How do we find the right dose in immune-oncology trials?

Is the traditional “maximum tolerated dose” approach still enough, or should we also focus on efficacy?

In this episode of The Effective Statistician, I talk with Teppo Huttunen, a seasoned statistician and Chief Executive Officer of EstiMates Oy. We uncover the shortcomings of the conventional three-plus-three design and explain how the Bayesian Optimal Interval (BOIN) design gives us more flexibility and better insights. Teppo shares practical tips on dose optimization and highlights the critical role statisticians play in shaping smarter, evidence-based decisions for phase two trials.

If you want to learn how we can balance safety, efficacy, and practical challenges in oncology studies, this episode is for you!

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Welcome to this episode of The Effective Statistician! Today, I explore an exciting and rapidly growing field: digital health interventions.

Have you ever wondered how to define engagement with these tools?

Why does measuring engagement matter so much for their success?

And how can statisticians solve the unique challenges that come with this digital space?

I speak with Jack Elkes, a PhD researcher focused on digital health, to answer these questions. Together, we tackle the complexities of these interventions, their use in areas like mental health, and how tools like cluster analysis help make sense of multidimensional data. With over 10,000 mental health apps already on the App Store, this field expands rapidly, creating opportunities and challenges.

If you want to know how engagement in digital health connects to marketing strategies or how these tools reshape decentralized trials, you’ll find plenty of insights here. Let’s dive in!

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Have you ever thought about how clinical trials affect the environment?

I hadn’t, until I spoke with Annie Wright, a first-year PhD student at Imperial College who is passionate about greener research. In this episode, we uncover how clinical trials contribute to climate change, from travel emissions to operational inefficiencies. We dive into practical actions statisticians and researchers can take to reduce the carbon footprint of trials, like adopting decentralized approaches and streamlining study designs.

Join us as we explore how to transform clinical research into a more sustainable practice while still delivering valuable scientific outcomes.

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Have you faced the challenge of dealing with non-proportional hazards in survival analysis?

In this episode, I team up with Kaspar Rufibach, a statistical methodology expert, to break down what proportional hazards mean, why the assumption often fails, and how you can tackle these situations effectively.

We explain key concepts like hazard functions, discuss practical ways to analyze and visualize survival data, and share strategies for designing better clinical trials.

Whether you’re working on your first survival analysis or refining your approach, this episode will equip you with the tools to address non-proportional hazards confidently.

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