In this episode of “In the Interim…,” host Dr. Scott Berry examines the challenge of communicating complex statistical concepts to non-statistical audiences. Drawing from firsthand experiences in agriculture, professional golf, and clinical development, as well as examples involving historical and scientific figures, Scott reflects on why technical rigor alone often fails to influence. The discussion focuses on the consequences of mismatched language, the importance of empathy, and the utility of simulation when bridging the gap between analysis and stakeholder understanding.

Key Highlights

• Illustrated barriers to statistical communication using stories from farming, golf, and early career encounters.
• Examples involving John Glenn, Ada Lovelace, and Charles Babbage show how communication, not just science, determines impact.
• Insights from Alan Alda on empathy as a foundational tool for scientists presenting technical ideas.
• Clinical trial simulations revealed knowledge gaps—such as misunderstanding of power—when communicating with decision-makers.
• Emphasizes the necessity of translating analytic outputs into operational, financial, or clinical language for meaningful impact.

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In this episode of "In the Interim…", host Dr. Scott Berry and frequent co-host Dr. Kert Viele, Senior Statistical Scientist at Berry Consultants, analyze the potential shift in FDA regulatory policy from requiring two independent trials to accepting a single trial as sufficient for “substantial evidence” in drug approvals. Reflecting on the statutory and regulatory definitions originating with the 1962 Federal Food, Drug, and Cosmetic Act and 21 CFR 314.126, they dissect current and emerging interpretations, referencing recent statements by Dr. Martin Makary and coverage described in a STAT article. The conversation focuses on the scientific and statistical foundations of the two-trial threshold, challenges with dichotomous results, and how pooled evidence might increase efficiency and rigor. They discuss statistical implications including alpha thresholds, sample size effects, program power, and the consequences for clinical labeling. The episode also introduces Bayesian approaches as a method for integrating totality of evidence. Attention is given to both population breadth and the possible risks of a narrowed evidentiary base under a single-trial standard.

Key Highlights

• Regulatory and historical context of “substantial evidence” since 1962 and current FDA directives.
• Industry practice: simultaneous Phase III trials, statistical power, and evidentiary replication.
• Criticism of binary, trial-level significance thresholds; merits of pooling or meta-analysis.
• Potential efficiency gains and tradeoffs with a more stringent alpha requirement for single trials.
• Strategic and operational effects on trial design, sample size, and label indications.
• Bayesian statistical approaches for full evidence integration, discussed as an analytical viewpoint.

In this episode of "In the Interim…", Dr. Jenny Devenport, Global Head of Methods, Collaboration, and Outreach at Roche, joins Dr. Scott Berry for a detailed discussion on career evolution, statistical culture, and communication in the pharmaceutical industry. Dr. Devenport describes her transition from psychology in New Mexico to statistical leadership in Basel, emphasizing the formative role of early academic mentors and her experience working across the US and Europe. She outlines her current functions in methods development, internal collaboration, and industry outreach, highlighting active engagement with academic and regulatory communities. The episode scrutinizes differences in workplace culture, such as the emphasis on debate and long-term collaboration in Europe, and differences in educational backgrounds among statisticians. The conversation covers practical barriers and slow adoption of Bayesian methods and the importance of communication in the acceptance of futility analyses in pharma, the importance of scale in problem-solving, and the emergence of AI as a tool for statisticians. Dr. Devenport provides pragmatic strategies for statisticians to improve their influence through tailored, audience-specific communication.

Key Highlights

• Dr. Devenport’s academic and geographic move from the US to Europe
• Responsibilities in methods development, collaboration, and outreach at Roche
• Contrasts in US and European pharmaceutical statistics cultures
• Measured perspective on AI’s effect on statisticians’ responsibilities
• Practical guidance for statisticians on communication and influence