Optimizing drug inventory management with a web-based information system: The TBTC Study 31/ACTG A5349 experience

Abstract

Introduction: Efficient management of study drug inventory shipments is critical to keep research sites enrolling into multisite clinical treatment trials. A standard manual drug-management process used by the Tuberculosis Trials Consortium (TBTC), did not accommodate import permit approval timelines, shipment transit-times and time-zone differences. We compared a new web-based solution with the manual process, during an international 34-site clinical trial conducted by the TBTC and the AIDS Clinical Trials Group (ACTG); TBTC Study 31/ACTG A5349.

Material and methods: We developed and implemented a technological solution by integrating logistical and regulatory requirements for drug importation with statistical simulations that estimated stock-out times in an online Drug Management Module (DMM). We measured the average shipment-related drug stock-outs and time to drug availability, to assess the efficiency of the DMM compared to the manual approach.

Results: An Interrupted Time-Series (ITS) analysis showed a 15.4% [p-value = 0.03; 95% C.I. (-28.8%, -2.0%)] reduction in average shipment-related study drug stock-out after DMM implementation. The DMM streamlined the restocking process at study sites, reducing median transit-time for sites associated with a depot by 2 days [95% C.I. (-3.0, -1.0)]. Under the DMM, study drugs were available for treatment assignment on the day received, compared to one day after receipt under the manual process.

Discussion: The DMM provided TBTC's Data and Coordinating Center and site staff with more efficient procedures to manage and consistently maintain study drug inventory at enrolling sites. This DMM framework can improve efficiency in future multicenter clinical trials.

Trial registration: This trial was registered with ClinicalTrials.gov (Identifier: NCT02410772) on April 8, 2015.

Keywords: Interrupted time-series analysis; Statistical simulations; Study drug inventory management; Study drug stock-out; Trial pharmaceuticals; Web-based system.

Conflict of interest statement

Declaration of conflicting interests

The authorship team members have declared (below or attached) any potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Sanofi commercial interests did not influence the study design; the collection, analysis, or interpretation of data; the preparation of this manuscript; or the decision to submit this manuscript for publication. A Sanofi technical expert served on the protocol team.

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Published by Elsevier Inc.

Figures

Figure 1:

Time-Series of Shipment-related Study Drug Stockouts, with Linear Trendlines for Manual and DMM Period Notes: DMM – Drug Management Module Slope of linear trendline in Manual Period (pre-DMM implementation) is 0.008. Counterfactual is a hypothetical representation of trendline with no DMM intervention. Slope of linear trendline in DMM Period (post-DMM implementation) is 0.002. A non-significant reduction of 0.006 in the slope from pre-DMM to post-DMM intervention (Table 2).

Figure 2:

Timing of Stock-out Events by Processing Type (Manual vs. DMM)