These data collections are longitudinal, and data is collected continuously. WP2 is responsible for the identification and collection of data from each clinical partner for the real-world RA cohort of the project.

Although partners may contribute longitudinal RA data, their internal structure and logic, use and choice of variables, formatting, timing of variable collections differ. Unaccounted for, these differences will hamper concerted analyses, especially fully federated analyses such as required in STRATA-FIT. Thus, WP2 will coordinate work to harmonise and pre-process partner-specific RA data to enable concerted analyses, as well as develop/validate specific common features over cohorts.

Lead Beneficiary: Universitair Medisch Centrum Utrecht (UMCU)
WP3 will develop and validate (computational/statistical) models that 1) predict when RA patients are D2T and 2) stratify D2T RA patients into clinically relevant phenotypes (subgroups with specific underlying problems e.g. inflammation, pain syndromes, comorbidity, mismatch of treatment goals, etc.). It will also develop and validate models to 3) identify RA patients early in the disease course (e.g., at diagnosis or after failing first line treatment before cycling second line treatment) at high risk for developing D2T RA.

Analyses will be made in collaboration with all partners contributing data for these, and will be performed within the project’s Federated Learning infrastructure (WP2).

To inform the modelling process and interpret the results of the analyses, a Consensus Board will be set-up. In the Consensus Board, all partners (as well as patient research partners) are represented and can have discussions on e.g., the choice of model types and variables/features to use as predictors, interpretation of results, suitability of predictive performance for decision making (in collaboration with WP4).

Lead Beneficiary: Medical University of Vienna (MUV)
WP4 specifically addresses the development and the establishment of a software called “Decision Aid”, capable of (a) identifying patients with D2T RA and (b) providing guidance on the treatments to consider in clinical practice.

WP4 will develop this Decision Aid software first by creating a personalised management algorithm based on (a) already existing EULAR Points-to-Consider for the management of D2T RA, (b) a comprehensive inventory of treatment options relevant to RA and (c) an algorithm defining D2T RA as informed by WP2 & 3.

In addition, WP4 will identify, based on existing datasets from clinical centres within the consortium, favourable treatment algorithms for patients with D2T RA.

A first version of the Decision Aid with basic functionality will be developed as proof-of-concept to validate its functionality and reliability. Then a second, final version with full functionality including suggestions for treatments will follow with the objective of being used in an intervention phase of a clinical study.

Lead Beneficiary: Universitair Medisch Centrum Utrecht (UMCU)
WP5 will develop a protocol for a pilot study (ACCESS-STRATA) for the evaluation of the feasibility, effectiveness and cost-effectiveness of a patient tailored treatment approach in D2T RA patients. It will use the Federated Learning infrastructure (WP2) and the STRATA-FIT decision aid (WP4) to 1) identify possible D2T RA patients, and 2) clinically confirm the information derived for final inclusion in the study, as well as 3) identify and confirm the specific D2T RA phenotype and propose a patient tailored treatment approach (WP4). Patients will be recruited in all participating clinical centres. The study will consist of two phases: an observation and an intervention phase and patients can participate in both phases of the study or only one of the phases. WP5 plans to include 175 patients in the observation phase and an extra ~88 patients in the intervention phase. The number of extra patients will depend on the drop-out rate from the observational phase.

Lead Beneficiary: Klinikum Der Universitat Munchen (KUM)
WP6 is responsible for establishing a biobank for (future) marker analyses to identify biomarkers that are 1) associated with the development of D2T RA; and/or 2) predictive for the development of D2T RA as well as distinct clinical profiles of D2T RA.

Therefore, WP6 will coordinate and harmonise the work of the different clinical partners recruiting patients for the biomarker study. It will perform a survey of available patient data, potentially relevant patient data and collection of this patient data among the partners. Finally, it will set-up a central biobank database and oversee biobanking and biomarker study for STRATA-FIT, according to developed standard operating procedures on biomarker collection and protocol.

Lead Beneficiary: Medical Data Works B.V. (MDW)
WP7 will develop computation models from real-world RA data that will be used to aid decision-making regarding personalised treatments for D2T RA patients. For these models to reach clinical practice, they need to be developed into medical devices which are subject to the Medical Device Regulation and must undergo a conformity assessment by an accredited notified body to demonstrate they meet legal requirements. Such requirements are to ensure the medical devices are safe and perform as intended. However, there is uncertainty as to what is needed to prove a computational model “is safe and performs as intended”. In recent years, regulatory agencies such as the FDA and the EMA, as well as the EU, are providing initial guidance. In addition, the use of real-world data for which no specific informed consent is obtained also presents challenges regarding anonymity/pseudonymity and privacy and needs to adhere to different regulations like the GDPR.

WP7 will perform tasks to ensure the activities in STRATA-FIT are conducted in a proven, high-quality, and ethical manner so that: the execution of the project adheres to all relevant regulations and its results are maximally prepared for conformity assessment after the project.

Lead Beneficiary: Instituto de Medicina Molecular João Lobo Antunes (iMM)
WP8 will ensure efficient and effective dissemination of project’s approaches, goals and results to stakeholders to maximise the impact of the STRATA-FIT project. The main tasks are the Stakeholder Analysis, elaboration of the Dissemination, Exploitation and Communication Plan, development of the Communication Toolkit and website and ensure proper communication of the project results.

In addition, WP8 is also responsible for coordinating and supporting the work of the STRATA-FIT Patient Advisory Panel, composed of patient research partners (PRPs) from the EULAR network. This panel will monitor project progress and provide patient input to tasks and deliverables across STRATA-FIT. Feedback from the panel will be used to ensure research activities are oriented to patients’ needs and promote successful translation of results to clinical practice.

Lead Beneficiary: Universitair Medisch Centrum Utrecht (UMCU)
The objective of this WP is to ensure compliance with the ‘ethics requirements’ set out in this work package.

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This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement no. 101080243 from the Swiss State Secretariat for Education, Research and Innovation (SERI) and from Hungary’s National Research, Development and Innovation (NRDI) Fund.
Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.