Trusted by leading sponsors. Grounded in science. Proven in trials.
Leading biopharma sponsors use Unlearn’s AI-powered products and solutions to design smarter trials and derive stronger signals from every participant, backed by regulatory alignment and a foundation of rigorous research.
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Regulatory Acceptance
Paving the regulatory path for AI in clinical trials
Unlearn’s methods have been recognized and supported by both U.S. and European regulators.
Our digital twins-based method was officially qualified by the European Medicines Agency for use in Phase 2 and 3 trials with continuous outcomes. U.S. FDA provided positive feedback on PROCOVA, supporting its use in covariate-adjusted analyses across clinical development.
FDA recommends that sponsors adjust for covariates that are anticipated to be most strongly associated with the outcome of interest…it may be useful to use previous studies to select prognostic covariates or form prognostic indices.
In a trial that uses covariate adjustment, the sample size and power calculations can be based on adjusted or unadjusted methods.
End-to-end AI-Powered Solutions
Driving Impact Across Clinical Development
Explore how our partners are accelerating their clinical development programs with us.
Case Studies
Alzheimer's disease Parkinson's disease Amyotrophic Lateral Sclerosis
Alzheimer’s disease
Amyotrophic Lateral Sclerosis
Asthma
Atopic Dermatitis
COPD
Coronary Artery Disease
Crohn’s disease
Dyslipidemia
Frontotemporal dementia
Huntington's disease
Hypertension
Migraine
Obesity
Osteoarthritis
Osteoporosis
Parkinson's disease
Psoriasis
Psoriatic Arthritis
Rheumatoid Arthritis
SCI
Stroke
Type 2 Diabetes
Ulcerative Colitis
Product
Trial Planning and Simulations
Reach confident, evidence-backed trial design decisions earlier — before protocols are finalized.
Trial Planning and Simulations impact
Faster, more confident trial design decisions
Clearer trade-offs when evaluating endpoints, populations, and sample size
Fewer handoffs between literature review, data analysis, and simulation
Preserved decision context as designs evolve
“Working with Unlearn to mine their extensive, well-curated database through the use of the ALS DTG will enable us to explore smarter designs and make confident and informed decisions as we plan our Phase 1/2 trial. Ultimately, these insights can help us to move faster for people living with ALS who are waiting for new treatment options."
Eric Green, M.D., Ph.D.
Co-founder and CEO of Trace Neuroscience
Product
Participant's digital twins
AI-generated forecasts of individual study patients’ control outcomes provide clearer, earlier signals at every interim timepoint, enabling more confident go/no-go decisions.
Conference Highlights
"Digital twins help us make the most of the data we’re getting from here. In this open-label study, digital twins obviously provide us with built-in placebo controls for each participant…they have a lot of key advantages over propensity score matching or other natural history controls that allow us to have more confidence in the data we’re taking out of that person-intraperson comparison."
Erin Fleming, COO, ProJenX
Why leading sponsors choose unlearn
“The ecosystem at the moment doesn’t sustain the way we’ve been doing it traditionally. And (Unlearn) is at the leading edge of this thinking.”
Kasper Roet, founder and CEO of QurAlis
"The collaboration with Unlearn and the resulting data further increases our confidence in our pioneering approach towards achieving symptomatic relief and disease modification in Alzheimer’s. This will support our efforts to advance an optimized second-generation therapy. Digital twins offer a new lens for interpreting biomarker trends over time—especially in early-stage trials where every data point matters."
Gerard Griffioen, Ph.D., CSO of remynd
Explore the Science
Our technology is built on a foundation of rigorous scientific research across therapeutic areas, from neurodegenerative diseases to oncology and obesity. Explore the full library.
Data & Platform Strengths
Indications
20+
Clinical study records
1M+
*Approximate values
Experts in Data Sourcing and Operationalizing Unstructured Data
Unlearn has deep expertise in transforming complex clinical data into AI-ready formats. Our technology draws from over 1 million longitudinal clinical study records and spans 20+ indications, including neuroscience, immunology, cardiovascular, and metabolic diseases. This rich data foundation powers scalable, scientifically rigorous disease-specific ML models with exceptional performance.
Research & Thought Leadership
Pioneering AI Research
Unlearn’s platform is powered by novel, disease-specific AI models called Digital Twin Generators (DTGs). Learn more about how we build and validate these models:
| Date | Title | Publisher |
|---|---|---|
| May 24, 2026 | Regulatory Considerations for Using Artificial Intelligence Models to Reduce Sample Sizes in Registrational Studies | arXiv |
| May 18, 2026 | FRESH: Information-Geometric Calibration of Patient-Level Models to Aggregate Evidence | arXiv |
| May 14, 2026 | Digital Twins as Synthetic Controls in Single-Arm Trials | arXiv |
| January 9, 2025 | Assessment of AI-generated digital twin methodology on reduction of treatment effect variance and potential clinical trial sample size saving using a Phase 2 trial dataset from patients with Alzheimer’s disease | Alzheimer's Association |
| May 2, 2024 | Digital Twin Generators for Disease Modeling | arXiv |
| April 26, 2024 | Enhancing Longitudinal Clinical Trial Efficiency with Digital Twins and Prognostic Covariate-Adjusted Mixed Models for Repeated Measures (PROCOVA-MMRM) | arXiv |
| November 23, 2023 | Bayesian Prognostic Covariate Adjustment With Additive Mixture Priors | arXiv |
| September 25, 2023 | Addressing Concerns About Digital Twins in Clinical Trials | arXiv |