What I have discovered is that one of the greatest challenges is to convert the understanding, and clarification of the scientific demands of a study into the definition of data to capture.
It can be very difficult to write a clinical trial protocol. Often the thought process for the data to capture, the schedule and the underlying statistics are a combination of conjectures. As a result, it can be difficult to provide a definitive statement on exactly the data that is required. Maybe more labs should be taken? Maybe bio-markers are required? Maybe we should extend the study? What we often see is that if any doubt exists – then the implementation will err on the ‘lets capture it’ approach – better to ‘have the data, and not use it’ approach.
Achieving an accurate definition of the study is critical. More importantly, achieving an accurate definition of the study that all stakeholders understand and accept is fundamental. How many Clinical Development organizations decide to sign-off on a protocol due to time pressures, even though they know it has flaws, and will require changes?
Protocol Authoring Tools
One of the potential solutions to the problem of late and/or inaccurate study specifications is the introduction of Protocol Authoring tools. I have absolutely no doubt that the introduction of such a tool brings positive benefits. Typically, it applies a structure, and discipline to the process that can otherwise drag on.
However, I am not entirely convinced that using a Protocol Authoring tool alone is the answer to the requirement definition challenges.
Does the Protocol document provide the necessary visualization of the study, and the resulting data that allows all parties to understand and accept that it has been prepared correctly. I would hazard a guess that typically it does not.
I will continue this discussion in a later post.