An exact match for each patient

Increasing trial power and confidence

Digital Twins can increase study power by decreasing variability, and even power secondary endpoints and exploratory analyses.

Accelerating trial timelines

Adding Digital Twins to a clinical trial means fewer patients who receive the placebo, and lower failure rates.

Enabling patient level insights

Digital Twins provide additional evidence to understand the treatment effect: how each patient responded to an experimental therapy in a trial.
First, we prepare a highly curated dataset, so our machine learning model can learn from the relationships. Control arm records from several trials focused on a specific disease are curated to become machine learning ready.

Creating a Curated Dataset

Once the dataset is prepared, we separate it into two groups, one for training, and the other for testing. The machine learning model builds an internal network of connections. We then evaluate the model to ensure it is ready to begin generating Digital Twins.

DiGenesis™: Generating our Machine Learning Model

What is a Digital Twin?

A comprehensive, longitudinal, and computationally generated clinical record that describes what would have happened if a specific patient had received a placebo.
While a patient’s journey in a clinical trial takes months, or even years, a Digital Twin’s record is created after the first visit. Our model uses baseline data to create a complete record that predicts how the patient would have responded if she had not received the experimental treatment.

Creating a Digital Twin

Digital Twins enhance data about patients already enrolled in the trial, and more data means more certainty, and in turn, power.
PROCOVA™ (prognostic covariate adjustment) is like an adapter - a statistical method that incorporates Digital Twins into statistical analysis plans to provide a more precise estimate of the treatment effect.

Introduction to PROCOVA™

Randomized controlled trials augmented by Digital Twins and PROCOVA™

Prospectively incorporating Digital Twins into clinical trials enables smaller, more efficient trials. In addition to reducing sample size, Digital Twins can be added to trials at any time to increase power.

Each patient in the trial is paired with their AI-generated predicted placebo outcome, or Digital Twin. Digital Twins maintain randomization and blinding, and increase certainty without introducing bias.

Supplement single arm trials with Digital Twins

An Intelligent Control Arm is an external control arm populated with Digital Twins. Incorporating an ICA into a clinical trial increases power and provides patient level results when estimating the treatment effect.

Each patient has a Digital Twin, and a single arm trial can now be analyzed with two arms.

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