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"Reduce control arm sizes by up to 35% for Alzheimer's disease"

RCTs with digital twins require fewer control patients and shorten trial timelines for Alzheimer's disease

Complex Alzheimer’s disease (AD) clinical trials require thousands of patients, resulting in long trial timelines that delay bringing potentially effective new treatments to patients.

By using machine learning to leverage existing patient clinical data, we create patient-specific prognostic digital twins that significantly reduce control arm sizes. Smaller control arms give more patients the chance to take the experimental treatment and accelerate drug development timelines. 

Here we describe how our regulatory-suitable method using digital twins enabled a control arm size reduction of up to 35% for a Phase 2 AD study on crenezumab (the ABBY study, NCT01343966). Download the abstract to learn more.

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