How are we changing clinical trials?


Machine learning for comprehensive forecasting of Alzheimer's Disease progression

We have shown that generative models capable of sampling conditional probability distributions over a diverse array of clinical variables can accurately model the progression of Alzheimer’s Disease.

Will digital clones transform how pharmas run clinical trials? This S.F. startup is counting on it.


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


Broadening Role for External Control Arms in Clinical Trials

Unlearn.AI Inc. is going a step further, using data from historical trials and patient registries to build algorithms that simulate artificial patients.
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.
The San Francisco-based company creates digital replicas of participants in clinical drug trials using artificial intelligence. The result, says Charles Fisher, CEO and co-founder of Unlearn AI, will

The FDA needs to set standards for using artificial intelligence in drug development

Digital Twin Advances Poised to Expand Clinical Trial Reach

What is a Digital Twin?

The Advantages of Modeling Clinical Data for Control Arms

Your Digital Twin - UnlearnAI

A fascinating approach to the problem of how to make clinical trials more efficient, and understand more about what may be possible with more and better patient data.

Generating Digital Twins with Multiple Sclerosis Using Probabilistic Neural Networks

Using a dataset of subjects enrolled in the placebo arms of MS clinical trials, we trained a Conditional Restricted Boltzmann Machine to generate digital subjects.

Boltzmann Encoded Adversarial Machines


Transforming Clinical Trials with Intelligent Control Arms


Learning from Data Across the Alzheimer's Disease Spectrum

At AAIC, I watched the talks with this question in mind: how would we build a model of disease progression in the early stages of AD?
Digital twins can be used to populate an intelligent control arm, a type of external control arm with a variety of applications.
The deep learning revolution has driven tremendous advances on supervised learning problems, and a primary outcome is that feed-forward neural networks have become a powerful tool.

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