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.

Group sequential trials, interim analyses, final analyses, updated analyses… what do these terms actually mean, and why is there so much confusion? In this technical yet highly practical episode, I speak with Kaspar Rufibach, Principal Biostatistician at Roche, to unpack some of the most commonly misunderstood terminology and concepts in clinical trial design and analysis. If you've ever questioned what really qualifies as an "interim analysis" or struggled to explain why a “final analysis” isn’t always the last word, this conversation is for you.

In this episode, I had the pleasure of speaking with Prof. Holger Fröhlich, who leads the AI and Data Science Group at the Fraunhofer Institute and is an honorary professor at the University of Bonn. We explored one of the hottest topics in healthcare data science right now: synthetic data. Holger and I discussed how synthetic data is generated using AI, what role digital twins could play in the future of clinical trials, and how these innovations could fundamentally reshape how we design and conduct research. We dove into the Cynthia Project, which is part of the Innovative Health Initiative (IHI) – the largest public-private partnership for health research in Europe.

In this episode, I’m diving into a topic that’s very personal to me—working in an English-speaking environment as a non-native speaker. If you’ve ever felt unsure about your English skills in meetings, emails, or presentations, you’re not alone. I’ve been there myself, and I want to share what’s helped me grow more confident and effective over the years. I’ll walk you through practical strategies that go beyond grammar—things that have really made a difference for me in both speaking and writing, and most importantly, in getting my message across clearly.

In this episode, I’m once again joined by Daniel Sabanés Bové for a deep dive into one of the most impactful tools for statisticians working with data visualization—R-Shiny. We explore how interactive data visualizations can help you iterate faster, collaborate better across functions, and focus more on the actual scientific questions rather than just coding. Daniel shares some excellent examples from clinical trials and gives practical tips on how to avoid common pitfalls when building Shiny apps. Whether you're designing your first app or maintaining a more complex one, you'll find plenty of value in this conversation—from best practices around UI/UX design to strategies for modular development and testing.

In this episode, I’m sharing three personal stories where soft skills—or better yet, human skills—made a huge difference in my work as a statistician. Whether it was building trust to access critical data, presenting results in a way that truly resonated, or negotiating a fair contract, these experiences reminded me how essential these skills are alongside our technical expertise.

In this episode, I’m joined once again by Daniel Sabanés Bové to talk all about R packages—why they’re so useful, when to create one, and how to do it effectively. Whether you’re just starting out with writing reusable functions or thinking about building a more robust and reusable R package, you’ll find plenty of hands-on advice in our discussion. Daniel shares his experiences from working at Roche, Google, and now through his consultancy, Arconis. We dive into everything from writing clean and consistent code, to testing, documenting, and even promoting your package in the open-source world. What You’ll Learn in This Episode:

In this episode, I welcome back Necdet Gunsoy, who’s now in a new role as the founder of EviMed, a boutique consultancy specializing in health economics, outcomes research, real-world evidence, and market access. We dive into the often tense relationship between statisticians and market access professionals, exploring why these functions struggle to collaborate and, more importantly, how we can work together more effectively.

In this episode of The Effective Statistician podcast, I dive into the art of persuasion. As statisticians and data scientists, we often rely on logic and data, but true influence requires more than just being right. Drawing from ancient Greek philosophy, I explore the three pillars of persuasion—ethos (credibility), logos (logic), and pathos (emotion)—and share practical strategies to help you effectively convince others. Whether you are presenting new methodologies, influencing key stakeholders, or advocating for change, this episode will equip you with essential communication skills to make a lasting impact.

In this episode of The Effective Statistician, I sit down with Kaspar Rufibach to tackle a topic that affects statisticians every day—how to interpret p-values, confidence intervals, and statistical hypotheses. We explore the differences between Fisher’s and Neyman-Pearson’s approaches, clear up common misconceptions, and discuss how misinterpreting statistical significance can lead to flawed conclusions. Using real-world examples from clinical trials and drug development, we highlight best practices for communicating statistical results effectively. Whether you're working with clinicians or business stakeholders, this episode will help you gain clarity on these fundamental statistical concepts and use them correctly in your daily work.

In this episode of The Effective Statistician, I dive into a crucial skill—building influence within a clinical trial team. As statisticians, we often need to negotiate timelines, advocate for better analysis methods, and ensure clear communication across teams. The stronger our influence, the more impact we can have on study outcomes and, ultimately, patients. I break down the key pillars of trust—care, character, and competence—and share practical strategies to help you collaborate effectively, align team priorities, and proactively tackle challenges. Tune in and start building your influence today!

I know firsthand how challenging it can be to manage a heavy workload while maintaining mental well-being. In this episode of The Effective Statistician, I talk with Peter Wehmeier about the five key dimensions of self-management—building strong relationships, setting priorities, making decisions, and taking action. We share practical strategies to reduce stress, strengthen resilience, and take control of both work and life. With insights from Peter’s upcoming workshops, this conversation offers valuable tools to help you stay balanced and productive. Tune in to learn how to take charge of your future!

Welcome to another episode of The Effective Statistician! Today, I sit down with Darko Medin to explore how artificial intelligence is transforming biostatistics. Darko works as a biostatistician for companies worldwide and builds digital solutions that push AI’s boundaries. We dive into Bio AI Works, the platform he’s developing to improve AI reliability and eliminate issues like hallucinations in large language models. Darko explains how AI can enhance statistical accuracy, uncover hidden data patterns, and accelerate breakthroughs in oncology and precision medicine. If you want to understand how AI can revolutionize biostatistics while maintaining scientific rigor, this episode is for you. Let’s get started!

In this episode of The Effective Statistician, I explore Slow Productivity by Cal Newport—a book that challenges how we think about work and efficiency. I welcome Alun Bedding and Steve Mallett to discuss how statisticians can apply Newport’s principles: doing fewer things, working at a natural pace, and obsessing over quality. We share our experiences with managing workloads, cutting unnecessary meetings, and focusing on meaningful work. If you want to break free from the busyness trap and boost your impact, this episode is for you.