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Delivering novel solutions with digital twins that accelerate clinical development

AI-powered Clinical Trial Design for Key Studies

Try TrialPioneer

AI-powered Clinical Trial Design for Key Studies

Try TrialPioneer

01.

Phase 2 and 3 Studies

Design smaller, faster, highly-powered randomized trials that leverage digital twins to reduce sample sizes without sacrificing power. Alternatively, use digital twins to boost trial power without adding additional trial participants. This approach is qualified by the EMA and aligns with current FDA guidance.

02.

Single-Arm Studies

Generate digital twins as a simulated control group in single-arm studies, enabling precise treatment effect analysis for the trial. This provides a robust comparator group without needing a traditional or externally matched control arm.

03.

Multiple Ascending Dose (MAD) Studies

Design a MAD study using digital twins to accelerate the timeline for determining the safety, tolerability, and optimal dose ranges, allowing for quicker progression to later trial phases or go/no-go decisions.

Gain Predictive Trial Insights with the Digital Twins Dashboard

01.

Explore predicted outcomes

For any participant or subgroup across all measured clinical variables – outcomes, biomarkers, labs, and vital – at any point in time.

02.

Gain real-time insights

About expected progression as participants enroll and make more informed, data-driven decision-making throughout the trial.

03.

Identify sensitive clinical outcomes

To optimize composite scores for better signal detection. This enhances the sensitivity of outcomes at both the population and subpopulation levels, offering insight into meaningful clinical outcomes for your trial population.

Maximize Precision and Power in Trial Analysis with Digital Twins

01.

Obtain precise treatment effect estimates

For all variables at any time, for the full trial population, and in predefined subgroups.

02.

Boost statistical power for confident decision-making

Whether at interim stages or end of study. Achieve greater confidence in assessing drug effectiveness, reducing uncertainty, and enabling more informed decision-making.

03.

Discover responder subpopulations for targeted treatment

To identify likely responder individuals and subpopulations. Unlock valuable insights into the patients who benefit the most from the treatment.