According to Wikipedia, Fear, Uncertainty and Doubt (FUD) is “a strategy to influence perception by disseminating negative and dubious or false information and a manifestation of the appeal to fear.” This phrase dates to at least the early 20th century. How does this relate to the present common usage of disinformation related to software, hardware and technology in the biopharma industry? Well it is actually closer than you would think, so let’s have a look at some data management related issues, which are not new but obviously also not solved either.

There are quite a number of scientific evaluations which examine the impact of “wrong” data on study results. Whether this is because Source Data Verification (SDV) didn’t catch it or because edit checks were insufficient – all these studies show high robustness of collected data against errors. Nevertheless, we are all afraid of missing or erroneous data (Fear), we are uncertain about the number and kind of edit checks we need (Uncertainty) and we doubt that our monitoring and data management forces are doing enough to provide us with data quality which will be matching regulatory expectations (Doubt).

It seems that there isn’t much motivation to change the situation. CROs have sponsors pay for “intensive” data checking, sponsors want to be “on the safe side” and technology providers try to sell some innovations which claim to solve everything. Meanwhile, we are trying to use new clinical research information technologies without taking into account the impact this may have for the overall data flow and corresponding processes. What started with EDC (applying paper processes in an electronic world) continues with eCOA and mHealth approaches.

In a recent client example, we observed five different data sources, multiple technology providers plus a Data Management / Statistics CRO who was in charge to transfer, consolidate, clean, transform and eventually analyze the data. Primary endpoint data was coming from an eCOA device via a symptom score. Of course the sponsor was concerned about the completeness, the consistency and the overall quality of the data. Despite the fact that the eCOA data was transferred to the database at the eCOA vendor instantly, the transfer of eCOA data to the DM CRO didn’t happen until after 2 months of study start, and at that time 80% of the overall data had already been collected. Similarly, uncovering errors within the eCOA system or device handling issues by sites and patients could only be discovered relatively late in the process, after data transfer.

This leads to the ongoing and critical questions all sponsors have about proper data flow, processes and the single point of truth for all data. This is becoming more complicated as the number of different data source keeps increasing. Does the technology solution need to be one single big repository? This topic has been discussed for many years, with quite different answers coming from technology providers (or CROs) on the one hand, and company-specific solutions among sponsors. To define and consistently execute proper processes for these scenarios is at least as important as the technology itself. This requires people with technical understanding, flexibility and process thinking. The challenge will be to identify, develop, recruit and maintain these people who will do the work in this evolving environment.

Eventually, the combination of people, processes and technology (in this order!) can make a difference. It will enable us to gain better efficiency and could be the route to guide us from FUD to CCT: Confidence (we do it right!), Certainty (we do it in the most appropriate way) and Trust (we do it with the best people).

Detlef Nehrdich

Senior Associate

© Waife & Associates, Inc., 2019