Applications of Digital Twins in Clinical Trials for Alzheimer’s Disease

AI-driven clinical trials have the potential to achieve higher power with fewer subjects, to provide actionable insights into which patients achieve the greatest benefit, and to design faster, more efficient clinical trials - all while ensuring reliable evidence about safety and efficacy. Digital Twins, or simulated control outcomes for individual patients, can be used to design trials that are smaller, faster, and/or more powerful. In this whitepaper, we describe 4 novel trial designs that balance three different characteristics: (i) the number of subjects required to achieve the power to detect a pre-specified effect size, (ii) insensitivity to potential confounding factors, and (iii) the type-I error rate, to demonstrate how Digital Twins can accelerate both early and late-stage clinical trials.

Enter your email address to download paper.

Click the link to begin download.
Oops! Something went wrong while submitting the form.

Enter your email address to watch the webinar.

Click the link to watch webinar.
Oops! Something went wrong while submitting the form.
White Papers

Using AI-based Prognostic Models to Design Efficient, Unbiased Clinical Trials

Webinars

Part 3: Innovation in Clinical Research: AI-based Drug Development Tools and the Regulatory Landscape‍

Webinars

Part 2: Faster, More Efficient Trials: Novel Trial Designs using Digital Twins‍

Watch an overview of specific use cases for Digital Twins and learn how novel trial designs with Digital Twins enable smaller trials that maintain their power.
Watch a panel discussion on the regulatory landscape where experts share perspectives on the future of AI-based drug development tools like Digital Twins.
Statistical principles of clinical trials with Digital Twins