The Effective Statistician - in association with PSI — Подкаст

Will AI Replace Statisticians? The Future of Statistics in Pharma 07.09.2026 24мин

Will artificial intelligence make statisticians obsolete—or make our expertise even more valuable? In this episode, I speak with independent statistical consultant Chris Harbron about how AI could reshape the role of statisticians in the pharmaceutical industry. Our conversation builds on Chris’s paper, Will the Pharmaceutical Industry Need Statisticians in an AI World? We explore what happens when AI generates protocols, statistical analysis plans, programs, and reports. We also discuss why producing a plausible document differs from making sound decisions about clinical development. Chris and I examine the areas where human statisticians continue to add essential value—from navigating trade-offs and challenging assumptions to building trust and accepting accountability. We also share practical ways statisticians can begin working with AI while protecting quality, scientific rigor, and authenticity.

How to Build an Effective Patient-Reported Outcome Strategy for Clinical Trials 01.09.2026 20мин

How can we build a patient-reported outcome strategy that captures the patient voice and strengthens clinical development? In this episode of The Effective Statistician Podcast, I speak with Julia Poritz, Senior Research Consultant on Cytel’s Evidence, Value, and Access team, about developing and implementing an effective patient-reported outcome (PRO) strategy for clinical trials. We discuss how PROs help us understand the effects of a disease and its treatment from the patient’s perspective—including symptoms, physical functioning, health perceptions, and overall quality of life. Julia explains how the Wilson and Cleary model helps us connect these different outcomes and create a clear measurement strategy. We also explore the four essential parts of a PRO strategy: selecting appropriate PRO measures, implementing them within the study, analyzing the data, and reporting the results. Throughout our conversation, we emphasize the importance of early planning, validated measures, patient relevance, regulatory expectations, and comparability with previous clinical trials.

How the R Consortium Is Transforming Regulatory Submissions and AI in Clinical Trials 11.08.2026 18мин

In this episode, I talk with Ning Leng, Ph.D., Director II, Data and AI Acceleration Group, Data & Statistical Sciences at AbbVie, about the growing role of the R Consortium in the pharmaceutical industry. Ning brings extensive experience in statistics, computational genomics, open-source technology, and the adoption of R across the pharmaceutical industry. Before joining AbbVie, she spent 10 years at Roche Genentech, where she helped drive the adoption of R, cloud technologies, Git, and Shiny. We discuss how the R Consortium creates a platform for statisticians, programmers, pharmaceutical companies, and regulators to collaborate on practical challenges—and how that collaboration is changing the way we approach regulatory submissions.

Project Optimus and what you need to know about it 21.07.2026 25мин

Cancer treatments have changed dramatically over the past decade, but have our dose-finding strategies kept pace? In this episode, I speak with Dr. Ayon Mukherjee, who leads statistical innovation in early oncology development at Eli Lilly. Together, we explore Project Optimus, the FDA initiative that is changing how we think about dose optimization in oncology. Instead of simply finding the highest dose patients can tolerate, Project Optimus encourages us to identify the dose that provides the best balance between efficacy, safety, pharmacokinetics, pharmacodynamics, and long-term tolerability. Ayon explains why the traditional maximum tolerated dose approach worked well for chemotherapy but often falls short for targeted therapies and immunotherapies. We also discuss how statisticians can help lead this transformation by designing better dose optimization studies and collaborating more effectively with clinicians, pharmacologists, and regulators.

Unlocking Growth: The Power of Coaching and Mentoring for Statisticians 30.06.2026 35мин

In this insightful interview, Emma May and Alun Bedding explore the nuances of coaching and mentoring, sharing personal stories, frameworks, and practical tips to enhance professional growth. Discover how these powerful tools can transform statisticians' careers and foster leadership development.

Understanding and Mitigating Endpoint Bias in External Control Arms 09.06.2026 28мин

External control arms are becoming increasingly important in drug development, but creating valid comparisons requires more than matching patient populations. In this episode, I speak with Ben Ackerman, Director of Real-World Biostatistics at GSK, about one of the most overlooked challenges in external control arm studies: endpoint bias. We discuss why differences in how outcomes are measured can influence study results, what researchers should consider when designing studies, and how the field is evolving to address these challenges. If you work with real-world evidence, causal inference, or innovative clinical trial designs, this episode offers valuable insights into improving the credibility and transparency of external control arm analyses.

