Please scroll down to the bottom of the page for the most recent upcoming events
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Boston Chapter of the ASA Webinar: A Perspective Review of FDA's Draft Guidance on the Use of Bayesian Methodology in Clinical Trials of Drug and Biological Products
Join the Boston Chapter of the ASA for an insightful 1-hour webinar featuring Dr. Yuan Ji, Professor of Biostatistics at The University of Chicago, as he shares his perspective on the FDA's Draft Guidance on the Use of Bayesian Methodology in Clinical Trials of Drug and Biological products
Date: Tuesday, March 3, 2026
Time: 12:00 AM – 1:00 PM ET
Location: Online (Zoom link will be provided to registered attendees)
Cost: Free
Don't miss this opportunity to gain expert insights into the recently released FDA's Draft Guidance on the Use of Bayesian Methodology in Clinical Trials of Drug and Biological products!
Registration Link
Abstract:
This review provides a foundational illustration of Bayesian philosophy as a logical framework for scientific inference, tracing its historical evolution, probability-theoretic underpinnings, and natural connection to human decision-making. I examine the FDA's January 2026 draft guidance, highlighting key provisions relevant to Bayesian methods in clinical trials, with particular emphasis on Phase 3 pivotal studies. Central concepts—including Type I error control, error rate calibration, multiplicity adjustment, and sequential decision-making—are discussed in the context of both calibrated and non-calibrated Bayesian designs. Future perspectives on optimizing Bayesian methods for clinical development are presented, including the practice of calibrating Bayesian decision rules against frequentist Type I error rates. Finally, practical recommendations are proposed for the appropriate application of Bayesian designs and success criteria in regulatory submissions approach improves the precision of treatment effect estimates while reducing the biases associated with borrowing data from external sources.
Reference: Ji, Y., & D, Ph. (2026). Regulatory Expectations for Bayesian Methods in Drug and Biologic Clinical Trials: A Practical Perspective on FDA’s 2026 Draft Guidance (Version 1). arXiv. doi.org/10.48550/ARXIV.2601.14701. Read More
About the Speaker:
Dr. Yuan Ji is Professor of Biostatistics at The University of Chicago. His research focuses on innovative Bayesian statistical methods for translational cancer research. Dr. Ji is author of over 200 publications in peer-reviewed journals including across medical and statistical journals. He is the inventor of many innovative Bayesian adaptive designs such as the mTPI and i3+3 designs, which have been widely applied in dose-finding clinical trials worldwide. His work on cancer genomics has been reported by a large number of media outlets in 2015. He received Mitchell Prize in 2015 by the International Society for Bayesian Analysis. He is an elected fellow of the American Statistical Association.
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Registration is now open for the Women in Data Science (WiDS) Conference Cambridge, taking place Friday, March 6th from 8:00am - 2:30pm ET at the Microsoft NERD Center, One Memorial Drive in Cambridge, MA.
In collaboration with WiDS Worldwide, MIT and Microsoft Research New England are proud to host the annual conference, which features an all-female line up of speakers and panelists from academia and industry talking about the latest in data science research and applications.
Learn how researchers and leading-edge companies are leveraging data science for success, and connect with potential mentors, collaborators, and others in the field. All genders are invited to attend!
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Poster Session
Students, postdocs, and early researchers interested in presenting a poster for the WiDS Cambridge conference can submit an abstract by Wednesday, February 11th, 11:59 pm. Email wids-posters@mit.edu with any questions regarding poster submissions.
Email wids-cambridge@mit.edu with any other questions.
We’re looking forward to seeing you! -
WiDS Cambridge Planning Committee @ MIT IDSS
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The May Institute on Computation and Statistics for Mass Spectrometry and Proteomics!
May Institute is taking place on April 27 – May 9, 2026, on the campus of Northeastern University in Boston MA.
For the first time, Northeastern University is issuing an e-badge recognizing successful completion of the May Institute. The e-badge can be displayed on LinkedIn and other social media.
Also new this year, we have a greater focus on AI. We also introduce "bring your own data" sessions, where you can get assistance analyzing your own data.
We gratefully acknowledge the support of our sponsors Biognosys and Fragmatics.
Participants can select a subset of the following programs:
* April 27 - April 28: Quantitative proteomics with Skyline: Susan Abbatiello, Brendan MacLean, Lindsay Pino
* April 28: AI in action: from drug discovery to regulatory insight: Romi Singh, Wengong Jin
* April 29: Quantitative proteomics with FragPipe: Alexey Nesvizhskii, Fengchao Yu
* April 30 - May 1: Beginners R and beginners statistics: Ryan Benz
* April 30 - May 1: Intermediate R, data visualization and statistics: Kylie Bemis
* April 30 - May 1: Applied Python for data analysis and beginners statistics: Arzu Tuğçe Güler
* May 4 - May 6: Statistics for quantitative mass spectrometry & bring your own data clinic featuring a Spectonaut support specialist and MSstats developers: Brian Searle, Olga Vitek, Devon Kohler, Monika Pepelnjak
* May 7 - May 8: Interpretation of proteomic experiments in the context of biomolecular networks with INDRA: Ben Gyori
* May 7 - May 8: Analysis of mass spectrometry images with Cardinal & bring your own data clinic: Kylie Bemis
* May 9: Frontiers in computational methods
-- Michelle Li, Deep learning models for understanding protein interaction networks and phenotype-driven diagnosis of rare genetic diseases
-- Ed Huttlin, Integration of structural predictions and protein interactions for interpretation and discovery
-- Theodore Alexandrov, Metabolite annotation for imaging mass spectrometry using METASPACE
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MIT Statistics and Data Science Conference 2026
(SDSCon 2026)
We are pleased to invite you to MIT SDSCon 2026, hosted by the Statistics and Data Science Center on Friday, April 10th
Registration is open here for this year’s event, which will be held on the 8th floor of 51 Vassar Street (Bldg 45) at MIT. Additional information and the agenda can be found at https://sdscon.mit.edu
SDSCon 2026 is a celebration and community-building event for those interested in statistics. Presentations will cover applications of statistics and data science across a wide range of fields and approaches.
As part of the Institute for Data, Systems, and Society (IDSS), the Statistics and Data Science Center (SDSC) is an MIT-wide focal point for advancing academic programs and research in statistics and data science.
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