ACM Global Blog Harnessing the Power of Clinical Data

Data management within the central laboratory field is currently undergoing an identity crisis. Data management groups across today's industry are facing challenges in adding more value to the information they produce. This is the final installment of a three-part series that examines the evolving role of the modern data manager. Data governance is also a current trend within data management among central labs. The dissolution of the Safe Harbour agreement and the limbo period we currently find ourselves in show the balancing act we currently face for data ethics and information transfer consent. As many companies are scrambling to get a model clause agreement in place to enable the data transmission across the Atlantic, the thoughts of data governance are beginning to expand across all central lab data. In today's clinical trials, clinical data solely belongs to the CRO or pharma company running the trial. We can run data trend recognition across the data sets for a CRO or sponsor, but only on their data. The trends we can see, which highlight site error rates, country-wide collection rates and time from enrollment to first visit are helpful for the current clinical trial, but the data sets are usually too small to provide an understanding of a full pattern that is applicable outside of the current disease area. Modern thoughts are turning to aggregated data. What if we pool the enrollment data for all clinical trials run at a central lab? What if we have data on 80 sites in a specific country and maintain a separate data set of 60 sites in a different country? Imagine the power that combined data sets could provide during clinical trial set up. The major stumbling block for the pooling of data is consent. We need consent to pool data from different sponsors and across different trials. If we want to add power to our datasets, we need to collaborate more as an industry. This collaboration is beginning to gain momentum, but until we can legislate the pooling of anonymized data, we are still only harnessing a small portion of our data's power.Throughout all of the topics discussed in this blog series, the theme should remain constant: data management groups, regardless of their industries, are facing challenges in adding value to all of the data they can output. The days of sending out datasets without adding value by interpreting trends or highlighting error rate fluctuations are assigned to history. The modern data manager is morphing into a data scientist who is not just responsible for transforming dataset formats, but also for driving how the data can benefit a trial. Many companies such as Google, LinkedIn and Facebook are establishing high-powered data scientist roles, and the need for such a role in clinical research is becoming a constant pressure. With the online revolution of data taking place, it is evident that it is time for clinical data management to reinvent itself. I certainly think so.To learn more about ACM Global's data management expertise, click here and read my previous posts.