Information governance is a set of practices and methodologies involving the oversight of information in a corporate setting, taking the various controls, metrics, processes and roles regarding information into account . Information governance in life sciences is especially important, particularly where clinical trials are concerned. Considering the complex nature of records, regulations and sensitive data in this industry, it’s easy to see why. Governing information efficiently, cost-effectively and compliantly is an essential concern for firms in the pharma industry and all those involved in clinical trials.

The Basics of Governing Information

Most corporations and large organizations have a management framework in place for their sensitive records and valuable information assets because, data is a valuable business asset. The idea behind information governance is to look at these commodities holistically and take active, accountable measures to ensure regulatory compliance, make information assets available, cut data storage costs and make management more productive and efficient. When managing important information (such as the data collected in a clinical trial), the right governance techniques can also mitigate legal risks, make the research operation more responsive in the face of change and streamline the firm’s overall organizational structure. To successfully govern such information, it takes more than basic records management methodologies. The critical nature of this data makes its accuracy, compliancy, availability and security more important than other large sets of data.

The Unique Considerations of Clinical Trials

Clinical trials are heavily regulated to ensure accuracy, privacy, human safety and compliance with federal, state and industrywide regulations. The amount of data collected by research firms during the clinical trial cycle is overwhelming, and the amount of information being generated and stored continues to grow at an aggressive rate. It’s practically impossible to express just how much data is generated in this industry, but take one example: The amount of data generated by the life sciences industry in 2011 alone was approximately 150 exabytes , according to leading estimates. Experts have also estimated that if we were to store every word that a person has ever spoken, in every language past and present, the resulting data would amount to about five exabytes. That’s more data than one person can truly fathom! While information governance in life sciences involves more than just clinical trials, these trials account for a huge chunk of this growing data, and governing it effectively (and compliantly) obviously poses some unique challenges.

Takeaways about Information Governance in Clinical Trials

When implementing a new records management and data governance plan for a pharmaceutical or clinical research firm, it’s important to understand and analyze every aspect of the information being generated. These are a few of the most important factors to consider:

  • What is the purpose of each set of information?
  • What kind of data are we dealing with?
  • What security and compliance measures are in place?
  • Where is this data being filed/stored right now?
  • When was this information generated?
  • Which people are authorized to access this information ?

To resolve the big data challenges facing pharma companies today, particularly with regard to clinical trials, it’s essential to have an enterprise information management solution that is intuitively designed for an organization in this specific industry. Such a solution should be based on a reference architecture for clinical trials, carefully integrated within the information framework of the organization with customized applications for recording and storing lab data, complying with federal regulations, analyzing results and quickly accessing information when necessary. This solution might differ from one life sciences firm to the next depending on their unique needs and goals, which is why working with an experienced consultancy is recommended when implementing a new enterprise information management system in this or any other heavily regulated industry.