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.

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.

This episode is a little different because Alun turns the microphone toward me. After 456 episodes, it feels both strange and exciting to be the “guest” on my own show. Together, we reflect on the journey so far and then dive into a topic close to both our hearts: the human skills that make statisticians and quantitative scientists truly effective. We talk about leadership as helping others accomplish something, how to influence people across functions (not just departments), why being known inside your organization matters, and how presentation skills can make or break your impact. We wrap up with three actions you can start applying right away.

I’m excited to reshare one of our most-played conversations—the one where Norwegian regulator/HTA leader Anja Schiel and I get very practical about when single-arm trials fail decision-makers and what comparative, smarter alternatives look like for regulators, HTA bodies, payers, clinicians, and—most importantly—patients.

As statisticians in pharma, one of the most important professional relationships we can build is with our physician colleagues. When this partnership works well, studies run smoother, decisions are better, and our impact for patients grows. In this all-time Top 7 replay, Benjamin Piske and I talk about what makes this collaboration effective, the challenges you may face, and how to establish yourself as a true partner rather than “just the statistician.”

This is one of our most downloaded episodes ever, and I’m excited to bring it back in this replay. In this conversation, I spoke with Lara Wolfson (MSD) and Anders Gorst-Rasmussen (Novo Nordisk) about EU HTA (European Union Health Technology Assessment): what it is, why it’s coming, and why statisticians like us must pay attention. If you’ve ever wondered whether your approach to safety analysis is leading to misleading conclusions, this episode is a must-listen.

We’re bringing back one of our most downloaded episodes ever – a deep dive into how adverse events should be analyzed properly. This conversation with Jan Beyersmann and Kaspar Rufibach is packed with methodological insights and practical implications for statisticians working in clinical trials. Adverse event (AE) analysis has long been approached differently from efficacy analysis, often using overly simplistic methods that can bias results. In this episode, we discuss why that’s a problem – and how the SAVVY collaboration (Survival analysis for AdVerse events with Varying follow-up times) is pushing the field forward. Together with academia and multiple pharma companies, this collaboration tackled the issue of AE analysis using real randomized trial data, not just simulations. The findings show how common methods can underestimate or overestimate event probabilities and how established statistical methods can be applied more consistently to ensure fair benefit–risk assessments. If you’ve ever wondered whether your approach to safety analysis is leading to misleading conclusions, this episode is a must-listen.

In this special replay of one of our all-time most popular episodes, we dive deep into one of the most debated topics in the pharmaceutical industry: R vs SAS. Together with Thomas Neitmann and my co-host Sam Gardner, we compare these two powerful statistical programming tools from multiple angles — ease of learning, day-to-day usability, community support, visualization capabilities, regulatory acceptance, and more. Whether you are a seasoned SAS programmer, an R enthusiast, or someone deciding which tool to focus on, this conversation will give you valuable insights into where each shines, where they struggle, and how the industry is evolving.

In this special replay episode — the top 3 most downloaded of all time — I’m again joined by Stuart McGuire as we explore The Chimp Paradox by Professor Steve Peters. This book provides a simple yet powerful model for understanding how our brain works — and how it often works against us if we’re not aware of it. Whether in meetings, under pressure, or dealing with self-doubt, understanding your inner “chimp” can help you manage emotions, lead with clarity, and avoid the traps that keep so many statisticians and scientists stuck. This episode remains a favorite because it strikes at the core of how we think, react, and lead — especially in high-stakes scientific and business environments.

This episode ranks as the #2 most downloaded of all time—and for good reason. As data science continues to disrupt and redefine the healthcare and pharmaceutical industries, statisticians everywhere are asking: Where do I fit in? In this insightful conversation, two leaders from Cytel—Yannis Jemiai, Head of Consulting and Software, and Rajat Mukherjee, Head of Data Science—share their personal journeys from traditional statistics into data science, how the field is evolving, and why statisticians are uniquely positioned to lead the future of analytics in life sciences. Whether you're curious, skeptical, or already exploring data science, this episode will inspire and equip you with practical insights.

This episode originally struck a chord with statisticians around the world—and for good reason. Whether you’re just starting with real-world evidence (RWE) or mentoring someone who is, this conversation is packed with practical lessons that will help you navigate the complexities of observational data with more confidence. In this special replay, guest Rachel Tham and I reflect on the real-world analysis mistakes, misconceptions, and growing pains they wish someone had warned them about earlier in their careers. From ambiguous index dates to messy exposure definitions and unexpected data quirks—this episode will save you hours of rework and help you better manage timelines and expectations.

