October 26 2007 - The true test of the suitability of data collection and processing systems for adaptive studies is more than a measure of discrete activities at the input stage.
Adaptive research is critically dependent on timely availability of clean data and metadata for both strategic (design) and tactical (study management) decisions that determine the course of the trial. The more and sooner clean data and performance metrics are available, the greater the likelihood of making the right decision – especially if there is only one chance to make the decision, as in the case of an interim analysis. Conversely, delays in the availability of clean data can lead to less sure and possibly erroneous decisions and compromise other study activities, such as timely enrollment. The adaptive requirement for timely clean data focuses attention on EDC systems because “electronic” is equated with “fast and accurate.” While Web-based EDC systems are indeed faster than the laborious paper and hand entry-verification system, they nevertheless remain considerably slower and less accurate than other EDC systems, such as the electronic pen, that do not require keyboard entry at the site and multiple transcription steps of data (source to CRF to keyboard).
A major deficiency in most Web-based EDC is that it deals solely with data, overlooking the more important ability to collect study performance metrics that provide the critical ability to effectively manage complex studies.
Adaptive research increasingly calls on systems that go beyond data capture for high-velocity programs. The “middleware” that turns data and metadata must effectively and promptly turn a stream of raw data into meaningful, actionable information that must be provided in different forms for different roles. This leads to further improvements in the research process, such as adaptive monitoring – monitoring according to need rather than rigid fixed schedules – and, more critically, the ability to look further ahead in the program to minimize the between-study intervals.
With experience on more than 300 adaptive trials, it’s clear that data capture is necessary but not sufficient to run fast-moving programs. Indeed, the more important elements are performance metrics that enable the capability that lies at the heart of adaptive trials: continuous fine tuning of multiple study parameters. Even effective management of study supplies can affect key elements that underlie adaptive strategies, for example, if the right drug isn’t at the right place when needed. This emphasizes the need for a fully integrated system that deals with data collection, randomization, data management, and logistics, such as supplies and payments.
The true test of suitability of data collection and processing systems for adaptive studies is more than a measure of discrete activities at the input stage. Study decision-makers on multiple levels must have the timely, accurate they need when they need it to make decisions based on adaptive criteria. A weak link anywhere along the chain will compromise the capability of the whole system and undermine the success of any of the adaptive components.