Bayesian prediction and modeling have emerged as transformative tools in the design and management of clinical trials. By integrating prior knowledge with accumulating trial data, Bayesian methods ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

Okay. Good afternoon, everybody. Thank you for joining us. I'm Doug Tsao, Senior Analyst at H.C. Wainwright. We are thrilled today for what I think is a very unique event. We are joined by Professor ...

This analysis is by Bloomberg Intelligence Industry Analyst Andrew Galler and Senior Associate Analyst Jack Maltby. It appeared first on the Bloomberg Terminal. Clinical trials represent a significant ...

The development of robust clinical trial methodologies increasingly relies on advanced statistical frameworks for model selection and the characterisation of dose–response relationships. With modern ...

We provide a comprehensive review of adaptive phase I clinical trials in oncology that used a statistical model to guide dose escalation to identify the maximum-tolerated dose (MTD). We describe the ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

Clinical trial attrition can be detrimental to clinical outcomes, patient well-being and the financial health of research programs. Clinical trial dropout rates, which range from 15% to 40%, greatly ...

"This research represents a pivotal step in understanding how the immune system responds to vaccines through the use of real-world data collected remotely," said Praduman "PJ" Jain, CEO, Vibrent ...

Looking to get into statistical programming but lack industry experience? We spoke with several statistical programmers from diverse backgrounds, and one thing became clear—there’s no single path to ...