Growing Concerns About Data Continuity in Biopharma Evidence Generation

One of the common concerns within biopharma is not a matter of generating evidence per se. What makes it even harder is the possibility of sustaining a consistent stream of information through several studies or regulations over prolonged periods of time. As such, the issue of data continuity gains more importance as evidence generation software solutions are currently evaluated by potential buyers.

Evidentiary initiatives are never limited to the sole scope of their objectives. Information retrieved once can become relevant several times over the life cycle of a particular product. Researchers may need to re-examine certain findings, compare results of treatment between different periods of time or study data acquired within separate research processes. It becomes especially complicated if there are no consistent information sources within an organization.

Such considerations begin to impact the choice of evidence generation software. While the tools themselves are hardly ever used to produce any scientific insights directly, their contribution lies in facilitating further evidence processing and management.

The problem becomes apparent as evidentiary research programs move past their initial objectives. It is rare for evidence generation initiatives to have a definite deadline or goal. Several years may pass between the start of the research process and its end, which means that there can be many staff changes, reconsiderations of previous assumptions or emergence of new questions.

When information proves hard to find or analyze, the whole process can be slowed down significantly. The amount of effort spent tracking documents, verifying the integrity of information and understanding research history may prove to be considerable. At the same time, these aspects might not become a major focus of technology evaluation.

Procurement conversations about evidence generation software solutions are shifting in this direction. Buyers' attention moves from operational effectiveness to information sustainability as evidence programs grow more extensive and complex. They are starting to see evidence generation software platforms as tools for sustaining knowledge over time rather than project management resources.

This brings a change to the list of priorities for software developers. Features aimed at optimizing research processes are essential but buyers become concerned with data preservation as well. As such, information continuity becomes part of a solution's institutional memory function rather than just another aspect of project management.

While data continuity may not be as prominent as some new trends in evidence analytics, it addresses a pressing problem faced by many biopharma teams. Evidence generation projects tend to outlast their budgets, original objectives or even the members of a team conducting research.

For biopharma companies investing in such tools, the problem is shifting from acquiring new information to keeping existing data context-sensitive.