Paid tool

unlearn.ai

AI platform creating digital twins of patients to optimize, shorten, and de-risk clinical trials.

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Intro

What is unlearn.ai?

Unlearn.ai is a clinical research platform that leverages artificial intelligence to create highly precise digital twins of clinical trial participants. The Unlearn platform operates an advanced machine learning engine known as a Boltzmann machine (specifically a Conditional Restricted Boltzmann Machine) to generate comprehensive, personalized clinical trial digital twin trajectories. By computing what would happen if a specific patient received a placebo, the platform introduces TwinRCTs, which utilize their proprietary PROCOVA (Prognostic Covariate Adjustment) statistical methodology. Backed by research papers and a positive qualification opinion from the EMA alongside alignment with US FDA guidance, Unlearn helps global pharmaceutical groups like Johnson & Johnson design smaller, faster, and more powerful randomized controlled trials across complex medical areas like Alzheimer's and ALS.

unlearn.ai at a glance
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Pricing

unlearn.ai Pricing Plans

Compare unlearn.ai free options, unlearn.ai paid pricing plans, and usage notes before you choose the best way to use this AI tool in 2026.

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Pricing updated:Jun 12, 2026

Features

unlearn.ai AI Features

AI-Generated Digital Twins of Patients: Simulates longitudinal clinical outcomes and future disease progression trajectories for individual participants based on baseline data.PROCOVA Statistical Integration: Employs a qualified Prognostic Covariate Adjustment framework to maximize statistical power without introducing bias or inflating type-I error rates.TrialPioneer Workspace: Provides an upstream workspace featuring Scout for literature tracking, Hindsight for dataset exploration, and SimLab for protocol simulation.Control Arm Size Reduction: Enables clinical development leads to design smaller, regulatory-aligned control cohorts while maintaining identical study power.
Pros & Cons

unlearn.ai Pros and Cons

Pros

  • Significantly reduces patient enrollment bottlenecks and associated millions in trial costs
  • Saves up to several months in clinical trial enrollment times
  • Fully qualified by the EMA and explicitly aligned with current FDA guidance
  • Minimizes the ethical burden of exposing real human participants to placebos

Limitations

  • Requires large volumes of clean, harmonized historical patient data to train reliable disease models
  • May have reduced predictive accuracy if standard-of-care treatments change dramatically over time
  • Primarily optimized for continuous, slowly progressing indications like neuroscience (Alzheimer's, ALS) and metabolic diseases

unlearn.ai FAQ

PROCOVA (Prognostic Covariate Adjustment) is a proprietary statistical method developed by Unlearn. It uses a patient's digital twin to compute a prognostic score tracking expected outcomes on a placebo, integrating it as a baseline covariate into standard ANCOVA analyses to increase trial power.