This chapter explores the collaboration between academia and pharmaceutical companies in addressing safety analysis challenges in clinical trials. It highlights the importance of trust, structured data-sharing, and teamwork in analyzing adverse events, showcasing successful outcomes influenced by real data application. The discussion emphasizes the need for statisticians to effectively convey the significance of their findings to drive meaningful improvements in safety analysis methods.
✔ How differing follow-up times and censoring bias AE results.
✔ The role of the Aalen–Johansen estimator and why it should be standard practice.
✔ What the SAVVY collaboration achieved by uniting pharma, academia, and regulators.
✔ Real-world examples of how safety analyses can dramatically change the interpretation of treatment risk.
✔ Lessons on collaboration, methodology, and change management in the pharma industry.
Why You Should Listen:
Adverse events are a critical part of any trial, yet they’re often analyzed using simplistic methods that can mislead decision-makers. This episode will help you:
Gain insights you can apply immediately to your own projects to improve the accuracy and credibility of your analyses.
Understand the hidden biases in traditional AE analysis.
Learn how to align safety and efficacy assessments for a fairer benefit–risk evaluation.
Discover the power of collaboration between pharma, academia, and regulators through the SAVVY project.
🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills.
🔗 My New Book: How to Be an Effective Statistician - Volume 1– It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine.
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