The Careers and Academic Liaison Committee (CALC) will be hosting their third Maths Meets Medicine event this year at the University of Reading.

This webinar proposes a short primer on stated preference methods and how they can be used to explore the patient preferences for specific drug profiles that are currently available or may be developed in the near future. The theory will be then discussed as applied to two case studies using quantitative preference methods.

As the availability of big data increases and statisticians assist with predicting outcomes or understanding patterns in an ever-wider variety of scenarios then supervised and unsupervised learning methods become increasing called upon. Such machine learning algorithms offer the opportunity to understand potential predictors or clusters amongst large datasets, but are also subject to the risks of overfitting or over-interpretation. This Webinar seeks to introduce ideas and share experiences in this field.

The draft ICH E9 addendum on estimands and sensitivity analysis was released back in July 2017 and (more than 1000) comments are back. All stakeholders are gaining the necessary experience and familiarity with estimands along with the associated challenges and methodologies. The language and thinking behind causal inference is well suited to this area.