Atlas Bio
Atlas Bio provides an AI-powered computational platform that runs in silico clinical trials in immunology, predicting patient responses to treatments before expensive Phase II studies begin. The platform's foundation model, trained on 6.35 billion data points and over 560,000 patient profiles, enables biopharma teams to compare mechanisms, identify biomarkers, and de-risk development decisions in 8–12 weeks.
- Artificial Intelligence
- Biotechnology
- Healthcare Technology
- Drug Discovery & Therapeutics
- Data & Analytics
- Software Only
Funding
Raised to date
$12.5MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
across 2 rounds
LP$2.5M · Pre-Seed
Announced Oct 2026 · from article date
Disclosed cumulative: $12.5M
Founders
Product
Problem
Clinical development programs suffer from high attrition rates, with roughly 90% of trials failing and costs often exceeding $1 billion per program. This uncertainty prolongs time-to-market and inflates R&D budgets for biopharma companies. Limited ability to predict patient outcomes early in the trial design further amplifies financial risk.
Solution
Atlas Bio delivers a computational platform that models human biology at scale to inform trial design and execution. By training a foundational model on 6.35 billion data points and clinical records from over 560,000 patients, the system can generate virtual patient cohorts and forecast endpoint outcomes for proposed protocols. Predictive analytics are delivered through an API-driven analytics engine that integrates with existing R&D workflows, enabling researchers to evaluate multiple trial scenarios in minutes rather than months. The platform's outcome-prediction module quantifies de-risking metrics, allowing sponsors to prioritize the most promising candidates and reduce unnecessary patient enrollment. Cloud-native infrastructure ensures secure, compliant data handling while providing real-time simulation results to support rapid decision-making.
Target Audience
The primary customers are pharmaceutical R&D divisions, biotech firms, and contract research organizations that design and manage early-phase clinical programs and seek data-driven risk mitigation tools.
Features
- Foundational AI model trained on 6.35 billion biomedical data points, capturing multi-omics, phenotypic, and longitudinal clinical information
- Virtual patient cohort generation that mirrors target demographics and disease heterogeneity for in-silico trial simulations
- Outcome prediction engine delivering probabilistic forecasts of primary and secondary endpoints across trial designs
- Full transcriptomic response prediction per patient, not a single score, enabling detailed molecular-level differentiation analysis
- Comparison of multiple mechanisms in the same underlying patient profiles at the same disease state, a comparison no live clinical trial can make
- No prior asset-specific efficacy data or molecular structure required to inform Phase II decisions
- RESTful and GraphQL APIs for seamless integration with existing clinical data management systems and electronic trial master files (eTMF)
- Cloud-native analytics pipeline with auto-scaling compute, ensuring low-latency simulation runs and secure, HIPAA-compliant data storage
- Scenario-comparison dashboard that visualizes risk metrics, power calculations, and cost-benefit analyses for alternative protocols
- Role-based access controls and audit logging to meet GxP and regulatory compliance requirements