U

Unlearn AI

AI-powered patient digital twins for simulations

VP of Clinical Solutions

Full-Time
$260k - $310k/yr+ Equity participation + 401(k) match
Expert
San Francisco, CA, USA
In Person
Biology & Biotech

About the job

Requirements
  • At least 10 years leading scientific or analytical delivery work in clinical development, including significant experience at the Senior Director or VP level with responsibility for multidisciplinary technical teams.
  • A track record of leading data analytics, biostatistics, data science, or related delivery organizations serving biopharmaceutical customers, such as real-world data companies, contract research organizations, or analytics-driven clinical development partners.
  • The ability to provide credible technical guidance and governance across biostatistics, data science, and machine learning, with fluency in quantitative methods.
  • Experience growing individual contributors into technical leaders.
  • Strong operational skills, including keeping complex, concurrent customer delivery portfolios on track, resourcing projects under real constraints, and scaling delivery teams and processes as demand grows.
  • Domain knowledge of clinical development, including study designs, clinical data, sponsor expectations, and regulatory and evidentiary standards.
  • Experience reporting to executive leadership on delivery capacity, growth, and risk, managing commitments realistically, and surfacing problems early.
  • Comfort operating cross-functionally with Business Development, Product, Engineering, R&D, Quality Management, and customer stakeholders, and translating between technical and non-technical audiences.
  • Experience in growth-stage or early-stage companies.
Responsibilities
  • Lead the scientific delivery organization and own the quality, timeliness, and scientific rigor of customer-facing delivery work across a portfolio of concurrent projects.
  • Partner with Business Development, Product, Engineering, R&D, and Quality Management to shape scopes of work, resolve cross-functional blockers, feed delivery learnings back into the product, and ensure sold work can be delivered excellently.
  • Serve as a senior scientific voice with customers by handling escalations, building trust with sponsor teams, and representing the credibility of the company's science in clinical development settings.
  • Develop technical team leaders through direct people leadership, mentorship, and career development.
  • Establish and uphold technical governance, including standards, review practices, and quality frameworks for statistical analyses, data products, and machine-learning applications.
  • Own delivery operations at scale, including project staffing and resourcing, capacity planning, prioritization across customer demands, and delivery processes that keep the portfolio on track.
  • Report regularly to company leadership on delivery health, capacity, and portfolio risk; manage the growth of delivery commitments; and escalate risks early and transparently.
  • Build systems, metrics, and delivery models that maintain quality as the organization grows.
Desired Qualifications
  • Direct machine-learning delivery experience.

About the company

Unlearn.AI builds AI-powered digital twins of patients to simulate health outcomes and predict how conditions may evolve. It generates patient-specific virtual replicas from data and runs treatment scenarios to forecast results. Unlike traditional trials, its twins model control groups for clinical studies, potentially reducing the number of real patients needed and speeding drug development. The goal is to speed healthcare decisions, improve trial efficiency, and lower costs by using digital twin simulations to forecast outcomes.

Company Size

51-200

Company Stage

Series C

Total Funding

$130.7M

Headquarters

San Francisco, California

Founded

2017

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Simplify's Take

What believers are saying

  • SOLA, VectorY, and Acumen deals show 2026 sponsor adoption across ALS and Alzheimer’s.
  • TrialPioneer launched January 2026, expanding Unlearn earlier into study-design budgets.
  • Series C funding from February 2024 still supports data, engineering, and commercial expansion.

What critics are saying

  • Acumen and VectorY validate demand, but no public repeatable revenue scale exists.
  • Certara, Dassault Systèmes, and InSilicoTrials commoditize digital-twin messaging across trials.
  • If FDA rejects sponsor-specific use cases, Unlearn's platform becomes a niche analytics vendor.

What makes Unlearn AI unique

  • EMA-qualified PROCOVA and FDA-supported methodology gives Unlearn rare regulatory credibility.
  • AD DTG 4.2 uses 26,000-plus records to model p-tau217 and GFAP biomarkers.
  • TrialPioneer unifies precedent review, benchmark data, and simulations in one workflow.

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Benefits

  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • 401(k) Retirement Plan
  • 401(k) Company Match
  • Unlimited Paid Time Off
  • Paid Holidays
  • Commuter Benefits
  • Paid Parental Leave
  • Company Equity

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

0%

2 year growth

-1%
Unlearn.AI
Mar 13th, 2026
AD model update: AD DTG 4.2 - exploring biomarker outcomes in Alzheimer's disease.

