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.

As someone who found my way into statistics late—only halfway through university—I often wonder: what if more young people knew about this path earlier?

In this episode, I sit down with two wonderful guests and PSI volunteers, Emma Crawford and Alex Spiers, to explore exactly that: how we, as statisticians and scientists, can inspire the next generation.

We talk about the why behind investing in STEM outreach, share personal stories, and get into the practical steps you can take—whether you want to volunteer at a school, present virtually, or simply start a conversation with a student.

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: