The Effective Statistician - in association with PSI

A conversation with Alexander Schacht and Alun Bedding Why You Should Listen: ✔ Hear my personal reflections on 456 episodes and the evolution of this podcast. ✔ Learn a simple, values-based view of leadership that applies no matter your level. ✔ Discover how to influence people—not departments—and build trust. ✔ See why contextual teaching beats generic “Stats 101” courses. ✔ Walk away with three immediate actions: decide to lead, listen deeply, and invest in your presentation skills. Episode Highlights: 00:00 – Why Alun is interviewing me for Episode 456 01:57 – What counts as an “episode” and why this milestone matters 03:03 – From estimands to blurred lines across stats/data science 06:10 – My view of leadership: helping others accomplish something 08:08 – Values, purpose, and the “win–win” principle 10:09 – Goal-driven meetings and tying them to vision and values 12:44 – Why you can’t influence a department—you influence people 15:47 – Trust = character × competence × care (as others perceive it) 17:16 – Being known: why personal and departmental branding matters 19:00 – How targeted training builds credibility and influence 23:00 – Presentation skills as a multiplier for all other communication 28:34 – Listening: the most underrated leadership skill 33:00 – My three practical actions to apply this week 35:30 – Closing thoughts and invitation to connect Resources and Links: Stephen R. Covey — The 7 Habits of Highly Effective People Michael Hyatt — leadership and values-driven success John Blakey — trust model (ability, integrity, benevolence) Oscar Trimboli — How to Listen Toastmasters — practice for public speaking How to Be an Artist (book on learning and creativity) 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Anja Schiel, a vice chair at UNETA 21 and expert at the Norwegian Medicines Agency, delves into the complexities of single-arm studies in drug approval. She discusses the critical need for robust comparisons in evidence evaluation and the limitations of single-arm designs. Anja also highlights the importance of concurrent controls and shares practical strategies for choosing effective comparators. With insights into adaptive trial designs, she sheds light on statistical communication between regulators and HTA bodies, emphasizing the need for clear evidence strategies.

Discussion with Benjamin Piske and Alexander Schacht Why You Should Listen: Working with physicians isn’t always easy. Different mindsets, expectations, and communication styles can get in the way. In this episode, you’ll hear how to: ✔ Build trust and respect with physicians in pharma ✔ Communicate effectively across disciplines ✔ Know when to support, when to push back, and how to be seen as a partner Episode Highlights: [01:28] Introducing the topic of working with physicians in pharma [02:27] Seeing physicians as colleagues, not customers [04:53] Learning to speak each other’s language [06:26] Cultural challenges for physicians moving from hospitals into pharma [10:59] Approaching discussions with a partnership mindset [12:59] Why involving statisticians early leads to smoother studies [15:18] Strategies for handling disagreements constructively [19:08] The p-value debate and knowing when to push back [24:55] Explaining outputs so physicians (and beyond) can understand [25:26] The idea of having a physician mentor Links: 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Interview with Lara Wolfson and Anders Gorst-Rasmussen Why You Should Listen: ✔ EU HTA is becoming reality: Joint Clinical Assessments begin soon with oncology/ATMPs and will expand to all medicines over the next years. ✔ Statisticians are central: Re-analyses, indirect comparisons, RWE, and quality-of-life analyses will be required—often beyond what regulatory trials were designed for. ✔ Timelines are tight: From EMA Day 120 scoping to dossier deadlines and final JCAs just 30 days post-marketing authorization. ✔ Transparency and resources matter: Joint assessments will be public, and both companies and agencies face capacity and clarity challenges. ✔ You can prepare now: Incorporate HTA needs into trial design, analysis planning, and cross-functional collaborations. Episode Highlights: 00:00 – 02:30 | I introduce the episode and explain why EU HTA is such a critical topic 02:30 – 05:30 | Lara and Anders introduce themselves and their HTA work at MSD and Novo Nordisk 05:30 – 10:45 | Regulatory vs. HTA: safe & effective vs. how good, for whom, and at what cost 10:45 – 18:30 | Europe’s patchwork: national differences in comparators, standards of care, and access 18:30 – 23:45 | The EU regulation: joint clinical assessments, economic modeling, and what’s changing 23:45 – 32:30 | What it means for us as statisticians: re-analyses, ITCs/NMAs, RWE, QoL, and capacity issues 32:30 – 36:00 | Why “transparency” can’t just be 50,000-page PDFs—clear, reproducible evidence matters 36:00 – 45:00 | The PSI HTA SIG’s role, current activities, and how you can get involved 45:00 – end | Our final takeaways and a call for statisticians to engage now Links: 🔗 Join the PSI HTA Special Interest Group and watch for their newsletter and training. 🔗 Review EUnetHTA 21 methodological drafts—they are shaping the future of JCAs. 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician. Glossary: HTA – Health Technology Assessment EU HTA / JCA – Joint Clinical Assessment forming the evidence base for national HTA decisions EMA / CHMP – European Medicines Agency / Committee for Medicinal Products for Human Use RWE – Real-World Evidence; NMA/ITC – Network/Indirect Treatment Comparison QoL/HRQoL – (Health-Related) Quality of Life measures PSI HTA SIG – PSI Special Interest Group on HTA EFPIA – European Federation of Pharmaceutical Industries and Associations

Kaspar Rufibach, an expert in survival analysis and member of the SAVVY collaboration, and Jan Beyersmann, a professor of biostatistics at Ulm University, discuss the complexities of analyzing adverse events in clinical trials. They highlight how varying follow-up times can bias results and advocate for using the Aalen–Johansen estimator as a standard practice. The conversation emphasizes the successful collaboration between pharma and academia, revealing how real-world data can change the perception of treatment risks and enhance benefit-risk evaluations.

