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Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH)
Date du début: 1 juin 2015, Date de fin: 30 nov. 2020 PROJET  EN COURS 

The problem: finding the right patient for the right treatmentDespite a large and growing disease burden in osteoarthritis (OA), many pharmaceutical companies have de-emphasized or even abandoned OA drug development due to perceived hurdles. Crucial in this is the lack of appropriate outcome measures that can robustly identify patient benefit from a specific therapy. The lack of specific and sensitive endpoints to differentiate between responders and non-responders both at the level of pain and tissue structure modification (disease modifying OA drug: DMOAD) has led to trials that included hundreds of patients in each arm with at least 3-years follow-up. Even despite these enormous trials, EMA and FDA have not approved any DMOAD yet. There is a general lack of understanding OA pathogenesis, which appears rather variable and likely reflecting different phenotypes with fundamental differences in disease aetiology, tissue alterations, clinical manifestations (pain/mobility) and disease progression. Although the current mind-set for drug treatment in the field is moving to a more personalized medicine and patient stratification approach, there are no accepted methods or guidelines to classify patients according to their prognosis and differentiate between subsets in terms of diagnosis methodology and treatment plan. The APPROACH consortium brings together a competent and multidisciplinary group of stakeholders that will setup – for the first time – a longitudinal cohort based on highly innovative stratification methods that identifies different OA phenotypes and subsequently develop guidelines for differentially diagnosing the right patient for the right treatment.The stratified medicine APPROACH The APPROACH consortium brings together a unique complimentary set of skills to develop, validate and link biomarkers with biological processes and clinical end points in OA patient subsets. This will support future regulatory qualification and guide clinical trials for relevant endpoint validation, thereby paving the road for stratified or personalized medicine. This leads to the following overall objectives of the consortium:- Implement and establish a new, integrated and comprehensive database platform of existing data from partners that will be extended with newly collected longitudinal data, incorporating novel high quality biomarkers.- Define subsets of (phenotypically) different patients in both the existing cohorts as well as (later) in the new longitudinal extension cohorts and subsequently identify the “right patient” to treat for each subset/phenotype via innovative stratification techniques. - Optimize, introduce and validate the next generation imaging methodologies (modality + post-processing), human motion analysis and biochemical assays to enable more efficient and reliable diagnoses and treatment of OA patients. - Identify mechanistic targets for patient subsets, create prediction models and establish guidelines for a DMOAD development that forms the roadmap for OA.APPROACH: a tri-partite partnership between relevant stakeholdersThe ambitious objectives of the APPROACH consortium require the mobilization of a broad set of skills and extensive expertise, from academics, clinicians and the private sector. The APPROACH consortium brings together a strong tri-partite team from European clinical centers (cohorts), basic research institutes (state-of-the-art tools) and SME/Industry (certified tool analyses and logistics) which also collaborate with large US-based OAI and MOST cohorts. This group is engaged with end users in hospitals and patient advocacy groups actively involved in OA awareness, fundraising and research support. The consortium crosses barriers and enables inter-sectorial collaborations that bring together all the expertise and knowledge in one place, where the information can be seamlessly integrated and, as such, contributes to innovative stratification and personalized diagnostic methods

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