However, current AI applications are severely inadequate in predicting clinical trial outcomes. There are more articles on AI applied to drug development than to clinical trials due to factors such as data availability and complexity. In fact, efficiency gains or cost reductions in the clinical trial phase have a much larger impact on investment in new drug R&D than in the drug discovery phase as illustrated by Fig. . There has been a surge in the interest surrounding AI in the prediction of clinical trial outcomes due to two main factors. Firstly, the widespread adoption of electronic health records (EHRs) and electronic data capturing systems (EDC) has resulted in an unprecedented volume of patient data being available. Second, AI has had numerous successful applications in fields such as chatbot, object detection and art design.