Interview with Sam Gardner & Thomas Neitmann What You’ll Learn: ✔ How Thomas and Sam were first introduced to SAS and R — and how their early experiences shaped their preferences. ✔ Key differences in learning curves and the resources available for beginners. ✔ How each tool fares in day-to-day work and long-term maintainability. ✔ Strengths and weaknesses of SAS and R communities — and the events, forums, and support structures that keep them thriving. ✔ The impact of cost, licensing, and open-source vs proprietary models on adoption. ✔ How both tools handle data visualization and producing publication-quality graphics. ✔ Regulatory acceptance: How far R has come in being used for submissions to agencies like the FDA — and what’s still needed for broader acceptance. ✔ Why your choice of tool might also depend on generational trends and the skillsets of new talent entering the field. Why You Should Listen: This isn’t just a technical comparison — it’s a candid, practical discussion based on real-world pharmaceutical research experience. You’ll hear about cultural differences between the SAS and R worlds, the business factors that influence adoption, and the ways companies are moving toward hybrid environments where both can thrive. If you’re making decisions about tools for your team or career, this episode will help you navigate the trade-offs with eyes wide open. Links: 🔗 Thomas' Adventure Blog 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Interview with Stuart McGuire What You’ll Learn: ✔ How to recognize when your “chimp” is in control — and what to do about it ✔ The difference between emotional, rational, and programmed brain responses ✔ How to manage anxiety and fear in high-stakes situations like meetings and presentations ✔ Why we often overwork out of tribal guilt — and how to break that cycle ✔ How false beliefs can be reprogrammed — just like changing default settings in a computer ✔ Why rest, reflection, and celebration are essential for performance Why You Should Listen: Do you ever freeze in meetings, hold back from sharing your opinion, or overwork out of guilt or fear of letting others down? You’re not alone — and there’s a reason why. This episode will help you: Understand your emotional triggers Reframe your reactions in high-pressure situations Build better habits for communication, leadership, and resilience And most importantly, take back control of your mindset Whether you’re presenting to leadership, leading a project, or just navigating stress — The Chimp Paradox can equip you with the tools to respond more intentionally and perform at your best.

Interview with Yannis Jemiai & Rajat Mukherjee What You’ll Learn: ✔ How two leading statisticians transitioned into data science ✔ The key differences (and overlaps) between data science, statistics, big data, and machine learning ✔ Why data science is more than hype—and why statisticians are needed more than ever ✔ The role of visualization and statistical learning in interpreting high-dimensional biomedical data ✔ Real-world applications of data science in biomarker discovery, precision medicine, and pharmacovigilance ✔ What makes data science in pharma different from tech giants like Google or Amazon ✔ Tips for statisticians who want to get started in data science Why You Should Listen: If you're a statistician wondering whether data science is your next career step—or simply curious about how the two fields intersect—this episode offers an honest, expert-led exploration. Yannis and Rajat pull back the curtain on what data science really involves, how it's transforming pharma and healthcare, and what skills and mindset statisticians can bring to this evolving space. Links: 🔗 Explore Cytel’s data science insights and case studies 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Interview with Rachel Tham What You’ll Learn: ✔ Why “index date” is more complicated than it sounds ✔ Common mistakes around exposure definitions ✔ The importance of understanding how RWE data is generated ✔ What programmers should know about timing, variables, and algorithms ✔ Why project management in RWE must be iterative and stakeholder-driven ✔ Key terminology pitfalls that can trip up even experienced professionals ✔ How data issues like duplicates, implausible values, and partial dates impact analyses ✔ Best practices for communication, timelines, and managing expectations in RWE projects Why You Should Listen: If you're working in real-world evidence or thinking of transitioning from clinical trials, this episode is packed with practical advice to help you avoid common mistakes and set your projects up for success. Rachel shares from her own hands-on experience—starting from data management and programming to leading statistical analyses in RWE. Alexander and Rachel also highlight real-world data quirks that no textbook prepares you for, making this episode an essential resource for statisticians, data scientists, and healthcare researchers alike. Links: 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Manjari Narayan, a speaker at the Effective Statistician Conference 2024, dives into the transformative impact of AI on biotechnology and drug development. She discusses the untapped opportunities for statisticians to innovate before clinical trials and the challenges posed by AI-guided experiments. Manjari emphasizes the importance of experimental design, decision-making, and the need to rethink biomarker discovery. She also encourages embracing generalism and risk-taking for career growth, highlighting strategies for expanding professional opportunities.