Obiettivo
The problem: finding the right patient for the right treatment
Despite 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 stakeholders
The 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
Campo scientifico
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
- medical and health sciencesbasic medicinepharmacology and pharmacydrug discovery
- natural sciencescomputer and information sciencesdatabases
- natural sciencescomputer and information sciencesartificial intelligencecomputer visionmotion analysis
- medical and health scienceshealth sciencespersonalized medicine
Argomento(i)
Invito a presentare proposte
IMI-JU-11-2013
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Meccanismo di finanziamento
JTI-CP-IMI - Joint Technology Initiatives - Collaborative Project (IMI)Coordinatore
WC1A 1DG LONDON
Regno Unito
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Partecipanti (24)
3584 CX Utrecht
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3521 AL Utrecht
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22100 LUND
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1090 Wien
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NE1 7RU Newcastle Upon Tyne
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91054 Erlangen
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91054 Erlangen
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4000 Liège (Sart-Tilman)
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5611 ZT EINDHOVEN
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LS2 9JT Leeds
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1056 AA AMSTERDAM
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2333 ZA Leiden
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GU2 7XH Guildford
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15703 Santiago De Compostela
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75012 Paris
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0319 Oslo
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NE35 9PD Boldon
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LU1 1QZ Luton
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ST41 7TD Chesterfield
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91190 GIF-SUR-YVETTE
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64293 DARMSTADT
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2730 Helev
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75794 Paris
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60064 North Chicago Il
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