The blog by Kert Viele discusses the tradeoffs of using external or synthetic data in clinical trials, highlighting how aggressive use can save patient resources but risks scientific robustness, and emphasizes the importance of understanding the agreement between synthetic and actual trial data to optimize inferential performance while minimizing patient enrollment.

Since March 2020, Berry Consultants LLC has been collaborating with the Los Angeles County Department of Health Services to develop COVID-19 hospital demand modeling projections, utilizing an SEIR epidemiologic model to predict hospital needs and assess the impact of physical distancing measures, with their findings prominently featured in various media outlets.

The article emphasizes the importance of optimizing clinical trial designs by investigating multiple therapies simultaneously and utilizing strategies like Bayesian thinking and platform trials to significantly reduce the time and resources needed to identify effective treatments for difficult medical conditions.

Highly powered clinical trials are costly and often yield statistically significant but clinically meaningless results due to large sample sizes designed to mitigate random errors, suggesting the need for alternative approaches like flexible sample sizes and group sequential designs to optimize resource use and improve trial efficiency.

Kert Viele discusses the challenges and probabilities of success in a drug development program, highlighting that a standard approach often leads to a high rate of failure due to poor dose selection in early trials, but suggests that a revised strategy of continuous patient allocation and dose escalation can significantly improve the chances of successfully bringing an effective therapy to market.

Kert Viele discusses the concept of historical borrowing in clinical trials, highlighting its potential benefits and risks, particularly in relation to FDA guidance and the importance of assessing "drift" to determine when it is appropriate to utilize historical control data for improving trial efficiency and accuracy.