Published clinical trial data holds rich information on treatments and clinical endpoints that can be useful for future trial design and clinical decisions. This data is usually locked in text form, and not easily accessible. Making such published clinical trial data FAIR is challenging. Even with such data being accessible there remain added complexities in using the data for mathematical models. This talk will explore the various stages of compiling useful datasets from published data all the way to leveraging this clinical knowledge to generate insight and enable data-informed decisions. Challenges and opportunities in this data journey will be discussed.