Interview with Tim Rolfe

Risk-based monitoring plays an increasingly important role for clinical trials. Of course, the assessment of the risk is based on statistics. This presents now only interesting career options for statisticians, but also has an impact on the role of statisticians in study teams.

In this episode, we’ll give you an introduction to risk-based monitoring (RBM) as well as speak about the role of statisticians in this area. Further we provide you as a study statistician insights into what you need to know about RBM. Finally, we also give some recommendations in terms of further resources to learn from.

Tim Rolfe

Tim Rolfe has over 20 years of experience working as a statistician at in the pharmaceutical industry.  He is currently Director of Risk Based Monitoring at GlaxoSmithKline R&D. 

He has been part of GSKs RBM team since 2013, providing statistical leadership in the development and implementation of GSK’s RBM strategy within clinical trials.

Useful references

ICH E6-R2 – Good Clinical Practice:

ICH Harmonised Guideline.  Integrated Addendum to ICH E6(R1): Guideline for Good Clinical Practice E6(R2)

FDA Guidelines:

Guidance for Industry Oversight of Clinical Investigations — A Risk-Based Approach to Monitoring.

A Risk-Based Approach to Monitoring of Clinical Investigations Questions and Answers Guidance for Industry DRAFT GUIDANCE.

EMEA Guidelines:

Reflection paper on risk based quality management in clinical trials.


Position Paper: Risk-Based Monitoring Methodology.

Central Statistical Monitoring:

Buyse, M, George, SL, Evans, S.  The role of biostatistics in the prevention, detection and treatment of fraud in clinical trials. Stat Med 1999; 18: 3435–51.

Baigent, C, Harrell, FE, Buyse, M, Emberson, JR, Altman, DG.  Ensuring trial validity by data quality assurance and diversification of monitoring methods. Clin Trials 2008; 5: 49–55.

Kirkwood, A. A., Cox, T., & Hackshaw, A.  Application of methods for central statistical monitoring in clinical trials. Clinl Trials 2013;10(5), 783–806. 


Join The Effective Statistician LinkedIn group

I want to help the community of statisticians, data scientists, programmers and other quantitative scientists to be more influential, innovative, and effective. I believe that as a community we can help our research, our regulatory and payer systems, and ultimately physicians and patients take better decisions based on better evidence.

I work to achieve a future in which everyone can access the right evidence in the right format at the right time to make sound decisions.

When my kids are sick, I want to have good evidence to discuss with the physician about the different therapy choices.

When my mother is sick, I want her to understand the evidence and being able to understand it.

When I get sick, I want to find evidence that I can trust and that helps me to have meaningful discussions with my healthcare professionals.

I want to live in a world, where the media reports correctly about medical evidence and in which society distinguishes between fake evidence and real evidence.

Let’s work together to achieve this.