Full-Time

Data Partnerships Lead

Posted on 9/19/2025

Unlearn AI

Unlearn AI

51-200 employees

AI-powered patient digital twins for simulations

Compensation Overview

$150k - $180k/yr

H1B Sponsorship Available

Remote in USA + 1 more

More locations: San Francisco, CA, USA

In Person

Category
Business & Strategy (2)
,
Requirements
  • At least 4 years of experience at a pharmaceutical/biotech company, or a technology or technical services company in the pharmaceutical or healthcare industry.
Responsibilities
  • Collaborate with executives to define the data strategy for particular product lines and indications.
  • Drive the execution of data acquisition, including negotiating data usage agreements, pricing, and in-kind services.
  • Work with internal teams to define data requirements for targeted acquisition, technical evaluation of data quality, and resourcing for partnership projects.
  • Survey and understand the landscape of available data to characterize opportunities for specific indications, products, or use cases.
Desired Qualifications
  • Strong experience in oncology.
  • Experience working in data partnerships for clinical trial applications.
  • Experience with data science and machine learning applications on healthcare data.

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

Simplify Jobs

Simplify's Take

What believers are saying

  • AD DTG 4.2 released March 13, 2026, predicts p-tau217 outcomes using enriched biomarkers.
  • Partnerships with SOLA Biosciences for ALS SOL-257 trial and CHDI for Huntington's Enroll-HD.
  • TrialPioneer launched integrates Scout, Hindsight, SimLab to accelerate trial planning.

What critics are saying

  • FDA rejects p-tau217 biomarkers as endpoints, eliminating AD DTG differentiator in 12-24 months.
  • Eli Lilly, Roche internalize AI twins, commoditizing Unlearn's subscription in 18-36 months.
  • Parexel, IQVIA integrate simulations with pharma relationships, eroding Unlearn in 12-24 months.

What makes Unlearn AI unique

  • Unlearn invented TwinRCT using digital twins to reduce control arms by 33% while preserving power.
  • TwinRCTs create prognostic digital twins from baseline data for precise treatment effect estimation.
  • EMA-qualified and FDA-supported digital twins enable smaller RCTs with historical data integration.

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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

-4%

1 year growth

-5%

2 year growth

-2%
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.

The 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.

The 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.

The 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.

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