Leveraging External Information in Clinical Trials

11th-12th July 2023, Newcastle upon Tyne, UK


Tuesday 11th July - Wednesday 12th July 2023


Newcastle upon Tyne

Cost and Registration

Private sector: £600 Public sector: £400 Students: £300

To enrol, please go to the Newcastle University Webstore


The ability to utilise external information (such as from disease cohorts, previous trials, and expert opinion) when designing and analysing clinical trials brings many benefits, including maximising the evidence provided by the trial, reducing the sample size required (particularly important for rare disease trials) and improving the generalisability of trial results. This course provides participants with a range of the latest statistical methods that can be used to incorporate external information and thus improve the efficiency and robustness of clinical trials. We also cover potential biases and pitfalls that may arise, and how to address them.

The following topics will be included:

  • Bayesian methods that form prior distributions from elicited and (multiple) external data sources.
  • Bayesian and hybrid approaches (e.g. assurance) that account for uncertainty in sample size calculations.
  • Methods that facilitate borrowing of historical information or data from within the same trial (e.g. master protocols).
  • Frequentist methods (e.g. propensity score weighting) that use external data, such as cohort studies and routinely collected healthcare records, to for synthetic control groups and generalise results from less representative trials to wider patient populations.
  • Application to real clinical trials, including trials for rare diseases.

As well as the necessary theory, we will cover computational approaches to implement the methods and practical issues, such as funder and regulator views.



This will be a two-day course consisting of around 8 lectures each with an associated practical session delivered in R.


Q: Is the course running in person or online?

A: Currently we are only planning to run the course in person

Q: I’m not a statistician, will I benefit from the course?

A: The course is predominantly aimed at applied statisticians, but hopefully many parts of the course will be useful to non-statisticians! Some lectures may be more difficult but if you don’t mind some Greek letters and other mathematical symbols, you should be okay.