This is an extraordinary episode that takes us deep into the world of modern pharmaceutical research.

Today, we are embarking on a captivating journey guided by the insightful dialogue between me and Elena Polverejan.

Throughout this episode, we uncover the incredible potential of Estimands Framework, a revolutionary concept born from the collaborative efforts of brilliant minds dedicated to transforming clinical trials.

Join us as we delve into the origins of Estimands, discover its practical applications in the complex realm of depression studies, and witness the meticulous process of creating a practical guide that empowers research teams worldwide.

This conversation not only sheds light on the complexities of pharmaceutical research, but also reveals a blueprint for progress, illuminating a path towards more accurate, efficient, and impactful clinical trials.

So, listen now and get ready for an enlightening exploration into the future of pharmaceutical innovation while we discuss also about the following points:

I'm thrilled to dive into a topic that has been untouched in the past 300 episodes - crossover studies. It's a classical design that offers unique advantages, yet it's often overlooked.

Joining me today is Markus Savli, a biostatistician with a diverse background in biomedical engineering, mathematics, and epidemiology. Together, we'll explore the intricacies of crossover studies and their applications in scientific research.

.A crossover study is a longitudinal study where subjects receive multiple treatments in a sequence. This design allows subjects to serve as their own controls, enhancing the ability to address confounding factors. Crossover studies are particularly valuable in scenarios where treatments need to be compared, and their effects measured over multiple periods.

Listen to this episode now while we walk through the following key concepts:

In the intricate world of statistics organizations, a common challenge often arises: how to balance increasing cost pressures while maintaining the quality and relevance of the produced tables. In this episode, I dive into this recurring scene, shedding light on the art of negotiation on the numbers of tables.

I also talk about the following important points:

In today's episode, I discuss the crucial topic of risk management in clinical trials with guest Jess Thompson. Jess, the founder of the Association of Clinical Research Project Managers, shares her extensive experience in the field, emphasizing the importance of proactive risk identification and collaborative communication within project teams.

The conversation delves into practical strategies for risk assessment, impact scoring, and contingency planning, highlighting the significance of involving all team members, including statisticians, in the risk management process.

We talk more about the following key points:

In this episode, I interview Katharina Schueller, a statistician and entrepreneur, to discuss the importance of ethical guidelines for statisticians. Katharina shares her insights on the ethical aspects of statistics, the responsibilities of statisticians, and the relevance of the Declaration of Ethics by the International Statistics Institute (ISI). We explore various values, examples, and practical applications related to ethical statistical practices.

Here are some more points we discuss:

The modern working environment is defined by endless to-do lists, tight deadlines, and the expectation to do more with less. As employees struggle to manage the job responsibilities of 2 or 3 people, exhaustion happens first. Long working hours, with little to no downtime, lead to mental and physical fatigue. Working like this is harmful and not sustainable, but many of us keep going because of the fear of judgment, rejection, or missing out on a promotion. 

In this episode, I explore the steps that employees can take to prevent burnout and improve their overall experience at work.

Welcome to the third and last part of Moving from SAS to R where Thomas joined us again to talk about transitioning from SAS to R.

We also discuss the new SAS to R course of The Effective Statistician and you’ll learn, if this is the right course for you.

We provide a couple of learnings from the course for you to get an impression of what we cover in the course.

Click here to get to the course overview!

We also discuss the following points:

This episode is the second part of Moving from SAS to R with Thomas.

We also discuss the new SAS to R course of The Effective Statistician and you’ll learn, if this is the right course for you.

We provide a couple of learnings from the course for you to get an impression of what we cover in the course.

Click here to get to the course overview!
https://theeffectivestatisticianleadershipprogram.teachable.com/p/open-source-programming

We also discuss the following points:

The use of R in the pharmaceutical and healthcare industry has been increasing over the years, with larger companies like Roche adopting it as their primary statistical software. Others like GSK, NovoNordisk, and Merck make heavy investments into it. 

In this episode, Thomas Neitmann discusses various lessons from his career within pharma and the role R played in it. He provides insights into how to start with R and what are key differences to SAS.

We also discuss the new SAS to R course of The Effective Statistician and you'll learn, if this is the right course for you.

We provide a couple of learnings from the course for you to get an impression of what we cover in the course.

Click here to get to the course overview!

We also discuss the following points:

The healthcare industry is constantly developing, and with it come new regulations and guidelines that businesses must adhere to. One regulation that has recently been set in Germany is the 15% threshold for relevant improvement for some endpoints used in clinical trials. Many have critiqued this threshold. It's important for all statisticians (not only for the market access experts) to understand what it is and how it can affect drug approval. In this episode, we'll dive deep into the 15% threshold and why it's essential for statisticians beyond the market access experts to be knowledgeable about it.

We specifically discuss the following important points: