Today we are a data management team, reviewing data, checking quality and ensuring data is ready for submissions. Tomorrow we are data scientists monitoring data, analyzing data trends and ensuring processes produce quality data for submissions. Lets talk about what makes data sciences different from data management, and if there are there any roadblocks or alarms we should be heading through our metamorphosis.

Although we may not have all of the answers or plans in place just yet, one thing is certain, and that is that the role of a data manager as we currently know it will be changing over the next few years. It is unavoidable and we need to already be adapting our process, plans, strategies and most importantly our work force to be aligning with this approach to data management/cleaning.

We are already seeing new data collection approaches, but not just around the actual data collection (CRF and external data) itself but also the strategies of data collection/cleaning as well. When standing back and observing from a distance it is quite easy for a data manager to feel a little worried/threatened by the prospect of these changes, since many of these are limiting/changing the way in which data will need to be collected, analysed and cleaned. Additionally, while walking through the booths at any industry relevant conference it becomes very obvious that there is are technologies out there which are currently successfully supporting these new approaches and in effect changing the way we manage our data as a whole on clinical trials. This should however be an exciting prospect, not a threatening one. It does not mean the end of the “data Manager role” it just means a change in focus, adaption to new strategies and support of new technologies. The birth of the “Data scientist”.