• How can the integration of multi omic data and real-world evidence be used earlier in drug discovery to inform target selection, indication choice and responder hypothesis generation?
• What limitations of current real-world evidence sources most impact their usefulness for discovery stage modelling, and how can these be mitigated through study design or data curation?
• Which applied AIML approaches are proving most effective at linking molecular mechanisms to observed patient level drug responses and resistance patterns?

*Agenda subject to change