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Products and SolutionsDigital TwinsTrialPioneerDigital Twin GeneratorsResourcesBlogEvidenceArtificial IntelligenceClinical ResearchCompanyAboutCareersPressBook a demoDriving clarity in clinical developmentPowered by digital twins, data, and AIReplace siloed workflows and black-box predictions with a unified, upstream workspace for trial design, planning, and analysis—so your teams reach alignment faster, test assumptions earlier, and move forward with confidence.Get in touchReal-world ResultsControl Arm Size Reduction*0%Enrollment Time Saved (months)*0+*Approximate valuesAccelerating Clinical Development in Alzheimer’s DiseaseWe work in neuroscience, immunology, metabolic disease, and more.View AbbVie Case StudySolutionsConfident decisions across the clinical development lifecycle.01TrialPioneerOne workspace for upstream trial designUnlearn brings together the critical components required for trial design — where decisions are iterative, assumptions evolve, and rationale must remain clear and defensible across review cycles.Learn moreScoutContinuously search, structure, and summarize relevant literature and regulatory precedent from sources like PubMed, ClinicalTrials.gov, and drugs@FDA — all in one place. Eliminate scattered searches and align on precedent in days, not weeks.HindsightExplore harmonized clinical trial and real-world datasets to validate clinical and statistical assumptions. Assess feasibility, population characteristics, endpoint behavior, and benchmarks using transparent historical data.SimLabBuild and compare trial-design scenarios to evaluate endpoints, inclusion/exclusion criteria, sample size, and constraints. Every scenario is explainable, reproducible, and linked to underlying evidence — supporting informed design trade-offs before protocol finalization.ScoutContinuously search, structure, and summarize relevant literature and regulatory precedent from sources like PubMed, ClinicalTrials.gov, and drugs@FDA — all in one place. Eliminate scattered searches and align on precedent in days, not weeks.HindsightExplore harmonized clinical trial and real-world datasets to validate clinical and statistical assumptions. Assess population characteristics, endpoint behavior, and benchmarks.SimLabBuild and compare trial-design scenarios to evaluate endpoints, inclusion/exclusion criteria, sample size, and constraints. Every scenario is reproducible, and linked to underlying evidence — supporting informed design trade-offs before protocol finalization.02Trial Analyses with Digital TwinsStrengthen trial analyses with digital twins—AI-generated forecasts of clinical trial participants’ expected control outcomes.Used as external comparators in early-stage and open-label studies, digital twins reduce variability and improve the ability to detect treatment effects. The same approach extends to randomized trials, where digital twins can support smaller sample sizes or increased power.This methodology is qualified by the EMA and aligned with current FDA guidance, enabling clearer go/no-go decisions earlier in development and more efficient late-stage trials, with measurable reductions in trial size, cost, and time to readout.Learn moreTrusted by leading sponsors“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 QurAlisView Presentation"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 remyndSee Press Release“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 NeuroscienceSee Press Release“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 QurAlisView Presentation"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 remyndSee Press Release“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 NeuroscienceSee Press Release“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 QurAlisView PresentationPartnershipsCollaborating with leaders to move the industry forward.Explore how leading biopharma companies are applying Unlearn’s AI-powered solutions in active studies today to reach clinical milestones faster.View allFEB 12, 26PressUnlearn to Apply AI-Generated Digital Twins to the VectorY Therapeutics PIONEER-ALS StudyJan 28, 26PressUnlearn Introduces TrialPioneer, an AI-powered Workspace to Strengthen Upstream Trial PlanningApr 3, 25PressUnlearn and remynd Partner on Alzheimer’s Study to Strengthen Confidence in Early Clinical Signals Using Digital TwinsAPR 1, 25PressUnlearn and Trace Neuroscience Partner to Optimize ALS Clinical TrialSep 27, 24PressProJenX and Unlearn partner to use AI-generated digital twins in ALS trialThe AI partner of choice for top pharma and biotechsContact usPRODUCTS AND SOLUTIONSTrialPioneerDigital TwinsDigital Twin GeneratorsConnectRESEARCHArtificial IntelligenceClinical ResearchCOMPANYAboutCareersBlogPress© 2026 Unlearn.ai, Inc. All rights reserved.TermsPrivacyData Acknowledgements TrialpioneerStill rebuilding trial design work every review cycle?TrialPioneer helps clinical development teams reach design decisions faster by replacing fragmented searches, spreadsheets, and one-off analyses with a single, unified AI-enabled workspace. Teams can investigate and compare trial design scenarios earlier, anchor assumptions to credible evidence, and enter governance discussions with clear, defensible rationale.See a better trial planning workflow --- Products and SolutionsDigital