Daily updated systematic literature reviews - the future of oncology
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.
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22:57
A novel approach for finding predictive biomarkers
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.
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35:39
A Webinar Recording: Redefining the Role of Statisticians in a World of Real-World Data and AI
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.
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51:48
RWE and JCA - how do they go together
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.
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20:21
Why and how you can promote more students become statisticians
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.
Sobre The Effective Statistician - in association with PSI
The podcast from statisticians for statisticians to have a bigger impact at work. This podcast is set up in association with PSI - Promoting Statistical Insight. This podcast helps you to grow your leadership skills, learn about ongoing discussions in the scientific community, build you knowledge about the health sector and be more efficient at work. This podcast helps statisticians at all levels with and without management experience. It is targeted towards the health, but lots of topics will be important for the wider data scientists community.