Thursday June 17 2021

Hi3+3: A Model-Assisted Dose-Finding Design Borrowing Historical Data

Join Yuan Ji, Professor of Biostatistics at The University of Chicago, for a new webinar on a recent publication.

Yuan Ji will discuss his recent publication, Hi3+3: A Model-Assisted Dose-Finding Design Borrowing Historical Data, in the webinar presentation. The purpose of the publication was based on a hybrid design that partly uses probability models and partly uses algorithmic rules for decision making. The aim is to improve the efficiency of the dose-finding trials in the presence of historical data, maintain safety for patients, and achieve a level of simplicity for practical applications.  

To read the full-text paper click below.

Read the Paper

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Meet the Speaker: Yuan Ji

Yuan Ji, Ph.D. is currently the Professor of Biostatistics (with tenure) at The University of Chicago. He spent 9 years at The University of Texas M.D. Anderson Cancer Center, holding tenure-track and tenured faculty positions. 
He is internationally known for his work on designs of dose-finding trials, adaptive dose insertion, seamless and overlapping phase I/II trials, immune-oncology studies, and subgroup enrichment approach. He is also an expert in bioinformatics and computational biology, with a deep understanding of translational medicine. 
He has published over 100 peer-reviewed papers in top journals across different scientific disciplines, including Nature Methods, Journal of Clinical Oncology, Journal of the National Cancer Institute.