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What is a secondary paper? What is its typical content? Where is the content coming from? A secondary paper is a paper you do once you are done with your primary paper. I've been working on this for a long time and always have fun doing it. Together with Benjamin, we discuss the following points:

Feeling comfortable does not lead to growth. But why do most people stay in their comfort zone? Are your own expectations holding you back? In this episode, I am talking about the reasons why people stay in their comfort zones and always choose the “safe side”. And why choosing this hinders you from your personal and career growth.

I am really passionate about leadership and Claude Petit is also passionate about building leaders and being an effective leader. Together, we will share with you how to become a statistical leader and how to build such an organization. So stay tuned!

What is a pharmacometrician? What does the training of a pharmacometrician look like? In my career, my experience of working with pharmacometricians was very limited because I spent most of my time working more on the later phases; and the contact with people in that space of the industry is not that big, that's why I found this episode really helpful. If you don't have a clue what they do then stay tuned for this episode.

What can go wrong with network meta-analyses? You often have multiple endpoints but these are not collected consistently across all the studies included in the NMA. How do you deal with this? Even with the same variables assessed over studies, they might be collected at different time points. This often has an effect on both efficacy and safety results. What do you do? Your placebo treatment might change over time and consequently your placebo response. Often placebo plays a crucial part in your network, but can you really pool all your placebo arms? The patient population differs between studies and hence between treatments. How do you control this bias? The pool of relevant treatments differs across countries when using network meta-analyses for HTA submissions. Should you adapt your NMA for each country's submission? You’re not submitting all your HTA dossiers at once and thus the literature search needs to be updated repeatedly hence you input data into the NMA. How big are the differences and how long will it take to update everything (and what will it cost?)?

In today's episode, I am the interviewee, and Jenny is the one asking the questions. We are talking about how training in launch and commercialization can be a super weapon, what its role is, and how can this be developed and administered for non-statisticians. We also talk about the following interesting points:

The world has changed, and it will not turn back to what is used to be before the pandemic. This comes on top of other trends, like the increased use of data across all aspects of data. The hunger for talent in the data science space has dramatically increased, and it is not only coming from the Apples, Googles, and Amazons. Other trends are the increase in prices, the shifts in motivations of employees, and the debate about what really makes people join and stay at companies.

I first became aware of these sources for real-world evidence some years ago, and I tried to get an expert on this topic so often, but unfortunately no one would speak with me. Then finally someone agreed when they found out what country my research was being conducted in-the Scandinavian Union! You might be wondering why we need data from such a unique place as Scandinavia? Stay tuned because you'll find out soon enough… This region provides us statisticians everything we could hope: perfect measurements plus high-quality counts.

Is a board of directors essential for everyone? Is it necessary for it to come from within your company? This episode is all about career advise. Together with Heather, we talk about having your personal board of directors and how could this concept help you have a career advancement overtime.

We all need to present frequently and the more you progress with your career the more important the presentations become. Messing these presentations up - especially in front of those responsible for your next promotion - will lead to bad career outcomes.

What are biomarkers, and why is this essential?

Today’s episode is an extract from my interview with Jenn Fenwick, who's also a podcaster like me and we talk about my career and leadership. This is a fun chat where we talk about navigating fear, opening ourselves up to vulnerability and making courageous decisions… oh and Beyonce gets a mention too!

What is extrapolation? How can we use extrapolation in paedriatics? What are the main challenges? Paedriatic research always comes with challenges and understanding paedriatic submission is very important. There's always a lack of treatment in this area. In this episode, you'll understand what you can do to get evidence through extrapolation for the children population.

What are the benefits of including external data in the design and analysis of clinical studies? How does the meta-analytic predictive model (MAP) work? I know you've had this dilemma of either having had the difficulty in collecting data or having too much available and yet irrelevant data while trying to conduct a clinical trial. When is it appropriate to use historical data and when is it appropriate to enroll new patients to collect new data? Today, Gaëlle and I talked about the main objective of using historical data in clinical trials.

Why are we raving about this conference? Why is this the best conference I have been attending to? What are the other activities beside the conference itself? This is a special episode while Benjamin and I talk about the upcoming PSI conference and what you can expect from it. This will be a face to face conference in Gothenburg, Sweden!

The FDA is developing a series of four methodological patient-focused drug development (PFDD) guidance documents to address, in a stepwise manner, how stakeholders can collect and submit patient experience data and other relevant information from patients and caregivers for medical product development and regulatory decision making. In today's episode, we discuss the process with the FDA publishing a timeline of planned public workshops, draft guidance documents and final guidance documents for 4 documents, originally planned to finish in end 2021 and its objective to explore the factors that need to be considered when developing COA-based endpoints.

What is a DIGA? Why is Germany so important for DIGAs? Nowadays, there are a couple of available apps being used in several countries that collect user information, such as heart rate combined with algorithms that calculate certain health risks that the user may be vulnerable to. What differentiates these apps from the apps listed in the DIGA registry? In today's episode, Dr. Stefan Walzer and I discussed the goal of the Digital Health Application.

Why do companies want to develop new patient-reported outcomes? How does the process start when we want to develop a new questionnaire? What are the key areas to look into for understanding the quality of a PRO? What guidelines exist for developing new PROs? In today's episode, Antoine and I answer these questions and more. E.g. we talk about the importance of calibrating the relevance of the existing items in the questionnaire and developing new ones in order to reach more accurate measurements resulting in good PROs.

What is medical affairs? Launch and Lifecycle? How has this area evolved over the last 2 decades? What is the current state across the industry in terms of the role of statistics in this space?

When there is one topic, which is really hot, it's causal inference. I've got in contact with it about 20 years ago when analysing observational studies and when nobody working on clinical trials would consider it. But now - after the introduction of the estimands framework - this becomes part of every statisticians toolkit. Today, we have one of the world leading experts in this field as a guest - Miguel Hernan. I'm talking with him about: How can this help generate and analyze data to identify better strategies for the treatment and prevention of both infectious and noninfectious diseases?