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Introducing Cognivia Signal: Early-Warning Behavioral Risk Intelligence for Clinical Trials
Cognivia launches the world’s first early-warning behavioral risk intelligence dashboard—Cognivia Signal—empowering clinical teams to see what’s coming before it happens. Mont-Saint-Guibert, Belgium – October 9, 2025 – Cognivia,…
Clarifying Treatment Effects Through Prognostic Adjustment
This page provides an interpretation of a clinical study evaluating roflumilast in post-stroke cognitive impairment. For the full scientific details including study design, statistical approach, and complete…
The effects of the PDF4 inhibitor roflumilast on cognitive performance after a cerebrovascular accident : A double-blind randomized placebo-controlled trial with an open label extension (ROSTMEMA).
Background Effective pharmacological treatments for Post-Stroke Cognitive Impairment (PSCI) remain elusive. Preclinical studies have shown that phosphodiesterase 4…
Why Better Data Now Matters More Than Better Tools
There comes a moment in every industry when the conversation subtly shifts. Not because a single breakthrough changes everything, but because long‑standing concerns finally converge into a…
The Behavioral Layer: An Overlooked Determinant of Clinical Success
Clinical research continues to evolve at an impressive pace. Digital technologies streamline data capture, biomarkers deepen biological insight, and innovative trial designs broaden access for diverse populations. These advances have unquestionably accelerated development and expanded participant reach. Still, across all this progress, one dimension consistently shapes…
Placebo response modelled by psychological characteristics in a remote osteoarthritis trial
Background Accurately characterizing placebo response is essential for improving sensitivity in osteoarthritis (OA) trials. This analysis investigates how…
Why Patient Retention Still Fails in Clinical Trials — And How Predictive Signals Can Help Ops Teams Anticipate Drop‑Out Earlier ?
Patient retention or patient engagement have become a main operational challenge in today’s clinical trials. Despite major investments in decentralized models, engagement tools, and site‑facing technology, patient drop‑out still catches clinical operations teams by surprise. And when it does, the impact on timelines, data quality, and…
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