Causal AI - Workshop
Harness artificial intelligence to discover, model, and simulate real cause-and-effect relationships.
Hands-on program that equips your data science, biostatistics, and R&D teams with the latest Causal AI tools to move beyond correlation, uncover true drivers, and reliably simulate the impact of interventions in meaningful business scenarios.
Workshop Specialities
Automated Causal Discovery from Real-World Data
Uncover hidden causal structures directly from your data
- Learn causal structure directly from EHR, omics, and trial data
- PC, GES, and NOTEARS algorithms in practice
- Combine expert knowledge with data-driven discovery
- Validate and refine discovered graphs against clinical reality
- Immediate application to target identification and biomarker discovery
Double/Debiased Machine Learning & Heterogeneous Effects
Identify who benefits most with precision treatment effect estimation
- Double ML, causal forests, and Bayesian additive regression trees
- Estimate individual treatment effects with correct confidence intervals
- Discover patient subgroups that respond differently
- Methods accepted in regulatory-grade individualised medicine submissions
- Ready-to-use R and Python implementations
Counterfactual Prediction & Individual Intervention Simulation
Answer "what if" questions for every patient and scenario
- Generate accurate "what-if" predictions for every patient or molecule
- Off-policy evaluation and individual-level policy learning
- Simulate dose changes, combination therapies, or label expansions
- Build digital patient twins grounded in causal mechanisms
- Direct use in precision medicine and optimal dosing strategies
Synthetic Data & Causal Digital Twins
Create privacy-safe synthetic data that preserves causal truth
- Generate fully synthetic datasets that preserve causal relationships
- Train and validate models when real data are limited or restricted
- Create enterprise-level digital twins of disease progression and treatment
- Maintain privacy while enabling unlimited experimentation
- Tools used by leading pharma AI labs
Causal AI + Large Language Models Integration
Merge causal reasoning with LLMs for explainable decision support
- Combine causal graphs with LLMs for automated root-cause reasoning
- Natural-language "why" questions answered with causal evidence
- Generate intervention recommendations backed by simulation
- Build explainable AI systems that regulators and clinicians trust
- Live demos with open-source and proprietary models
Industry Applications & Deployment Roadmap
Launch production-ready Causal AI solutions across your pipeline
- Optimal dosing and combination therapy selection
- Safety signal triage and mechanistic adverse-event prediction
- Market-access simulation and payer "what-if" scenario testing
- End-to-end reproducible Causal AI pipelines (MLflow, Weights & Biases)
- Return ready to launch your first Causal AI project within weeks
Bring practical, regulator-focused training directly to your team. Through hands-on workshops I deliver modern biostatistics, causal inference, and industry-standard tools, transforming complex data into clear, submission-ready insights that accelerate approvals and strengthen your pipeline.
Flexible Delivery Options
Intensive Multi-Day Workshops
Typically 2–5 day intensive programs. Fully flexible to match your timeline. Featuring hands-on projects and real-world case studies. Certificate of completion included.
Custom In-House Training
Fully tailored programs at your facility or virtual. Aligned with your tools, processes, and therapeutic areas.
Modular Course Series
Monthly or quarterly workshops for continuous skill development from beginner to advanced levels.
On-Demand Support
Post-training consultation for specific project challenges and expert review of analyses.
Organizations We Train
Pharmaceutical & Biotech
Drug developers, medical affairs, regulatory departments, CROs
Academic Research
Universities, hospitals, government research labs
Public Health
Government agencies, parapublic institutions
Medical Device & MedTech
R&D, clinical affairs, post-market surveillance
Real Applications
12-Hour RWE Intensive for Pharma Company
Delivered a library of training material that is re-used to train and onboard new analysts.
Quarterly Causal Inference Series for Biotech
Monthly office-hours to tackle any challenges faced by client’s teams through Q&A and open discussions about potential solutions and foreseeable difficulties.
Regulatory Biostatistics Onboarding for CRO
Custom small group training to review and enhance statistical analyses of complex biotechnology experiments. Developed re-usable templates tailored to client’s needs for future statistical analyses.
Expert Consultant & Educator
University Teaching Experience
Lecturer at HEC Montreal and ETS Montreal with proven methods for making complex concepts accessible.
Real-World Consulting
Daily work with pharma and biotech organizations ensures training reflects current industry practices.
Thought Leader
Audiences of thousands follow me online for deep and incisive thought-leadership in biostatistics
Customized Content
Tailored to your therapeutic areas, software, regulatory needs, and team levels.
Ongoing Support
Follow-up assistance to ensure successful application of new skills.
Client Feedback
