Dylan Thibault
Senior Biostatistician building clinical AI systems that hold up in real workflows.
I work at the intersection of biostatistics, healthcare data, and AI product delivery, translating rigorous research practice into tools teams can actually adopt.
publications
years clinical analytics
DCRI Innovator Award
About
Clinical research meets product execution
I'm a Senior Biostatistician at the Duke Clinical Research Institute, where I lead statistical work and AI initiatives across registries, trials, outcomes research, and internal tooling.
My background spans Medicare data, risk prediction, propensity methods, dashboard development, and collaborative publication work across more than 100 papers. The more recent layer of my work is building AI products that make statistical and clinical workflows faster without lowering the bar.
Biostatistics leadership
Cardiovascular registries, clinical trials, health outcomes research, and modeling work that has to stand up to scrutiny.
AI system design
Workflow automation, retrieval systems, QA agents, and domain-specific interfaces for research and clinical operations.
Team enablement
Training analysts and researchers in AI-assisted workflows, modern coding practices, and practical tool adoption.
Education
MS Biostatistics — Georgetown University
BS Biological Sciences — University of Vermont
BA Philosophy — University of Vermont
Recognition
DCRI Innovator Award recipient in 2024 for ChatSum, a meeting-minutes AI product built to reduce coordination overhead for research teams.
Consulting
I help organizations use AI with a bias toward working systems, clear operating constraints, and measurable usefulness. The best engagements sit at the boundary between domain expertise and implementation.
AI strategy and workflow design
Find the highest-leverage places to introduce AI into research, operations, and analytic workflows without creating governance problems later.
Custom internal tools
Build focused applications for document processing, review, consent, summarization, and other domain-specific workflows.
Agent and RAG systems
Design retrieval pipelines, QA agents, and human-in-the-loop review patterns that fit regulated or research-heavy environments.
Team training
Teach teams how to use LLMs, prompt systems, automation, and coding tools in ways that are practical, safe, and repeatable.
Best fit
Teams that need both domain judgment and execution.
Research groups, healthcare operators, and product teams tend to get the most value when the work requires both analytical depth and hands-on delivery.
Typical outcomes
Clear workflow map, scoped tool concept, implementation plan, or shipped prototype.
Open source
I also build with and advise on open-source tools like OpenClaw.
Selected AI Work
The strongest work is not generic AI experimentation. It is domain-specific systems that reduce friction for research teams, reviewers, and patients.
Award-winning internal product
ChatSum — Meeting Minutes AI
GPT-4o powered meeting minutes summarizer. Won the 2024 DCRI Innovator Award.
Why it matters
The best tools remove coordination overhead for clinicians, analysts, and project teams instead of adding a layer of AI theater.
Built with
More systems
Automated SAP Generation
Next.js app using retrieval-augmented generation (RAG) to generate Statistical Analysis Plans. Upload a protocol, receive a tailored, downloadable SAP.
Agent-Based SAP Review
CLI tool with dual-agent framework (drafting + reviewer agents) that iteratively refines SAPs against CRO/industry guidelines.
AI Informed Consent Platform
Real-time patient-facing chatbot for informed consent evaluation. FastAPI + Next.js with GPT-4o/5, evaluating 17 quality metrics for regulatory review.
COVID Resource Calculator
Predictive calculator for hospital resource utilization during COVID — blood products, ventilation, LOS, readmission.
Azure AI Studio
AI-powered content generation studio with TTS, video, and image capabilities using Azure OpenAI.
Publications
Live search powered by the PubMed database.
Searching PubMed…
Experience
The through-line is long-form analytical work paired with increasing product, mentoring, and AI implementation responsibility.
Senior Biostatistician
Duke Clinical Research Institute (DCRI)
- ›Lead AI initiatives: automated SAP generation with RAG, agent-based SAP review, AI-enabled informed consent platforms
- ›Statistical analysis across outcomes, registry, claims, and administrative datasets
- ›Primary supervisor/mentor for junior biostatisticians
- ›Department-wide AI training and biweekly AI office hours
- ›DCRI Innovator Award recipient (2024) for ChatSum meeting minutes AI app
Biostatistician III
Duke Clinical Research Institute (DCRI)
- ›Lead statistician on the Society of Thoracic Surgeons (STS) registry across all three datasets: adult, thoracic, and congenital
- ›Published 50+ peer-reviewed manuscripts including risk prediction models
- ›Built COVID hospital resource utilization predictive calculator
Biostatistician
University of Pennsylvania, Department of Neurology
- ›Data analysis on NIS, Medicare CMS, KID, and NEDS datasets
- ›Statistical methods: survival analysis, mixed effects models, propensity score methods
- ›Published multiple first-author manuscripts in peer-reviewed journals
Projects
Some work is open and visible. A larger share lives behind institutional boundaries, but the technical patterns are consistent across both.
Private systems
AI-powered chatbot to help patients understand clinical trial informed consent documents.
Next.js app for GWTG statistical analysis plans using RAG.
CLI for creating statistical analysis plans with AI assistance.
PRE-EMPT chatbot for clinical trial screening and evaluation.
AI-powered content generation studio with TTS, video, and image using Azure OpenAI.
Download and organize Microsoft Teams meeting transcripts via CLI or web interface.
Web dashboard to check Azure OpenAI model capacity across regions.
This day in American history — daily trivia webapp.
Interactive Tools
Deployed applications
These are working tools used by collaborators and research teams, not gallery pieces. They exist to answer concrete analytic questions quickly.
Built with R Shiny. Hosted on shinyapps.io. Delivered through Duke-affiliated research workflows.
Capabilities
Working range
The common thread is not any single tool. It is the ability to move between rigorous analysis, product thinking, and implementation without losing the shape of the problem.
Statistical Methods
Programming
AI & Tools
Domains
Get in Touch
Let's build something useful.
If you're exploring a clinical AI workflow, an internal research tool, or a team enablement problem, send a note with enough context to make the first conversation concrete.
Consulting engagements and scoped AI tool work
Research collaboration, product strategy, and implementation planning
Speaking, team training, and workflow coaching