2026 Boston Pharma Statistics Symposium - Day 1, Short Courses - Virtual
About this Event
Tickets on this page are for virtual attendees of the short courses. To attend the courses in person, use instead. Tickets for the main event on November 13 can be found on .
All participants must register by Friday, November 6, 12 pm EST. The registration fee covers short course materials.
Join us at the 2026 Boston Pharmaceutical Statistics Symposium on November 12-13, hosted by the Boston Chapter of the American Statistical Association (BCASA). The 2025 symposium theme is Transforming Clinical Development Through Data Science, Innovative Design, and Statistical Excellence. This annual event, held at Novo, 75 Hayden Avenue, offers a unique platform for sharing cutting-edge statistical applications and research in the biotech-pharma industry.
It's an ideal opportunity for industry statisticians, academics, students, and professionals interested in pharmaceutical statistical topics to connect and exchange insights within Greater Boston's thriving pharmaceutical community. The symposium features a full day of engaging activities, including thought-provoking invited talks, a dynamic poster session, and ample networking opportunities. Two short courses will be offered on November 12, one day before the main symposium.
Don't miss enhancing your knowledge and expanding your professional network. Mark your calendar now and be part of this impactful event!
Short courses:
- 9 am–12 pm: AI Infrastructure for Biostatistics: From Evidence to Statistical Agents, presented by Jimeng Sun of Keiji AI and the University of Illinois Urbana-Champaign and Yilong Zhang of BBSW.
- 12 pm–1 pm: Lunch break
- 1 pm–4 pm: Practical Large Language Models: Foundations & Applications, presented by Xing He, PhD, and Haoran Ding, PhD, with Jiale Zhang, MS, serving as course facilitator.
Abstracts
AI Infrastructure for Biostatistics: From Evidence to Statistical Agents
Abstract: What if clinical trials could learn from all prior evidence, anticipate risk earlier, and guide better decisions before execution? In this talk, I will present a forward-looking view of AI agents for clinical trials, highlighting recent advances in evidence synthesis, trial representation, patient-trial matching, and outcome prediction. Based on peer-reviewed research and deployed systems, I will share where AI is already creating value, what challenges remain, and how these technologies may evolve to support statistical and analytical workflows in the near future. The session blends aspiration with practical insights and a brief product demonstration.
About the instructors
Jimeng Sun
Jimeng Sun is affiliated with Keiji AI and the University of Illinois Urbana-Champaign. Jimeng Sun asked the organizers to use the biography and photograph from the Duke University program page for “Reimagining Clinical Trials with AI Agents.” The full biography was not reproduced in the email.
Yilong Zhang
Yilong Zhang, PhD, is an AI committee member at the Bay Area Biotech‑Pharma Statistics Workshop. Previously, he was a statistician at Merck & Co., Inc., supporting late-stage clinical development. His interests include AI-first workflows and open-source R and Python tools for clinical trial development and regulatory submission. Yilong has published more than 30 peer-reviewed articles and holds a PhD in Biostatistics from New York University.
Practical Large Language Models: Foundations & Applications
Abstract: This introductory, practice-oriented course provides participants with a clear understanding of how modern large language models (LLMs) work and how to apply them effectively in real-world contexts. The course begins with an accessible overview of LLM fundamentals, including how models are trained, how they process information, and their current capabilities and limitations. Building on this foundation, participants will explore practical techniques such as retrieval-augmented generation (RAG), structured outputs using JSON schemas, and the use of tools and agentic workflows. Realistic examples will be drawn from pharmaceutical and biomedical domains, such as answering questions from scientific documents with citations. By the end of the course, participants will have the skills to build simple and interpretable LLM-based applications.
About the instructors
Xing He, PhD
Xing He is Assistant Professor in the Department of Biostatistics and Health Data Science at Indiana University School of Medicine and Faculty Lead for Strategic Data Science Infrastructure at the Regenstrief Institute. Xing He’s research centers on clinical NLP, computable phenotyping, and agentic AI systems that turn unstructured clinical text into research-ready evidence, with applications in real-world evidence generation and target trial emulation.
Haoran Ding, PhD
Haoran Ding is a Postdoctoral Fellow in the Department of Biostatistics and Health Data Science at Indiana University School of Medicine. Haoran Ding holds a PhD in Computer Engineering from Purdue University Indianapolis. Haoran Ding’s research applies NLP and large language models to electronic health record data, combining clinical narratives with structured EHR data for biomedical phenotyping and clinical risk detection.
Jiale Zhang, MS, Course Facilitator
Jiale Zhang is a PhD student in the Department of Biostatistics and Health Data Science at Indiana University School of Medicine. Jiale Zhang’s research applies NLP and large language models to clinical notes and literature mining, with a focus on building biomedical knowledge graphs from unstructured text. Jiale Zhang will support the hands-on exercises as course facilitator rather than serve as a lecturer.
More information on the 2026 Boston Pharmaceutical Statistics Symposium can be found on our website.
Our Sponsors
We thank our colleagues at Novo for hosting this event. Financial support from our sponsors is gratefully acknowledged.
- Platinum sponsor: Sanofi, Insilicom, Cytel
- Gold sponsor: Takeda, Alnylam, Servier, PhaseV, Roche/Genentech, Stat4Ward
- Silver sponsor: Astellas and Metrum
- Poster sponsor: ASA Biopharmaceutical Section
- Short course sponsor: Pfizer
Where is it happening?
Event Location & Nearby Stays:
USD 35.00 to USD 200.00
