Will AI Replace Statisticians? The Future of Statistics in Pharma

A Conversation with Chris Harbron

Why you should listen

Listen to this episode to:

• Understand how AI may change statistical work in the pharmaceutical industry
• Recognize the limitations of using AI in clinical trial design and decision-making
• Explore why human judgment, collaboration, and accountability still matter
• Learn which capabilities statisticians should strengthen for an AI-enabled future
• Discover practical ways to experiment with AI in your daily work
• Approach the future of statistics with greater confidence and curiosity

Episode highlights with timestamps

• 01:30 – Will AI make statisticians redundant?
  I introduce the central question behind my conversation with Chris.
• 03:27 – Can AI create an entire clinical study package?
  We examine what AI can generate—and why plausible outputs still require careful scrutiny.
• 05:16 – A protocol is more than a document
  Chris explains how document development supports alignment, precision, and better scientific discussions.
• 07:08 – Navigating real-world trade-offsWe discuss the challenge of balancing timelines, budgets, sample sizes, biomarkers, and broader development goals.
• 10:18 – Combining human and artificial intelligence
  We consider how AI can complement experience rather than simply compete with it.
• 12:41 – Why keeping a human in the loop matters
  Chris highlights an important challenge surrounding review quality and confidence in AI-generated work.
• 13:37 – Building trust in an AI-enabled workplace
  We explore what statisticians provide beyond technical competence.
• 15:53 – Who remains accountable when AI gets it wrong?
  Our conversation turns to responsibility, risk, and the limits of delegating decisions to technology.
• 17:17 – How statisticians can prepare for the future
  Chris offers practical guidance for professionals working with clinical trials, real-world evidence, and other data projects.
• 22:07 – A promising future for statisticians
  We close by considering how AI could create new opportunities for the profession.

Links and Resources:

🔗 Read Chris Harbron’s paper: Will the Pharmaceutical Industry Need Statisticians in an AI World?

🔗 Learn more about Chris Harbron and PoshStatsConnect with Chris Harbron on LinkedIn

🔗 Learn more about PSI and become a member

🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician.

🔗 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.

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