TwinsTrialPioneerDigital Twin GeneratorsResourcesBlogEvidenceArtificial IntelligenceClinical ResearchCompanyAboutCareersPressBook a demoHarnessing data, AI, and digital twins to transform clinical development About usAt Unlearn, we are defining the future of clinical development with unmatched scientific credibility, replacing uncertainty with AI-powered precision so decisions are clearer and trials are stronger.Our mission is to transform clinical development by making every trial smarter. We harness data, AI, and digital twins to enable faster, more robust studies that bring life-saving treatments to patients faster. We're here to not just disrupt the pharmaceutical industry, but create lasting change.Read our blogMeet the faces of UnlearnExecutive TeamBoard of DirectorsSteve HerneChief Executive OfficerAaron SmithFounder & Head of AIJon WalshFounder & Chief Scientific OfficerPrathyusha DuraibabuChief Financial & Operating OfficerAndrew StelzerHead of Business DevelopmentKrates NgChief Technology OfficerKwame MarfoVP of ProductTheresa VermeerschVP of HRSteve HerneChief Executive OfficerCharles K. FisherFounder, Unlearn.AIMira MuratiFormer CTO, OpenAIAnn TaylorFormer CMO, AstraZenecaFrancisco GimenezPartner, 8VCKiersten SteadManaging Partner, DCVC BioDylan MorrisManaging Director at Insight PartnersCareers at UnlearnView careersUnlearners are innovators who are determined to dismantle the status quo. Our approach to innovation rests on moonshot thinking — by setting radically ambitious goals, we can make the impossible possible and solve a problem that impacts the lives of millions.The AI partner of choice for top pharma and biotechsContact usPRODUCTS AND SOLUTIONSTrialPioneerDigital TwinsDigital Twin GeneratorsConnectRESEARCHArtificial IntelligenceClinical ResearchCOMPANYAboutCareersBlogPress© 2026 Unlearn.ai, Inc. All rights reserved.TermsPrivacyData Acknowledgements --- Products and SolutionsDigital TwinsTrialPioneerDigital Twin GeneratorsResourcesBlogEvidenceArtificial IntelligenceClinical ResearchCompanyAboutCareersPressBook a demoRun quick and confident ‍clinical trials with digital twinsDigital twins are AI-generated forecasts of an individual trial participant’s control outcomes. By forecasting clinical outcomes at every future time point with unparalleled precision, they serve as the powering technology for a more rigorous clinical analysis.Digital Twin ApplicationIncrease signal. Reduce noise.Randomized Controlled TrialsIncrease power while maintaining sample sizes, or reduce control arm size while preserving power. This methodology improves sensitivity across primary and secondary endpoints for a clearer signal of efficacy.Early-Stage Trials and Rare DiseasesGenerate participant-level synthetic control arms to enable credible treatment comparisons when randomization is infeasible. Strengthen high-stakes go/no-go decisions through improved statistical sensitivity.Interim and Retrospective LooksImprove sensitivity in interim looks and subgroup analyses to catch signals that traditional methods may miss. Re-evaluate historical trial data using regulatory-aligned methods to support learning across programs.Regulatory AcceptancePaving the regulatory path for AI in clinical trialsUnlearn’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.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.CHMP qualifies PROCOVA and that the proposed procedures could enable increases in power and/or decreases in sample size in phase 2 and 3 in clinical trials with continuous outcomes.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.CHMP qualifies PROCOVA and that the proposed procedures could enable increases in power and/or decreases in sample size in phase 2 and 3 in clinical trials with continuous outcomes.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.CHMP qualifies PROCOVA and that the proposed procedures could enable increases in power and/or decreases in sample size in phase 2 and 3 in clinical trials with continuous outcomes.Digital twin technologyDisease-specific ML models trained on extensive historical clinical data generate digital twins for each trial participant using only their baseline data.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.Case StudiesDriving impact across clinical developmentOur trial solutions using digital twins are backed by collaborative research and successful implementation with global leaders in drug development.Reduce variability to improve decision making in early-stage trialsAbbVie[AAIC 2024] Assessment of AI-generated Digital Twin (DT) 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 (AD)AbbVie[AD/PD Vienna 2025] Digital twin predictions of patient outcomes enable more efficient and powerful Clinical TrialsJ&J[AAIC 2024] Accelerating randomized clinical trials in Alzheimer’s disease using generative machine learning model forecasts of disease progressionRoche[AAIC 2022] Evaluating Digital Twins for Alzheimer’s Disease using Data from a Completed Phase 2 Clinical TrialUnlearn[AD/PD Vienna 2025] Machine Learning Model Enables Accelerated Enrollment Timelines in Parkinson’s Disease Clinical TrialsUnlearn[35th International Symposium on ALS/MND 2024] Boosting Clinical Trial Power in ALS with AI-Generated Digital TwinsUnlearn[NEALS Meeting 2024] Boosting Clinical Trial Power in ALS with AI-Generated Digital TwinsUnlearn[MDS 