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We are currently onboarding a limited number of new programs.

Reach out before our capacity fills

We are currently onboarding a limited number of new programs.

Reach out before our capacity fills

Decision Support for drug
and device development
under uncertainty.

We help life science organizations turn complex scientific knowledge into confident, evidence-based development strategies using advanced analytics, causal ML/AI, and Bayesian decision support.

What Esylos does

[01]

Development Strategy & Decision Support

Integrating knowledge from the earliest development stage and continuously building a causal graph as evidence accumulates allows teams to see the whole program and make decisions that account for downstream consequences.

Open

Core capabilities

Causal AI for decision-making under uncertainty

Expert knowledge mapping and elicitation

Risk-centric development planning

[02]

Innovative Clinical Development

Our experts bring a proven track record of innovative trial design and published methods to help teams design optimal studies that deliver results faster and at lower cost without sacrificing rigor or regulatory acceptance.

Open

Core capabilities

Rare disease trial design and execution

Bayesian adaptive clinical designs

Real-world evidence integration and regulatory strategy

[03]

CMC Statistics & Decision Support

Esylos brings causal reasoning, Bayesian decision support, and deep CMC expertise to help life science teams make confident manufacturing decisions — from process characterization through commercial distribution.

Open

Core capabilities

Regulatory-ready CMC across the full lifecycle

DoE & Bayesian optimization for process understanding

Causal reasoning & digital twins for manufacturing decisions

[01]

Development Strategy & Decision Support

Open

Core capabilities

Causal AI for decision-making under uncertainty

Expert knowledge mapping and elicitation

Risk-centric development planning

[02]

Innovative Clinical Development

Open

Core capabilities

Rare disease trial design and execution

Bayesian adaptive clinical designs

Real-world evidence integration and regulatory strategy

[03]

CMC Statistics & Decision Support

Open

Core capabilities

Regulatory-ready CMC across the full lifecycle

DoE & Bayesian optimization for process understanding

Causal reasoning & digital twins for manufacturing decisions

How Esylos works

1
Define the decision
Frame what actually needs to be decided, and under what constraints. Not the question you wish you could answer, but the one that determines what happens next.
2
Elicit knowledge
Map what your team already knows. Structure expert judgment, uncover hidden assumptions, and build a shared understanding of how the system works before new data arrives.
3
Test and simulate
Run scenarios to compare options, stress-test assumptions, and quantify trade-offs. See what breaks before you commit resources in the real world.
4
Decide with confidence
Clear recommendations grounded in evidence, structured around risk, and designed to hold up under regulatory scrutiny and internal challenge.

The People Behind Esylos

Bruno Boulanger

Senior Scientific Advisor

Description

Bruno is a recognized leader in applied statistics with over 30 years of experience across pharmaceutical and medical device development. He has held senior roles at Eli Lilly and UCB, founded Arlenda in 2003, published over 100 scientific papers, and launched the BAYES conference series.

Arnaud Monseur

CSO

Description

Arnaud is a Bayesian biostatistician with over 10 years in pharma, specializing in innovative statistical methodologies for clinical and CMC development. He serves on the BAYES Scientific Committee and is President of the Quetelet Society, advancing causal inference and Bayesian networks in life sciences.

Sophie Guillaume

CEO

Description

Sophie is CEO of Trilenda — Esylos, Sanaitio & Arlenda. She brings over 30 years of international experience in regulatory consulting and operations, building and scaling organizations in complex regulated environments.

Nils Boulanger

CTO

Description

Nils leads technical architecture and AI-driven decision support at Esylos. With a Master's in Data Science Engineering, he brings expertise in machine learning, healthcare AI, and causal inference, with a focus on robust data infrastructure and patient-centric solutions.

Gaëlle Martin

Head of QA

Description

20+ years in QA leadership. QMS aligned with GMP, GCP, GAMP5, ISO 9001/13485. Computerized system validation and complex GxP projects.

Cédric Dubourg

Head of Software

Description

Cédric is the lead developer behind Arlenda's SmartSTATS platform, with nearly two decades of experience across banking, insurance, and pharmaceutical services. He has built and maintained the platform since 2010, covering Java development, web technologies, cloud infrastructure, containerization, database management, and Linux administration. He has kept SmartSTATS running, secure, and evolving for the past fifteen years.

Who this is for

We help life science organizations turn complex scientific knowledge into confident, evidence-based development strategies using advanced analytics, causal ML/AI, and Bayesian decision support.

Whether you’re a biotech navigating a rare disease or ATMP program, a mid-size pharma team scaling a complex manufacturing process, a HealthTech company developing IVDs, or a big pharma facing high-stakes quality decisions — Esylos is built for exactly this moment.

Who this is for

We help life science organizations turn complex scientific knowledge into confident, evidence-based development strategies using advanced analytics, causal ML/AI, and Bayesian decision support.

Who this is for

We help life science organizations turn complex scientific knowledge into confident, evidence-based development strategies using advanced analytics, causal ML/AI, and Bayesian decision support.

Why Teams Trust Esylos

Built by senior life sciences strategists

Deep experience across clinical development, regulatory strategy, and translational science, combined with advanced expertise in causal inference and Bayesian methods. Over 100 published scientific papers and leadership of the BAYES conference series.

Grounded in regulatory reality

Methods aligned with EMA and FDA expectations, built to support real-world submissions and accelerate regulatory pathways.

Proven track record from discovery to market

Engagements spanning the full product lifecycle, with demonstrated success bringing therapies from early research through clinical development and commercial launch.