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The Future of Clinical Trial Data Management and Technology's Growing Impact

Insights from the BioClinica 2015 Global User Conference

At BioClinica's 2015 Global User Conference, I had the pleasure of leading an expert panel discussion on the future of data management. I would like to share some highlights from my perspective. Panel participants were Daun Bahr, senior director data management Orexigen; Queennette Santiago, head of data management Ultragenyx; Clara Plascencia, associate director of clinical data management Pharmacyclics; and Ann Seibel, clinical data manager BioClinica.

Data Managers' Growing Role
We discussed the important role data managers play in clinical studies. These study professionals are responsible for reviewing the clinical study data from first patient in (FPI), to database lock. As such, data managers must ensure the quality of the data to be analyzed and used in determining whether or not the drug candidate or device being tested is safe and effective.

This is a big responsibility indeed! Yet data managers today are finding new tasks on their to-do list that go beyond the traditional data review and cleaning. Increasingly they are becoming gatekeepers for numerous clinical systems that contain the data in the trial.

So how is it that we've arrived here? To answer this, one must consider that the pharma industry has been diligently working on integrating data between multiple groups, for instance clinical operations, drug supply, medical writing, data management and statistics. Progress has been made with more and more systems integrated in the last couple of years alone. Integration benefits include enhanced data sharing − bringing with it new insights from the data and opportunity for improved decision-making. Such is the case, for example, where operational data generated by the clinical group are shared with data management, or where clinical supply management data are shared with data reviewers.

As these systems have become integrated, data managers' responsibilities have broadened. In fact, in some organizations, their responsibility touches technology-related areas of integration, reporting, and metrics. System integration has given data managers access to a plethora of operational data – all of which can be mined for additional quality metrics.

Integration Benefits, Challenges
Panel members indicated that while multi-system integration brings many important benefits, it also creates challenges. For instance, we must better define data output using CDISC standards. Another challenge expressed is the added complexity that comes with collecting, reviewing and cleaning specialized therapeutic area data. These data can be tricky to collect as they tend to be contained in separate, specialized systems. Additionally, the reporting of these data are unique based on study protocol. Fortunately, CDISC has been working on therapeutic area standards to aid in reporting. Data managers must understand and implement these new standards.

Direct-to-Patient Growing
Another area undergoing change is direct-to-patient integrations in response to growing use of wearable patient technology, such as Fitbit® bands and Apple Watch technology. Patient engagement tools are on everyone's list of hot items to watch − introducing yet another set of considerations.

Data Managers' Perspective on Risk-Based Monitoring
Risk-based monitoring, a topic explored in-depth at this year's conference, was acknowledged by our panel and data managers in the audience as another strong area of interest. Many attending organizations said they have implemented risk-and quality-based plans in studies past and current. Feedback we received indicates most data managers welcome new technology-based solutions that will bring further improvements to clinical studies, such as BioClinica's Compass intelligent monitoring solution.

No doubt, the future of data management promises to be exciting. We heard from several data management experts, including Jonathan Andrus, that the industry is experiencing a renaissance of sorts where technology implementations and integrations require data managers and the entire study team, to embrace new tools to be successful within this technology-enabled era.

Successful Application of Intelligent Monitoring Tools in Data Management

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