Episode

Discussion with Kaspar Rufibach

Podcast
In the Interim...
Published
Dec 1, 2025
Duration seconds
2838
Processing state
not_requested
Canonical source
https://share.transistor.fm/s/f394f058
Audio
https://media.transistor.fm/f394f058/a0737322.mp3
JSON
/v1/public/podcasts/in-the-interim-7211889/episodes/discussion-with-kaspar-rufibach
Markdown
/podcast/in-the-interim-7211889/discussion-with-kaspar-rufibach.md

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Summary

In this episode of "In the Interim...", Dr. Scott Berry interviews Dr. Kaspar Rufibach, Co-Head of Advanced Biostatistical Sciences at Merck. The conversation tracks Rufibach’s evolution from academic training in actuarial and mathematical statistics through cancer research collaborations, postdoctoral work, and academic consulting, leading to applied roles in Roche and Merck. Discussion centers on methodological rigor, pragmatic approaches to assurance and predictive probability, and real-world experience in drug development. Rufibach examines the organizational integration of quantitative disciplines at Merck—incorporating pharmacology, real-world data, statistics, programming, and data science—while remaining candid on the role and boundaries of AI in current pharmaceutical practice. Key Highlights Statistical education in Switzerland, bridging theory and early applied cancer trial experience Move from academic consulting to a trial statistician role at Roche, emphasizing structured problem-solving in drug development Approach to predictive probability and assurance, balancing Bayesian and frequentist tools with strict emphasis on practicality Formation of professional special interest groups with EFSPI and PSI, stepping in to address unmet community needs rather than seeking formal leadership Perspective on Merck’s unified quantitative department, designed to remove silos and leverage interdisciplinary expertise Cautious view of AI as a complement to specific tasks, but not yet a replacement for nuanced clinical trial design or regulatory-facing strategies Current focus on expanding causal inference methods and multi-state modeling for improved trial efficiency and evidence synthesis For more, visit us at https://www.berryconsultants.com/