The world of healthcare continues to change, and it’s important to keep up with the latest advances in technology and research. That’s why I'm excited to talk with Shirley Wang, one of the leaders of RCT Duplicate, a study focused on duplicating randomized clinical trials through real world data. 

She is currently leading the RCT Duplicate as the first author on some key publications related to the initiative. She has been instrumental in helping move the project forward by analyzing data from various sources and developing new methods for collecting information from real-world settings. Her work has helped pave the way for more reliable findings based on real-world evidence—which will ultimately benefit everyone who works in healthcare. 

In this episode, we discussed RCT Duplicate's goals and recommendations for real-world evidence researchers based on findings from the initiative. We also discuss the following points:

Today I'm talking with Rachel Tham, a principal statistician, about a book that has been incredibly impactful in both of our lives—Deep Work. We discuss what deep work is and how it can help statisticians at work. 

Deep work is a concept developed by Cal Newport which encourages people to focus intensely on one task for an extended period of time without any distractions. This type of focused work allows people to produce higher-quality results in less time than if they were trying to multitask or do shallow tasks.

Join us and learn more about deep work concepts and how they can improve your productivity and satisfaction.

Rachel and I discuss the following points:

Why are companies often running single arm studies in development? 
What are the potential drawbacks and why is it not a binary choice between full comparative study and single arm trial?
What are solutions in between to find a balance between feasibility and rigour?

Single arm studies are a popular method for collecting data despite being critiqued for decades. It is a type of research design in which the investigator only observes one group of participants over time. 

This design is often used when sponsors claim it would be unethical to randomise patients into different groups or when comparing two treatments would be too difficult. 

However, there are several drawbacks associated with single arm studies. First of all, bias can easily creep into the results.

Anja Schiel - the most recognised regulatory statistician in Europe -  and I discuss the potential drawbacks of running single arm studies, as well as ways to balance scientific rigour with feasibility.

Tune in while Anja and I give some of the great advice we have come up with. We also discuss the following points:

Reproducible research is a key part of research in the pharma industry.

It allows for transparency, understanding, and accuracy in the research process. But how can you make your research more reproducible?

Today, I talk with Heidi Seibold who has dedicated her career to helping researchers become more reproducible.

Let's take a look at 3 steps that she recommended for making your research more reproducible:

Are you a statistician working in the pharmaceutical industry and never got in touch with economic modelling and network meta-analyses? Then you should listen to this episode!

The EU HTA will not only affect all statisticians in the pharmaceutical industry with respect to skill sets and collaboration (we talked about that in podcast #3), but will also have impact on the economic modelling that is needed for the reimbursement and pricing decisions in many European countries. Understanding the influence of the joint clinical assessment on the economic modelling, the relationship between estimands and PICOs as well as the pre-specification of statistical analyses and their use in economic modelling is becoming much more important for statisticians in the near future.

In this episode, we will talk about role of economic modelling in the HTA process, and the influence of the EU HTA and the corresponding statistical analyses on that process.

All statisticians in the Pharmaceutical Industry will be impacted by the new EU HTA regulation. Activities around HTA submissions will happen earlier than currently, in parallel to the regulatory approval process for marketing authorization. There will be an increased scope of evidence for the joint clinical assessment to fulfill the needs of all EU member states, and so there will be a large package of statistical analyses that need to be provided in addition to the submission to the regulatory bodies.

This will redefine how you, as a statistician, work, and with whom you need to collaborate. Both HTA and clinical development statisticians will need to join forces to define the value story for the complete lifecycle of the drug. HTA specific analyses will need to be planned in parallel with clinical development.

In this episode, we will discuss the future skill sets that statisticians in the pharmaceutical industry need to adopt with the new EU HTA regulation being applied in 2025 already.

If you’re a statistician working in a regulatory setting, you’re probably familiar with estimands as a way to frame the clinical question of interest. But what’s the role of estimands beyond regulatory approval, in a Health Technology Assessment setting? That question is especially important these days where the framework for pan-European HTA is taking shape. In this episode, we’ll touch on some HTA body views around estimands, and reflect on how current draft guidelines for EU HTA do and don’t address estimands.

Are you a statistician, data scientist, or healthcare specialist looking for the perfect conference to attend?

The Effective Statistician Conference 2023 is an exciting opportunity for statisticians, health care specialists, and data scientists to come together and learn from industry experts, exchange ideas, share breakthrough advancements in statistics, collaborate with peers, and stay ahead of the latest trends. This virtual event will happen on the 25th of April and the registration is FREE.

Through comprehensive talks delivered by influential and seasoned professional speakers across many disciplines – statistics across the R&D phases, process optimization, data visualisation, leadership, simulation, ... – attendees can make meaningful connections that help them become more effective problem-solvers in the ever-evolving digital age. This highly anticipated event is sure to leave everyone inspired and well-equipped with newfound knowledge ready to apply to their practices.

Let's revolutionize how statistics can drive innovation!

In this episode, I'll be discussing these points in detail:

As a statistician, have you ever wondered—why are statistical analyses for HTA dossiers differ from those in regulatory dossiers? Aren’t they both just benefit-risk assessments? In this podcast, we review some of the history and background of how HTA and regulatory decision making have common sources of information, but different utility functions for how they use that information. Why have we had a common European regulatory framework, but not a common HTA framework—until the near future. And what is the EU HTA Regulation? Why has it been established, what does it hope to accomplish…..and why does this matter to statisticians working in the pharmaceutical industry? This podcast is the first of a series of 4 exploring the role of statisticians and statistics in HTA analyses, and how the new European HTA Regulation that will first start being applied to medicinal products in 2025, will impact statisticians working with clinical (and non-clinical!) data to support and evaluate HTA decision making. Learn how you can get more involved in shaping the future of EU HTA as a statistician at the local and regional level.