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    • Fri, April 23, 2021
    • 09:00 - 10:00 (PDT)
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    Fri, April 23, 2021, 09:00 – 10:00AM (PDT), 12:00 – 1:00PM (EST)

    Abstract

    According to a recent report, nearly 70% Phase II trials failed to move forward to Phase III. Part of the reasons caused such high failure rate could be inefficient trial design and trial monitoring. In this talk, we introduce the concept of dynamic data monitoring (DDM) for ongoing clinical trials. We develop the principles and procedures for dynamically monitoring on-going clinical trials and demonstrate that the accumulative treatment effect can be automatically estimated and continuously accessible over the information time. Building on the adaptive group sequential (AGS) methods, and by taking the advantage of modern eClinical technologies, we developed a clinical trial “radar” system on which the Wald statistics, conditional power, trend, timing for sample size re-estimation, alerting of early stopping for efficacy and/or futility can be automatically displayed. Thus, the trial can be intelligently monitored. Through simulation, we demonstrate the power of DDM in guiding a promising trial to success or detecting a “hopeless” trial to stop. We provide an example of DDM application in the 1st remdesivir trial in Wuhan China.


    Speaker:

    Dr. Tai Xie received Ph.D. in Applied Math and Statistics from University of Arizona in 1993. Right after his Ph.D., he worked at the Arizona Cancer Center (AZCC) for three years. From 1996-2004, he worked for Pfizer for 5 years, JNJ for 2 years and Eli Lilly for 2 years holding various positions from Sr. Biostatistician to Associate Director. He founded Brightech International in 2004, a data focused CRO and acquired Shanghai Magnsoft Software Development Ltd (Magnsoft) in 2009, the first EDC company in China. Magnsoft was renamed as CIMS Global. He serves as CEO for both companies with over 90 employees in US and over 50 in China and Taiwan. He also served as CEO for Biopharm Solutions for 3 years, a biotech company focused on innovative drug delivery technologies. Dr. Xie is an Adjunct Assistant Professor of Biostatistics Department, School of Public Health at the Rutgers University. He has extensive experience in innovative trial design and statistical analysis and reporting, clinical data management, EDC, eClinical and eHealth. In recent years, Dr. Xie has been actively interacting with the regulatory authority and drug industry in China. He was invited several times by China's CFDA to participate in authoring the guidance on EDC and by influential professional organizations (such as China Heart Congress, CHC) to deliver courses and speeches on a variety of topics. Dr. Xie is also an active researcher with a number of research papers published in distinguished journals on various topics including cancer prevention, adaptive design, dynamic data monitoring, survival analysis, personalized medicines and more.


    Joe Shih Bio

    Dr. Joe Shih, Professor Emeritus of Biostatistics (July 1, 2019), and former Chair of Biostatistics Department (1999-2017), School of Public Health, and Director of Biometrics Division of the Cancer Institute of New Jersey (1999-2019), Rutgers University – the State University of New Jersey. Prior to joining academia, he spent 17+ years at Merck Research Laboratories.  He served in the US FDA’s Advisory Board for reviewing new drug applications.  He is a distinguished statistician and opinion leader in industry and academia.  He has collaborated extensively with physicians in various therapeutic areas and published over 160 papers in statistical methodology and medical research. His book “Statistical Design and Analysis of Clinical Trials” is a top-chosen graduate-level textbook for many universities.  His expertise includes adaptive designs and missing data issues in clinical trials, and evaluation of therapeutic interventions. He is an ASA (American Statistical Association, 1996) Fellow and elected Member of the International Statistical Association (ISI, 2001).





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