Sanofi x STATION F
Our Ambition
Our ambition is to be an immunoscience powerhouse, redefining immunology as we know it by applying our deep understanding of the immune system to ignite discovery and advance innovative therapies. This is enabled by our pathway-led research approach—the bedrock of our R&D—where a single immune pathway can unlock breakthroughs in seemingly unrelated conditions across Neurology, Rare Diseases, Oncology, and Vaccines. We aim to be a world leader in immunology, redefining the field to discover and advance innovative therapies and vaccines.
Read our Global Head of R&D, Houman Ashrafian, on immunoscience and our R&D approach here.
Why Partner With Us
Value proposition for startups
Startups selected for the program will:
1
Work with our top experts
We’ll connect you with Sanofi’s leading scientists and technologists to co-develop and refine your solution.
2
Access exclusive data
We’ll open up proprietary datasets from decades of research to help you train, test, and validate your models.
3
Sanofi as a client
We’ll offer partnership pathways for promising MVPs , with the potential to become a supplier or collaborator
Who We Are
Sanofi is an R&D driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. We apply our deep understanding of the immune system to invent medicines and vaccines that treat and protect millions of people around the world, with an innovative pipeline that could benefit millions more. Our team is guided by one purpose: we chase the miracles of science to improve people’s lives; this inspires us to drive progress and deliver positive impact for our people and the communities we serve, by addressing the most urgent healthcare, environmental, and societal challenges of our time.
Who Should Apply
Eligibility
- All startups are encouraged to apply.
- No prerequisites, as long as you think you can address one of our key challenges
- We want new ideas – including from outside our industry
Maturity
- You have already built an MVP that shows your capabilities
- Pre-seed to seed B
Location
- There is no fixed requirement – but it would be great to collaborate in-person
- Worldwide startups can apply
How the Program Runs
Timeline
- Applications open: March 31st to May 3rd 2026 at 11:59 PM CET
- Interviews with Sanofi teams : second half of May
- First cohort launch : June
- Total duration: 3-6 months on average depending on the challenge vertical you pick
Organization
- Weekly: Check‑in with a Sanofi Program manager (PM).
- Every quarter: Steering Committee with R&D leaders.
- Ad‑hoc sessions with subject‑matter experts as evaluated by PM.
Benefits & costs
- No equity – you don’t have to give up equity to participate
- No cost – Sanofi covers your STATION F fees
- Potential to have Sanofi as a client incl. potential budget extension pending success
The Challenges We’re Trying to Solve
Build interacting AI agents
Objective: Understand how different agents in a system behave and influence each other and react to changing conditions
Technical problem: Build an agent-based model that captures individual behaviors and interactions over time and space, using real-world data to make it accurate
Predict networks interactions
Objective : Predict how a network reacts when one-part changes, e.g. Forecasting ripple effects in a system
Technical problem : Build a mathematical model that can simulate time-based interactions, feedback loops, and cross-talk between many interconnected signals
Structure, analyze & vizualize bio-data
Objective: Connect different types of complex data into a single system to uncover patterns and make smarter decisions
Technical problem: Harmonize and analyze large-scale, heterogeneous datasets using scalable architecture and advanced analytics
Model entire ecosystems
Objective: Simulate how different environments respond to an identical change
Technical problem: Build a computational framework that accounts for local differences, dynamic responses, and interactions across environments
Understand system failures
Objective: Understand when and why a system goes off track, starts attacking itself or stops working entirely
Technical problem: Build a model that simulates how different parts of a system behave, interact, and spiral out of control over time, using real-world data to make it accurate
Connect Labs around the world
Objective: Strengthen a digital backbone that lets automated labs in different regions work as one system
Technical problem: Create modular solutions that complement our automated labs by enhancing data harmonization, predictive analysis, and collaboration workflows all while staying secure and scalable
Agentic portfolio analytics
Objective: Create AI solutions that synthesize large external unstructured datasets to support dynamic, AI-driven decisions
Technical problem: Develop agents that combine and analyze diverse data (incl. Real time market updates), to provide insights that support portfolio analysis and risk assessment with Human-in-the-loop decision-making.
Apply Now
MAT-GLB-2601318