For Successful Clinical Trials - ‘Next Generation’ in the eClinical Landscape

Published 30th March 2009

Written by Peg Regan, President of PharmaPros

Today’s clinical research technology landscape has evolved into the next generation of data acquisition systems and processes. What was once a fairly simple process of paper collection and entry into a single database has now transformed into a complex environment of multiple vehicles for faster, better acquisition methods. Ultimately, these next generation technologies can be leveraged to provide more immediate access to higher quality data for analysis that may reduce the overall time from protocol development through data submission.

With these technical improvements has emerged the ability to make available new data that was not previously useful for analysis. Patient diaries are one such example where the paper predecessor was not as evaluable as the contemporaneous electronic solutions of today. Furthermore, data requirements to support the safety and efficacy of advanced therapies have become increasingly complex by incorporating data from images, genomic information, and an increase in specialized lab data.

These factors rooted in technical and scientific progress have increased study complexity and exacerbated some facets of study conduct that were once easily handled via manual management or weekly project team communications. Some areas in study conduct that have become more strained as a result include:

• Harmonization and reconciliation of data from multiple vendors (i.e., EDC, ePRO, Central Labs, Image Labs, and/or IVRS.)
• Management of multiple vendor “study startups,” each with different deliverables, timelines, and managers.
• Technical support across different platforms and terminologies to a larger, changing user base (i.e., investigator sites).
• Understanding if data is available as expected, if delays in data acquisition impact the study timeline, or if problems with data quality will surface once data are integrated.
• Absolute trust that data are attributable, contemporaneous, original, and accurate

The inherent complexity of the next generation landscape, coupled with these new symptoms of study conduct problems, has led to a variety of potential technology fixes, including data integration and interchange. These approaches alone, however, do not promise to bring back simplicity to the process. They also do not adequately address the new gaps in study conduct.

Bridging the gaps that are inherent in today’s next generation landscape requires next generation processes that ensure data are being acquired as expected, that vendors are delivering results, that sites are functioning, that cross functional teams are focused on their objectives and not duplicating efforts, and that data problems are detected early and resolved well before analysis needs to be conducted. In today’s landscape, this process is Electronic Data Lifecycle Management (eDLM).

eDLM is not the data management of the past where data comes in, data gets processed, queries go out, and databases get locked. Those activities are central to study conduct, but they are not eDLM. Rather, eDLM is holistic data management across data sources. eDLM requires the complete knowledge of the different types of data being acquired on a continuum, keeping track of indicators that may point to potential data issues or study delays, looking for trends that point to problem sites requiring additional support, and managing vendors to reconcile data issues and ensure that they are performing to the study timelines.

The challenge of achieving eDLM is aggregating information from all the various data sources and vendors to determine the current state of the data in comparison to its expectation to support the decisions required to effectively manage the study. In today’s landscape, with so many moving parts, this task must be performed frequently. Yet to do so is often too daunting due to the challenges of constantly integrating data. It is possible, however, to simplify this effort, and even automate it. The key is to focus on the status of the operational data.

All data have purpose, and the decisions required to optimize study progress can be inferred from the status of these data. Integrating the status of these data to provide a picture of the state of the study requires some knowledge of the type of source data. Effective management of a clinical trial cannot be achieved without getting control of the study data to understand when the appropriate information is available for necessary decision-making and timely corrective action.

Obtaining the knowledge of when the appropriate information is available or “ready,” and then once it is “ready” knowing what action should be performed, is a difficult challenge. This process can largely be automated, however, by coupling an operational integration strategy with critical data expectations defined in the study protocol.

To automate data “readiness” a system must be utilized that is context-aware. To be context-aware, the system must understand the expectation of data as described in the study protocol, and must be able to retrieve data status across data sources using an optimal integration strategy that provides the most contemporaneous status possible.

Finally, “readiness” cannot be achieved without a quality process for managing the study data and team resources. Certainly, the intelligence is in the data. But a system cannot replace the need to interpret results, identify trends, and communicate findings to the team for taking action. Furthermore, without appropriate management of study data, such as adhering to a workflow ensuring that manual reviews or other processes outside the system are completed when available, the value of knowing when information is “ready” to take action decreases.

As we enter the next generation of eClinical research, organizations will need to incorporate these types of best practices and technologies, in order to meet the demands of this new landscape and remain competitive in the race toward innovating new products. For more information go to www.pharmapros.com