Study Design Considerations for Digital Assessments in Parkinson’s Disease Clinical Trials
Disease-modifying therapy trials in Parkinson’s face a hard measurement problem. Progression is slow and variable, symptoms fluctuate day to day, and dopaminergic therapy adds noise on top. Consequently, detecting a treatment effect takes large samples and long timelines.
So how much does assessment frequency actually help? This poster answers that with simulation. Koneksa modeled one-year DMT trials across three designs, from conventional in-clinic visits to at-home bursts to weekly remote capture, using PD progression parameters drawn from PPMI data.
View the poster and supplement, or contact us to discuss digital assessment design for your Parkinson’s program.
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What You'll Learn
Sample sizes required for 80% power under each design, at both 90% and 50% drug efficacy
The point of diminishing returns, meaning where added assessments stop improving power
How much weekly at-home assessment reduces enrollment compared with in-clinic and burst designs
The Gaussian state space model and endpoint definitions behind the simulations
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