Generating Digital Control Subjects using Machine Learning for Alzheimer's Disease Clinical Trials (CTAD 2019)

Background: Recently, there has been a flurry of attention focused on the benefits of synthetic control patients in clinical trials. The ability to reduce the burden on control subjects with subjects in clinical trials for complex diseases like Alzheimer's Disease would drastically improve the search for beneficial therapies. Objective: To demonstrate a machine learning model is capable of simulating Alzheimer's Disease progression and generate digital control subjects that are statistically indistinguishable from actual controls. Methods: We developed a machine learning model of Alzheimer's Disease progression trained with data from 4897 subjects from 28 clinical trial control arms involving early or moderate Alzheimer's Disease. The model is an example of a Conditional Restricted Boltzmann Machine (CRBM), a kind of undirected neural network whose properties are well suited to the task of modeling clinical data progression. The model generates values for 47 variables for each digital control subject at three-month intervals. Results: Based on a statistical analysis comparing data from actual and digital control subjects, the model generates accurate subject-level distributions across variables and through time that are statistically indistinguishable from actual data. Conclusion: Our work demonstrates the potential for the CRBMs to generate digital control subjects that are statistically indistinguishable from actual control subjects, with promising applications for Alzheimer's Disease clinical trials.

Enter your email address to download paper.

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

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

Press

Unlearn.AI named to the 2021 CB Insights AI 100 List of Most Innovative Artificial Intelligence Startups

Blog

Welcoming Dr. Taylor to Unlearn.AI’s Board of Directors

I’m honored to have such an inspirational and experienced leader like Dr. Taylor join our board.
The AI 100 is CB Insights' annual list of the 100 most promising private AI companies in the world.
How Digital Twins make it possible to design and run more efficient clinical trials with well-defined statistical properties.