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    • Fri, January 29, 2021
    • 09:00 - 10:00 (PST)

    Fri, January 29, 2021, 09:00 – 10:00AM (PDT), 12:00 – 1:00PM (EST)


    Clinical trials of treatments for coronavirus disease 2019 (COVID-19) draw intense public attention. More than ever, valid, transparent, and intuitive summaries of the treatment effects, including efficacy and harm, are needed. In this talk, we will discuss the issues of the study endpoints selection and how to quantify and interpret the treatment difference using various endpoints. Specifically, we will talk about the concerns for the current COVID-19 trials and proposals for alternative procedures discussed in the attached publications.


    L.J. Wei is a professor of Biostatistics at Harvard University. Before joining Harvard, he was a professor at University of Wisconsin, University of Michigan, and George Washington University. His main research interest is in the clinical trial methodology, especially in design, monitoring and analysis of studies. He has developed numerous novel statistical methods which are utilized in practice. He received the prestigious Wald Medal in 2009 from the American Statistical Association for his contribution to clinical trial methodology. He is a fellow of American Statistical Associating and Institute of Mathematical Statistics. In 2014, to honor his mentorship, Harvard School of Public Health established a Wei-family scholarship to support students studying biostatistics. His recent research area is concentrated on translational statistics, the personalize medicine under the risk-benefit paradigm via biomarkers and revitalizing clinical trial methodology. He has more than 220 publications and served on numerous editorial and scientific advisory boards for governments and industry. L. J. Wei has extensive working experience in regulatory science for developing and evaluating new drugs/devices.

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Past events

Fri, November 13, 2020 Telehealth and Other Advancements in Healthcare Technology Spurred by COVID-19
Fri, October 02, 2020 A New Measurements-Based Approach to Machine Learning for Bioinformatics
Fri, September 25, 2020 Under the hood of 1Point3Acres COVID-19 map & tracker
Fri, August 28, 2020 Demystifying the drop-outs in single cell RNA-seq data
Fri, July 17, 2020 Using multiple natural experimental designs to triangulate the impact of a policy change
Fri, May 29, 2020 How AI is changing the financial service industry
Fri, March 13, 2020 AI Drug Discovery and Repurposing
Fri, February 28, 2020 The i3+3 Design: A Rule-Based Dose-Finding Approach for Phase I Trials
Fri, December 13, 2019 Statistical Considerations in the Clinical Development of Novel Cancer Therapies
Fri, November 15, 2019 15 Tips on Making Better Use of R Markdown
Wed, October 02, 2019 Principles of Data Science
Fri, September 20, 2019 AI Derived Personalized Solution: The Key Driver in the Era of Digital Health
Fri, August 09, 2019 Scalable Automatic Machine Learning with H2O
Fri, June 07, 2019 Network Meta-Analysis for Decision-Making
Fri, May 03, 2019 Global Prediction of Gene Regulatory Landscape Using Bulk and Single-Cell RNA-seq
Fri, March 08, 2019 Innovative adaptive design for immune-oncology trials
Fri, February 22, 2019 Survival analysis methods for non-proportional hazards
Tue, January 08, 2019 Design of Dose-Response Clinical Trials
Fri, November 16, 2018 Neyman-Pearson Classification Algorithms and NP Receiver Operating Characteristics
Fri, October 19, 2018 Machine Learning in Medical Imaging: the Challenge and Opportunity in Drug Development and Precision Medicine
Fri, September 14, 2018 Disease Heritability Inferred from Familial Relationships Reported in Medical Records
Fri, July 20, 2018 Big Data and Artificial Intelligence in Healthcare
Fri, May 25, 2018 The Genomic Landscape and Pharmacogenomic Interactions of Clock Genes in Cancer Chronotherapy.
Mon, May 21, 2018 Estimation of Treatment Effect under Non-Proportional Hazards
Mon, May 21, 2018 Subgroup Identification in Drug Development: Are Post-Selection Adjustments of Efficacy Useful?
Mon, April 30, 2018 An accurate and robust imputation method scImpute for single-cell RNA-seq data
Fri, March 30, 2018 Genome-scale signatures of gene interaction from compound screens predict clinical efficacy of targeted cancer therapies.
Thu, February 22, 2018 Expression Recovery in Single Cell RNA Sequencing
Wed, January 31, 2018 Single-cell transcriptomics reconstructs fate conversion from fibroblast to cardiomyocyte
Thu, October 19, 2017 Statistical Challenges in Immuno-Oncology, a Cellular Therapies Perspective
Tue, September 26, 2017 Big-Data Analysis Points Toward a New Cancer Therapeutic Discovery Approach
Thu, September 14, 2017 Software Patenting: The Current State of the Law
Mon, August 21, 2017 The Asthma Mobile Health Study, a Large Scale Clinical Study Using ResearchKit

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