Every clinical outcome at every future time point.
Predicted with unparalleled precision.
These twins forecast clinical outcomes at every future time point.
Predicted with unparalleled precision.
Run quick and confident
clinical trials with digital twins
Digital twins are AI-generated forecasts of an individual trial participant's clinical outcomes. By forecasting clinical outcomes at every future time point with unparalleled precision, they power more rigorous clinical analysis.
Digital Twin Generators
Disease-specific AI models for generating patients' digital twins
Digital Twin Generators (DTGs) are trained on extensive patient-level historical data to forecast individual disease progression under control or standard of care.
In addition to our validated DTGs, Unlearn enables sponsors to build and deploy custom DTGs using their proprietary data, entirely within their own environments and under their control. Deployment is flexible and scalable, available as a web-based application or a secure, on-premises solution within the sponsor's cloud infrastructure.
Built to meet regulatory-grade compliance standards, including GxP, 21 CFR Part 11, and SOC 2 Type 2, Unlearn's technology ensures sponsors maintain complete control over their systems, security, and data integrity.
We encourage you to request our specification sheets to gain a comprehensive understanding of our models, including their capabilities and underlying data.
Request specs
Alzheimer’s disease
Amyotrophic Lateral Sclerosis
Asthma
Atopic Dermatitis
Breast cancer
Colorectal cancer
COPD
Crohn’s disease
Depression
Dyslipidemia
Frontotemporal dementia
Huntington's disease
Hypertension
Migraine
NSCLC
Obesity
Ovarian cancer
Pancreatic cancer
Parkinson's disease
Prostate cancer
Psoriasis
Psoriatic Arthritis
Rheumatoid Arthritis
Schizophrenia
Type 2 Diabetes
Ulcerative Colitis
Alzheimer’s disease
Amyotrophic Lateral Sclerosis
Asthma
Atopic Dermatitis
Breast cancer
Colorectal cancer
COPD
Crohn’s disease
Depression
Dyslipidemia
Frontotemporal dementia
Huntington's disease
Hypertension
Migraine
NSCLC
Obesity
Ovarian cancer
Pancreatic cancer
Parkinson's disease
Prostate cancer
Psoriasis
Psoriatic Arthritis
Rheumatoid Arthritis
Schizophrenia
Type 2 Diabetes
Ulcerative Colitis
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Digital twin technology
Disease-specific ML models trained on extensive historical clinical data generate digital twins for each trial participant using only their baseline data.
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Regulatory Acceptance
Qualified by EMA, supported by FDA guidance
Unlearn's methods have been recognized and supported by both U.S. and European regulators.
PROCOVA 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.
Our digital twin solutions are backed by collaborative research with leading sponsors and validated in re-analyses of their completed trials.
See our case studies