AD model update: AD DTG 4.2 - exploring biomarker outcomes in Alzheimer's disease. March 13, 2026. Unlearn is excited to announce the release of AD DTG 4.2, the latest update to its Alzheimer's disease Digital Twin Generator. This release expands the biomarker data available to its model and enables early exploration of biomarkers as potential clinical outcomes. Why biomarkers matter in AD trials. Biomarkers are measurable biological molecules whose concentration shifts in response to disease processes or treatments. Unlike traditional lab values that monitor general physiology, such as electrolytes or liver enzymes, disease-specific biomarkers target molecular pathways tied to a specific condition. In Alzheimer's, novel biomarkers like phosphorylated tau-217 (p-tau217), amyloid beta 40 (Aβ40), and amyloid beta 42 (Aβ42) can signal neurodegenerative changes years before symptoms appear, making them valuable for detecting disease, tracking progression, and evaluating therapeutic response in clinical trials. Expanded data, expanded possibilities. The updated data asset now includes or enriches several AD-relevant biomarkers, including: Aβ40, Aβ42, total tau (t-tau), phosphorylated tau-181 (p-tau181), p-tau217, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). Incorporating these biomarkers into the data asset creates new opportunities to explore their role in inputs, outputs, or both when generating digital twins of study patients in future DTG releases. An early exploration of ptau-217 as a clinical outcome. AD DTG 4.2 incorporates two biomarkers from the updated data asset, p-tau217 and GFAP. P-tau217 is a sensitive and specific marker of Alzheimer's pathology, correlating with amyloid accumulation, tau burden, brain atrophy, and physical degradation - and notably does not predict such changes in patients with other neurodegenerative disorders, making it highly specific to Alzheimer's disease. This specificity makes it a compelling feature for modeling disease progression. With this release, the model can now predict longitudinal changes in ptau-217 concentration as a clinical outcome, a capability Unlearn is optimistic about as Unlearn continue to grow and validate the underlying dataset. This capability may help support broader biomarker modeling within the AD DTG framework for future model updates. In addition, treating ptau-217 as the sole input to the model can provide prognostic information for other outcomes commonly measured in Alzheimer's trials. What's next. This biomarker work builds on the validated foundation of the AD DTG, which has already demonstrated meaningful impact in Alzheimer's studies. In retrospective analyses, digital twins of study participants have supported sample size reductions of up to 15% and up to 33% in control arms using Unlearn's EMA-qualified and FDA-supported method. As Unlearn continue to grow and enrich its AD dataset, now trained on over 25,000 patient records spanning cognitively normal individuals through moderate Alzheimer's disease, the model will be positioned to support increasingly robust biomarker modeling and stronger digital wins in future DTG releases. Blog.

Associated Press
Mar 10th, 2026
Unlearn deploys AI digital twins to strengthen SOLA Biosciences' Phase 1/2 ALS gene therapy study

Unlearn, a San Francisco-based AI company, will support SOLA Biosciences' Phase 1/2 clinical study of SOL-257, an investigational gene therapy for amyotrophic lateral sclerosis. The partnership will use AI-generated digital twins to strengthen the early-phase study. The single-arm trial will use digital twins as external comparators to help interpret clinical outcomes, addressing challenges posed by disease heterogeneity and small sample sizes in early-stage ALS studies. Unlearn's digital twins are created by a machine-learning model trained on extensive patient-level historical ALS data. The collaboration will support trial planning, regulatory engagement and participant-level analyses during the Phase 1/2 study and long-term follow-up. Unlearn has secured EMA qualification and FDA support for its digital twin technology in clinical trials.

Associated Press
Feb 24th, 2026
Unlearn refines AI model for Huntington's disease trials using CHDI Foundation data

Unlearn, an AI company specialising in clinical development, will use data from CHDI Foundation's Enroll-HD research platform to refine its Huntington's disease-specific Digital Twin Generator. The machine learning model generates individualised forecasts of disease progression using longitudinal, patient-level data. Enroll-HD is a global clinical research platform with over 22,000 active participants across 157 sites in 23 countries. CHDI Foundation is a privately funded nonprofit exclusively dedicated to developing Huntington's disease therapeutics. Unlearn's AI-generated digital twins are used in clinical trials to reduce variability and strengthen treatment effect estimation. The company has received EMA qualification and FDA support for applying AI in clinical trials. The collaboration aims to improve how Huntington's disease trials are designed and analysed.

Associated Press
Jan 28th, 2026
Unlearn launches TrialPioneer AI workspace to accelerate clinical trial planning

Unlearn, a leader in AI solutions for clinical development, has launched TrialPioneer, an AI-powered workspace designed to accelerate decision-making in upstream trial planning. The platform helps clinical development teams optimise study designs by consolidating evidence, assumptions and scenario evaluations in one workflow. TrialPioneer integrates three capabilities: Scout for AI-powered precedent review from sources like PubMed and ClinicalTrials.gov; Hindsight for exploring historical benchmarks using patient-level data; and SimLab for on-demand trial simulations comparing design scenarios. The workspace addresses fragmentation in planning workflows by making assumptions explicit and traceable, enabling teams to evaluate trade-offs earlier and align on study designs. Unlearn has received EMA qualification and FDA support for its science-first approach to applying AI in clinical trials.

Yahoo Finance
Sep 25th, 2025
Dr. Robert Lenz Joins Unlearn as Strategic Advisor

Dr. Robert Lenz joins Unlearn as strategic advisor.