The Future of Statistical Methodology in Drug Development 02.06.2026 31мин

This episode features three leading statistical methodology experts discussing the role, impact, and future of methodology groups in the pharmaceutical industry. They explore organizational structures, skill sets, AI integration, and strategies to accelerate adoption of innovative methods.

Rethinking Programming Validation and Traceability in Clinical Trials 26.05.2026 23мин

In this episode of The Effective Statistician, I speak with Andrew (Andy) York about the evolving world of programming validation, traceability, and quality assurance in clinical trials. Andy has decades of experience in statistical programming, leadership roles across pharma and CROs, and now works with AI-driven solutions focused on improving validation and traceability.

How Applied Improvisation Develops and Reinforces Interpersonal Skills 04.05.2026 33мин

In this episode, Alun Bedding speaks with Richard Zink about how **applied improvisation** can help statisticians become more effective communicators and leaders. They explore how improv techniques—like “yes, and,” active listening, and embracing mistakes—build confidence, strengthen collaboration, and improve the way we explain complex ideas. This conversation shows that developing interpersonal skills doesn’t have to be theoretical or boring—it can be practical, interactive, and even fun. If you want to communicate your ideas more clearly, connect better with stakeholders, and grow beyond technical expertise, this episode is for you.

What does a clinical lead expect from a statistician? 27.04.2026 32мин

Episode Overview In this episode, I speak with Anna Mosikian, a physician by training and Global Clinical Program Lead working at the intersection of clinical development and strategic marketing. Anna brings a powerful perspective on how clinical data translates into real-world value—bridging evidence generation, regulatory expectations, and commercial impact. We dive into what clinical leaders truly expect from statisticians and how statisticians can move from technical contributors to strategic partners. We explore what “good collaboration” really looks like in practice, why understanding the purpose of a study is critical, and how statisticians can elevate their impact through communication, proactiveness, and cross-functional thinking.

Measuring Trust – A Key to Effective Leadership 21.04.2026 27мин

Trust is one of the most fundamental elements of effective leadership—and yet, most organizations don’t measure it properly. In this episode, I speak again with my good friend Alun Bedding about how we can move from talking about trust to actually quantifying and improving it. We explore why trust is essential for collaboration, leadership, and performance, and what happens when it’s missing. We also dive into practical tools like the Leadership Trust Index, how to interpret trust as a lead measure, and how organizations can systematically improve trust over time. If you want to become a more effective leader and create real impact, this episode gives you both the mindset and the tools to do it.

Choosing and Interpreting PROs and COAs – A Guide for Clinical Trial Statisticians 17.04.2026 41мин

In this episode, I sit down with Rachael Lawrance to dive into a topic that has become absolutely central to clinical research: patient-centered outcomes. When I first started as a statistician, I knew these measures existed—but I didn’t really understand how they were developed, analyzed, or used in decision-making. That has changed dramatically over the years. Today, patient-reported outcomes (PROs) and the broader framework of clinical outcome assessments (COAs) play a key role in regulatory approvals, payer decisions, and how we demonstrate treatment value. Rachael brings deep expertise from her work at Adelphi Values and shares how these endpoints are developed, validated, and applied in practice. We also discuss how statisticians can contribute more effectively by understanding the science behind these measures—not just treating them as “just another scale.”

How Statisticians Can Build Trust and Lead with Emotional Intelligence 23.03.2026 39мин

In this episode of The Effective Statistician, Alun Bedding speaks with Emma May about the skills that truly differentiate effective statisticians from great leaders. While technical expertise remains essential, success in today’s environment increasingly depends on the ability to build trust, communicate effectively, and lead with emotional intelligence. Drawing from their joint leadership workshops, Alun and Emma explore how statisticians can develop these capabilities and apply them in real-world settings. They discuss practical approaches to creating psychological safety, shifting from a “telling” to a coaching mindset, and fostering a growth mindset within teams. The conversation highlights why leadership is not about having all the answers—but about enabling others to contribute, grow, and succeed.