In this special keynote episode, I’m excited to share the recording of Professor Tim Friede’s thought-provoking presentation from The Effective Statistician Conference 2024. Tim, a leading expert in biostatistics and clinical trial design, dives deep into the combination of randomized controlled trials (RCTs) and real-world data (RWD)—especially in the context of rare diseases. Drawing from his work at the University Medical Center Göttingen and numerous European research initiatives, Tim presents a compelling case for integrating RWD to support small or underpowered RCTs using advanced statistical models. He shares real-world examples (including CJD and Alport syndrome), simulation insights, and practical recommendations that can change how we approach evidence generation in low-prevalence populations. What You’ll Learn:

In this keynote episode, Professor Sebastian Schneeweiss from Harvard Medical School shares groundbreaking insights from his extensive research into emulating randomized controlled trials (RCTs) using real-world data (RWD). Recorded live at The Effective Statistician Conference 2024, this talk explores whether non-randomized studies based on electronic health records and claims data can reach conclusions as reliable as those from traditional RCTs. Prof. Schneeweiss, also Chief of the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital, walks us through the RCT DUPLICATE project, a major FDA-funded initiative that evaluated whether regulatory decisions could be replicated through high-quality real-world evidence (RWE). From the successes to the limitations—and everything in between—this episode is packed with lessons for statisticians, regulators, and pharmaceutical leaders interested in the future of data-driven healthcare decisions.

In this episode of The Effective Statistician, Alun Bedding takes the mic to explore one of the most underrated yet transformative tools in any professional's career—networking. With the PSI Conference happening, this episode offers timely insights into how statisticians—introverts and extroverts alike—can use networking to build meaningful professional relationships, accelerate their careers, and find support within the broader community. Alun shares personal anecdotes, including how a casual conversation with Alexander at a past PSI event led to his current guest host role, and outlines a step-by-step mindset and strategy for networking with authenticity and purpose.

In this episode, Alun Bedding welcomes Emma Crawford for a powerful and personal conversation about building inclusive workplace cultures—ones where every individual can thrive. Emma shares her late diagnosis of autism and how it reshaped her experience and expectations of the workplace. Together, they explore the limitations of the traditional “reasonable adjustments” framework and introduce the concept of success enablers—workplace strategies and tools that benefit not just neurodivergent individuals but everyone on the team. The conversation dives deep into the role of leadership, AI tools, flexible work arrangements, and cultural shifts that prioritize accessibility and well-being for all employees. Emma also previews her interactive workshop at the upcoming PSI conference and gives insight into how the session will encourage open discussion, hands-on activities, and actionable takeaways to help leaders and teams foster a more inclusive environment. Whether you’re a people leader, statistician, or advocate for change—this episode will challenge your assumptions and inspire more inclusive practices.

How can oncologists and healthcare professionals keep up with the ever-growing body of research to make the best decisions for patients? In this episode, I speak with Anna Forsythe, a pharmacologist, health economist, and founder of OncoScope, a groundbreaking platform delivering daily updated systematic literature reviews (SLRs) in oncology. Drawing on decades of experience in pharma and health economics, Anna shares how automation and AI are transforming the traditionally tedious SLR process—making up-to-date evidence accessible to clinicians in just a few clicks. Anna’s vision is clear: democratize access to high-quality, current evidence for clinicians—and ultimately improve patient care.

In this episode, I’m joined by Julia Geronimi from Servier and Dr. Pavel Mozgunov from the University of Cambridge to explore a topic that’s absolutely central to advancing precision medicine—predictive biomarkers. We dive into the challenges of identifying predictive vs. prognostic biomarkers, especially in early-phase clinical trials with limited sample sizes. What makes their approach so exciting is that it offers a model-flexible, visually intuitive way to detect predictiveness—even before we talk about dichotomizing biomarkers or setting cutoffs. If you work on clinical trial design, translational science, or biomarker development, this conversation will give you fresh tools—and a lot to think about.

In this special episode, I’m sharing the recording of a webinar I co-hosted with Cytel on March 20, 2025. I was joined by an expert panel of leaders in statistics and clinical development: Yannis Jemiai, Flaminia Chiesa, and Benjamin Piske. Together, we explored how the role of statisticians is rapidly evolving in response to industry changes, data innovations, and AI-driven transformation. This rich discussion dives into what it means to lead as a Clinical Data Scientist today—and why statisticians are uniquely positioned to influence strategy, innovation, and decision-making across the healthcare and pharmaceutical sectors.

In this episode, I’m excited to welcome back Katrin Kupas, a statistician with deep expertise in Health Technology Assessment (HTA) and real world evidence (RWE). We dive into how RWE and the new Joint Clinical Assessment (JCA) process in Europe can work together—and where the challenges lie. As the JCA becomes more central in EU regulatory and reimbursement discussions, knowing how and when to use real world data is critical. Katrin shares practical use cases, methodological guidance, and strategic insights for integrating RWE into early planning.