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MODELING THE EXPECTATIONS FOR IMPROVEMENT IN OSTEOARTHRITIS TRIALS TO ENHANCE MANAGEMENT STRATEGIES
Objective: The expectations of improvement among subjects participating in a Randomized Controlled Trials (RCT) are one of the…
Using aggregated site features computed with the MPsQ to allow a better monitoring of sites in clinical trials
Using aggregated site features computed with the MPsQ to allow a better monitoring of sites in clinical trials…
Using Artificial Intelligence-based Methods to Address the Placebo Response in Clinical Trials
Cognivia team members contribute critical elements to a recent paper published in Innovations in Clinical Neuroscience. Cognivia co-authored a…
Accounting for the high reduction of power due to floor effect in design of randomised controlled trials
Purpose Outcomes in Randomized Controlled Trials (RCT) are often computed as changes from baseline of finite scales (e.g.,…
Leveraging historical data to optimize the number of covariates and their explained variance in the analysis of randomized clinical trials
The amount of data collected from patients involved in clinical trials is continuously growing. All baseline patient characteristics…
Impact of excluding highly variable pain subjects on the treatment estimation
The baseline pain variability (BPV) has often been presented as positively correlating with the placebo response (PR) and…
The next frontier in clinical research & patient management
We’re proud to be leading the charge into the next era of drug development.
Cognivia helps clinical trials reduce data variability, empower decision-making, and accelerate the launch of new therapies.
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