2024] Boosting Clinical Trial Power in Parkinson’s Disease with AI-Generated Digital TwinsUnlearn[AAIC 2025] Boosting Trial Power in Early Alzheimer’s with AI-Generated Digital TwinsUnlearnParkinson's Disease Case StudyUnlearnAmyotrophic Lateral Sclerosis Case StudyUnlearnAlzheimer's Disease Case StudyUse digital twins as an external comparator to support efficacy findings in early-stage studiesProJenX[2025 ALS Drug Development Summit] AI-Generated Digital Twins in ALS: Improving Confidence in Early-Stage Clinical TrialsProJenXProJenX and Unlearn Announce Partnership to Augment ALS Clinical Trial PRO-101 with Digital Twin ModelQurAlisStreamlining Efficiency of QRL-201 Randomized Control Trial & Increasing Confidence of Results with Generative AI Technology.Reduce variability to improve decision making in early-stage trialsremynd[AD/PD Boston 2025] Use of digital twins in a Phase 2a trial to predict disease-progression of participants with mild-to-moderate Alzheimer's Disease supports early signals of efficacyThe AI partner of choice for top pharma and biotechsContact usPRODUCTS AND SOLUTIONSTrialPioneerDigital TwinsDigital Twin GeneratorsConnectRESEARCHArtificial IntelligenceClinical ResearchCOMPANYAboutCareersBlogPress© 2026 Unlearn.ai, Inc. All rights reserved.TermsPrivacyData Acknowledgements --- Products and SolutionsDigital TwinsTrialPioneerDigital Twin GeneratorsResourcesBlogEvidenceArtificial IntelligenceClinical ResearchCompanyAboutCareersPressBook a demoDesign clinical trials with speed and rigorReach confident, evidence-backed trial design decisions earlier — before protocols are finalized.Unlearn’s TrialPioneer helps clinical development teams reach design decisions faster by replacing fragmented searches, spreadsheets, and one-off analyses with a single, unified AI-enabled workspace. Teams can investigate and compare trial design scenarios earlier, anchor assumptions to credible evidence, and enter governance discussions with clear, defensible rationale.Schedule a demoHow It WorksSee how teams design, compare, and align on trial planning decisions earlier01Explore trial precedent, observed data, and simulations in a single environment02Compare endpoints, eligibility criteria, and design scenarios without building custom analyses03See how protocol choices change populations and expected outcomes04Iterate on design decisions live and understand trade-offs in real time05Preserve assumptions, evidence, and results so rationale doesn’t disappear after meetingsSchedule a demoProduct OverviewAn AI-enabled system for evidence, assumptions, and trial design scenariosTrialPioneer brings together the critical components required for early planning and design— where decisions are iterative, assumptions evolve, and rationale must remain clear and defensible across review cycles. Clinical development teams work from a shared source of truth, reducing rework and accelerating alignment.View allScoutAI-powered literature and precedent reviewSeamlessly search, structure, and summarize relevant scientific and regulatory precedent from sources such as PubMed, ClinicalTrials.gov, and drugs@FDA. Scout replaces scattered searches with a transparent, shared foundation for evidence review — helping teams align on precedent in days, not weeks.HindsightHistorical data explorationExplore harmonized clinical trial and real-world datasets to validate clinical and statistical assumptions. Assess population characteristics, endpoint behavior, and benchmarks using relevant historical data — grounding early design decisions in evidence rather than intuition.SimLabExplainable trial simulationsAutomatically link, build, and compare trial design scenarios across endpoints, eligibility criteria, and sample size. Every scenario is explainable, reproducible, and grounded in historical evidence — supporting informed trade-offs before protocol finalization.BenefitsFaster design cycles without sacrificing scientific rigorEarlier alignment on trial design decisionsClearer trade-offs when evaluating endpoints, populations, and sample sizeFewer handoffs between literature review, data analysis, and simulationPreserved decision context as designs evolveReal-world ImpactTrialPioneer in actionOptimize study design, including endpoint, time point and eligibility strategiesPartnershipUnlearn and Trace Neuroscience Partner to Optimize ALS Clinical TrialWhitepaperThe Hidden Bill of Inefficient Clinical Trial DesignOne-PagerUnlearn's TrialPioneerHow We're DifferentBuilt for trial planning — and scientific oversightBeyond document-first protocol platformsUnlearn supports evidence review, assumption testing, and scenario comparison before designs are finalized.Beyond siloed statistical simulationTrialPioneer makes assumptions, inputs, and outputs visible across clinical, biostatistics, and regulatory teams earlier.Beyond point AI toolsUnlearn links evidence, historical data, and simulations into a transparent, review-ready workflow.Beyond downstream execution systemsTrialPioneer focuses upstream, where early design decisions matter most.The AI partner of choice for top pharma and biotechsContact usPRODUCTS AND SOLUTIONSTrialPioneerDigital TwinsDigital Twin GeneratorsConnectRESEARCHArtificial IntelligenceClinical ResearchCOMPANYAboutCareersBlogPress© 2026 Unlearn.ai, Inc. All rights reserved.TermsPrivacyData Acknowledgements