✔ 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.

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.

🔗 Thomas' Adventure Blog

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🔗 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.

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✔ 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

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:

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.

✔ 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

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.

🔗 Explore Cytel’s data science insights and case studies

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🔗 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.

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✔ 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

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.

🔗 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.

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✔ Why the 21st century is truly the "century of biology" and what that means for statisticians

✔ The untapped opportunity for statisticians to innovate before clinical trials begin

✔ How AI-guided experiments are changing drug discovery—and the statistical challenges they bring

✔ Why experimental design and decision quality matter more than ever in biotech

✔ The critical need to rethink biomarker discovery through a counterfactual and regulatory lens

✔ How to increase the validity of translational models and bridge the in vitro-to-in vivo gap

✔ Reflections on career risk-taking, generalism, and increasing your “surface area of luck”

If you're curious about how artificial intelligence is transforming biotechnology—and what role statisticians can and should play—this keynote is for you. Manjari Narayan offers a rare perspective at the intersection of statistical thinking, AI, and early-stage drug development, showing how rigorous methodology can shape better decision-making in start-ups, research labs, and beyond. Whether you work in pharma, clinical research, or academic science, you'll gain a deeper understanding of how to improve experimental design, validate next-generation biomarkers, and contribute to high-impact innovations before clinical trials even begin. Beyond the science, Manjari also shares powerful insights on career growth, risk-taking, and how to increase your “surface area of luck” by stepping outside your comfort zone and pursuing ambitious problems.

🔗 Manjari Narayan

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🔗 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.

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✔ When and how to combine RCTs with real-world data (RWD)

✔ The CJD study: lessons from combining registry and trial data

✔ Hierarchical Bayesian meta-analysis and shrinkage estimators

✔ Robustness of these approaches in the face of heterogeneity

✔ Practical coding tips using the bayesmeta R package

✔ Design strategies for prospective data integration

✔ Regulatory perspectives on RWD-supported evidence

If you’re working in rare diseases, pediatrics, or situations where large-scale RCTs are not feasible, this episode offers practical tools and methodological clarity. Tim’s approach helps statisticians create more informative and reliable evidence from limited data—crucial for both research impact and regulatory engagement.

🔗 Bayesmeta R package

🔗 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.

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✔ The motivation behind emulating randomized trials using real-world data

✔ How claims and EHR data can support regulatory-grade evidence

✔ What makes a trial emulation good vs. suboptimal

✔ The role of adherence, measurement limitations, and data quality

✔ Use cases where RWE could expand indications or replace costly trials

✔ Key takeaways from the RCT DUPLICATE project and the “Benchmark-Calibrate-Extrapolate” strategy

✔ Biostatisticians and epidemiologists

✔ Health tech innovators and data scientists

✔ Regulatory affairs and clinical development professionals

✔ Anyone involved in real-world data, RWE, or comparative effectiveness research

🔗 JAMA 2023 RCT DUPLICATE Publication

🔗 RCT DUPLICATE protocols and SAPs on ClinicalTrials.gov

🔗 FDA Framework for Real-World Evidence

🔗 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:
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✔ Why networking is about curiosity—not small talk

✔ How to set clear intentions for networking at events

✔ The three biggest myths that hold people back from networking (and how to overcome them)

✔ Practical tips for PSI Conference attendees to network with confidence

✔ The real-world value of building relationships with peers, leaders, and mentors

If you’ve ever felt like networking was awkward, inauthentic, or simply “not for you,” this episode will change your mind. Whether you’re a seasoned statistician or new to the field, you’ll discover how to network with sincerity—and how that can lead to unexpected career breakthroughs, personal growth, and a stronger sense of community.

🔗 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:
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✔ Why inclusion is everyone’s responsibility—not just HR’s

✔ The difference between “reasonable adjustments” and “success enablers”

✔ How AI tools can support accessibility and productivity

✔ The hidden challenges behind late diagnoses of neurodivergence

✔ Why leaders need to ask, not assume, what their team members need

✔ How inclusive environments lead to better outcomes for people and businesses

🔗 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:
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✔ Discover how SLRs are evolving through automation and AI

✔ Learn how real-time data can improve cancer treatment decisions

✔ Understand the balance between innovation and clinical responsibility

✔ Hear about a tool that could change the way guidelines and clinical practice align

✔ Be inspired by a founder’s mission to create impact through altruistic innovation

🔗 Oncoscope - Real-time evidence in oncology
empowering effective treatment decisions

🔗 Connect with Anna Forsythe on LinkedIn

🔗 MRC Biostatistics Unit – University of Cambridge

🔗 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.

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