The Biopharmaceutical Report editorial team invited authors from government, industry, and academia to write articles about their perspectives on the impact of COVID-19 on clinical trials, particularly the statistical issues involved in designing new COVID-19 trials. The 2020 fall issue includes these articles.
Steve Wolf of Duke University, Peter Mesenbrink of Novartis, Herbert Pang of Genentech, and Xiaofei Wang of Duke University report a survey of COVID-19–related clinical trials based on the data extracted from Clinicaltrials.gov as of early October 2020. The article sets the stage for discussion about the status of and possible future design and statistical analysis issues in developing a safe and effective vaccine and treatments for COVID-19.
Zachary McCaw of Google, Lu Tian of Stanford, and Lee-Jen Wei of Harvard summarize recent work about how to quantify treatment effect and competing risk in COVID-19 clinical trials.
Peter Mesenbrink of Novartis shares his experience designing several COVID-19 trials.
Mitchell Thomann, Michael Durante, and Paul Berg of Eli Lilly write about simulation studies they conducted to gain insight into choosing optimal study endpoints in a proof-of-concept trial.
Sheng Feng, Amanda Shield, and Andy Wilson of Parexel contribute a short article about the challenges and possible solutions of conducting real-world evidence studies on COVID-19 treatment.
An article by Yongming Qu and Ilya Lipkovich of Eli Lilly provides a comprehensive review of estimands and estimation of treatment effect of clinical trials during COVID-19 in the context of ICH E9.
In this issue, there is also an interview with Margaret Gamalo, the new editor for the Journal of Biopharmaceutical Statistics, and a summary report from Statistical Methods in Oncology Scientific Working Group on type I error considerations in master protocols.
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