Abstract
Background:
The pharmaceutical industry has continued to experience a large number of mergers, often involving the very largest companies. Behind many of these mergers has been the desire to achieve scale efficiencies and improved performance in both commercial and research and development (R&D) activities.
Methods:
This research draws upon ClinicalTrials.gov data about commercially sponsored phase 3 clinical trials started and completed between 2008 and 2013. The research uses the bidirectional stepwise Akaike information criterion for model selection, adding a second-order term to the model where second-order terms were significant.
Results:
First, and least surprising, the study therapeutic area has a major impact on study completion times. Second, the protocol design itself, as well as the clinical study execution plan, can have important consequences on study completion times. Several study execution variables are also critical to understanding completion times. While the size of clinical trial organization is not associated with more rapid completion times, the amount of organizational experience that an organization has in a particular therapeutic area does have a demonstrable impact. The models are able to supply the specific number of incremental completion days associated with each significant variable.
Conclusions:
Recent years have witnessed increasingly larger pharmaceutical R&D organizations, as many companies have worked to achieve the scale benefits of organizational size for R&D as well as commercial activity. Larger pharmaceutical companies may still achieve scale benefits. Faster phase 3 study completion times is not one of them.
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