Carl-Fredrik Burman

Biostatistics, AstraZeneca R&D, Sweden

Dr Carl-Fredrik Burman is Statistical Science Director at AstraZeneca, where he has been employed since 1995. He has worked within the cardiovascular, gastrointestinal and diabetes areas and contributed to the development of drugs such as Losec/Prilosec, Nexium, Seloken/Toprol-XL and Galida. He is currently engaged in promoting innovative methodology for the design of clinical trials and trial programmes.

Dr Burman has a basic education in Engineering (M.Sc.) and a Ph.D., based on a thesis about covariate-balancing adaptive study designs, in Mathematical Statistics, after studying at Chalmers Univ. of Tech., Gothenburg, Sweden. C-F Burman has been a guest researcher at Glasgow Univ., University College London and Chalmers. His current research interests are mainly within Decision Analysis, Modelling & Simulation, and design of clinical trials, especially adaptive designs. Dr Burman is a member of the European Federation for Statisticians in the Pharmaceutical Industry (EFSPI) council and PhRMA's working group on adaptive designs.

Any competing interests declared are displayed with individual evaluations.

Faculty Member: Research Methodology > Statistical Methodologies & Health Informatics (since 06 January 2006)

All recent recommendations

• 3.0
  Moving statistics beyond the individual clinical trial: applying decision science to optimize a clinical development plan
  Recommended by Carl-Fredrik Burman
  
• 4.8
  Implementing a decision-theoretic design in clinical trials: why and how?
  Recommended by Frank Harrell, Carl-Fredrik Burman
  
• 3.0
  Why most published research findings are false.
  Recommended by Carl-Fredrik Burman
  
• 3.0
  Tree-structured gatekeeping tests in clinical trials with hierarchically ordered multiple objectives.
  Recommended by Carl-Fredrik Burman
  
• 6.0
  Testing and estimation in flexible group sequential designs with adaptive treatment selection.
  Recommended by Carl-Fredrik Burman
  
• 3.0
  Phase 2 and 3 Combination Designs to Accelerate Drug Development
  Recommended by Carl-Fredrik Burman
  
• 3.0
  Dichotomizing continuous predictors in multiple regression: a bad idea.
  Recommended by Carl-Fredrik Burman
  
• 3.0
  Monitoring clinical trials--interim data should be publicly available.
  Recommended by Carl-Fredrik Burman
  
• 3.0
  A space-time permutation scan statistic for disease outbreak detection.
  Recommended by Carl-Fredrik Burman
  
• 9.0
  Evaluation of experiments with adaptive interim analyses.
  Recommended by Carl-Fredrik Burman