Platform designs are described as umbrella trials comparing multiple experimental treatments to a common control within a single disease that additionally allow new treatments to enter across the life of the study (LaVange and Woodcock, 2017). These designs aim to make efficient use of patient data, reduce numbers allocated to control therapy and trigger early decisions to halt ineffective treatments. More experimental versions consider the addition of combination arms (e.g., A+B+X) based on observed outcomes from initial arms (e.g., A+B). These designs introduce a number of statistical, operational and clinical challenges - for example, accounting for temporal changes in activity of the control arm, performing indirect comparison between experimental arms and the switching of controls mid-study. Trials that introduce biomarker enrichment strategies with arms add additional complexity in relation to both patient allocation and analysis. The authors will discuss these challenges and considerations for both design and analysis of such trials.