• Let’s talk about the definition of data management to kick off our conversation today 

• What is the ideal definition of a data scientist, and does that apply to data management? 

• What is the role of a clinical data manager?

• How can we handle data processes and what tools can be utilised on the front end to help data analysis 

• When it comes to assess the challenges of assessing data, can we touch on quality not quantity and data cleaning?

• Guidance on data management is imperative, how do we overcome the challenge and handling of protocol deviations?

• The format of data is incredibly important – can you talk to me about why and how we can standardise this approach? 

• Discussing the challenges and best practices in the evolution of data managers acquiring new skills, adopting new technologies and employing new working methodologies in Clinical Data Management 

• Assessing how machine learning and artificial intelligence can be applied to the practice of data management, review and data quality and how that may transform the function to data sciences