Hybrid
e-cohorts
combine 1,2,3 or 4 data sources on an agile digital platform as to enhance credibility and study robustness.
... and to provide outcomes sooner to all stakeholders.
Combine various data sources
with an agile and secure digital platform
Adaptive scheduling
Personalized ePRO
Smart reminders via SMS | email
Advanced CRF multi-lingual interface and storage
Quick inclusion mode
Insights and alerts (optional)
Environmental or disease activity tracker
Machine learning processing (1)
Approved SNDS (France) services supplier
In-house senior data expert
(1) Gossec L, Guyard F, Leroy D, el Al. Patient-Reported Flares Were Correctly Predicted By an Algorithm Using Machine-Learning Statistics on Activity Tracker Data on Steps, in a Longitudinal 3-Month Study of 170 Patients with Rheumatoid Arthritis (RA) or Axial Spondyloarthritis (axSpA) [abstract]. Arthritis Rheumatol. 2017; 69 (suppl 10)
browse e-poster (2017)
Enhance credibility and study robustness
and provide outcomes sooner to all stakeholders
Investigators
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Ease trial onboarding
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Increased inclusions
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Real-time insights
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Reduced data collection effort
Sponsor
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Lower attrition rate (1)
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Better follow-up
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More exploitable data
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CRO-operated patient assistance
(1) 93% follow-up at M24 (n=3000) for active patients (70% in ITT) for I-CARE study
funder
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Cost optimization
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Trials that stand out
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Earlier publication opportunities
Digital CRO
(2) Satisfaction score of 8.33/10 by project managers across our studies in sept. 2019