The Evolving Role of Generative AI in Pharma 20.01.2026 33мин

Generative AI is moving fast—and in pharma, it’s no longer just a buzzword. In this episode of The Effective Statistician Podcast, I speak with Manuel Cossio about how Generative AI is already being applied in real-world pharma settings, where it’s delivering value today, and what still needs careful consideration in regulated environments. Manuel brings a unique hybrid background, combining molecular biology, genetics, pharma experience, and deep AI engineering expertise. He works at the cutting edge of AI in clinical development, including agentic systems, human-in-the-loop approaches, and large-scale document automation. This conversation goes well beyond theory. We focus on practical use cases, real limitations, and how statisticians, programmers, and data scientists can responsibly use GenAI to become more effective.

Kicking Off 2026: Gratitude and What’s Ahead 06.01.2026 2мин

As we start 2026, I want to take a moment to express my sincere gratitude to everyone who has been part of The Effective Statistician podcast. This episode features my co-host, Alun Bedding, reflecting on the past year and sharing thanks on behalf of both of us. From our listeners who tune in, share episodes, and engage with the content, to our guests who generously share their expertise and real-world experiences — your participation makes this podcast both insightful and practical for statisticians worldwide. I also want to recognize Reine and her production team. So much of the work that brings each episode to life happens behind the scenes, and we are deeply grateful for their professionalism and dedication. We’re excited about what 2026 has in store. I look forward to continuing this journey with all of you and bringing even more valuable conversations to our community.

Why to present better and how as a statistician 01.12.2025 36мин

In this episode, I talk with my long-time friend and frequent guest, Kaspar Rufibach, about a skill that quietly determines how much impact we really have: presenting and communicating our work. We walk through how Kaspar prepares his talks (including why he starts months in advance), how he structures messages so stakeholders actually remember and act on them, and why overcrowded slides are often just a sign that we haven’t done the hard thinking yet. We also get honest about something many statisticians feel but rarely discuss: the fear of public speaking, the frustration of bad meetings, and the “personal brand” you build every time you present—whether you intend to or not. If you’ve ever walked out of a meeting thinking “I don’t think they really understood what I meant,” this episode is for you.

External control arms - how to get to a good one 27.11.2025 26мин

In this episode, I’m joined by Deepa Jahagirdar, Associate Research Principal at Cytel, to explore what it really takes to build a good external control arm (ECA). Deepa brings a fascinating background from social epidemiology, where causal questions often need to be answered without running randomized trials. That experience translates directly into today’s growing need for ECAs, especially when we rely on real-world data to support single-arm trials, extension phases, or situations where randomization simply isn’t possible. Together, we discuss how to choose the right data source, how target trial emulation works in practice, what to do about confounding, and how to judge whether an ECA is truly robust. If you’re working with real-world evidence, complex study designs, or causal inference, this episode will give you clarity and confidence in approaching ECAs the right way.

Top 9: Non-parametric analyses - much more than just the Wilcoxon test! 10.11.2025 40мин

Why this episode made our all-time Top 9: If you’ve ever thought “non-parametric = Wilcoxon/Mann-Whitney and that’s it,” this conversation will happily destroy that myth. Frank shows how rank-based methods unlock rigorous analyses for skewed data, outliers, ordinal endpoints, small samples, composites/estimands—and how to communicate effects without relying on means.

How to communicate results from adaptive studies simple, but still correct 27.10.2025 24мин

Adaptive designs let us learn earlier, stop smarter, and protect patients—but they also make communication tricky. In this episode, Kaspar Rufibach and I dig into what “still correct” looks like when you try to explain results from group-sequential and other adaptive trials to regulators, clinicians, and scientific audiences. We unpack conditional vs. unconditional bias, median-unbiased estimation, stage-wise ordering for p-values, confidence intervals in multi-stage settings, and what to do with secondary endpoints and multiplicity. We also touch on ICHE20 (Adaptive Clinical Trials) and why pre-specification isn’t just a box-tick—it’s what builds trust.

Introduction to adaptive designs and ICH E20 20.10.2025 29мин

In this episode, I’m joined once again by my friend and frequent guest, Kaspar Rufibach, to talk about a topic that’s been around for decades but is gaining fresh attention thanks to the new ICH E20 draft guideline—adaptive designs in confirmatory clinical trials. Kaspar and I discuss why and when we should consider adapting a clinical trial, what kinds of adaptations are statistically valid and meaningful in a regulatory context, and why these designs—despite their efficiency—are still not used as often as they could be. We also dive into the statistical foundations behind adaptive designs, such as p-value combination methods and meta-analytic thinking, and explore how adaptive approaches can help us make faster and smarter decisions in drug development.