The Effective Statistician - in association with PSI

Interview with Miguel Pereira What can statisticians and data scientists learn by exploring the early development research questions? Are there any unique design challenges that they should be aware of? How can Bayesian approaches offer new insights that traditional methods cannot provide? What strategies should data scientists employ in order to successfully navigate the complexities of these new approaches? What knowledge gaps exist regarding the implementation of these new analytical techniques, and how can statisticians and data scientists bridge them in order to maximize their effectiveness? These are all important questions for statistical and data science practitioners, and exploring them further could reveal opportunities for novel ways to approach problems in an increasingly complex field. So, share this link with your colleagues!

Discussion with Alexander We also discuss the following points: How does data visualization require consideration of the needs of an audience? What elements we should take into account when designing data visualizations? Why are standard data visualizations often difficult to create? Why do senior management teams not invest time in understanding the importance of visualizations? How can workshops help senior management better understand data visualizations? What percentage of data visualizations typically has the most impact? How should we allocate resources to ensure maximum impact of data visualizations? Listen to this episode and share this with your friends and colleagues!

Discussion with Alexander and Benjamin We also talk about alternative approaches and some rare cases, where single arm studies might be helpful.

Interview with Shirley Wang The story behind RCT DUPLICATE and how it was developed to facilitate research The approaches taken in conducting these studies. Predictions on how future advancements will affect the development of new therapies. Listen to this episode and share this with your friends and colleagues!

Interview with Rachel Tham What is deep work When have you stepped over this concept of deep work? Which aspects of deep work have helped you most? Were there any guidances in deep work, that you found difficult to follow? How do you use deep work concepts currently in your day-to-day work? References: Deep Work Atomic Habits

Interview with Anja Schiel Are you seeing a return to single arm studies from an HTA perspective? What potential drawbacks should be considered when opting for non-randomized comparative trials instead of randomized control ones? If a full RCT isn't feasible, what other viable approaches are available as substitutes? How can sponsors best communicate their research with HTAs on these alternative solutions and explain the value they present in comparison to an RTC design study? Listen to this episode and share them with your friends and colleagues!

Interview with Heidi Seibold Document Everything Create Reusable Code Share Results with Others Making sure that your research is reproducible is important in the pharma industry because it allows others to understand what you have done and how you arrived at those conclusions. By following these three steps—documenting everything, creating reusable code, and sharing results—you will be able to make sure that your research is reproducible for anyone who needs access to it now or in the future! Resource: Transparimed Share this episode with your friends and colleagues who can learn from this!

Katrin Kupas and Jen Min-Hua discuss the role of health economics in EU HTA, the influence of joint clinical assessment on economic modeling, the need for pre-specification of statistical analyses, and the importance of statisticians having a broader perspective in health economics.

Interview with Katrin Kupas and Dr. Arthur Allignol 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.