A dashboard for exploring clinical trials sponsorship and potential virtual monopolies

S Scott Graham; Zoltan P Majdik; Joshua B Barbour; Justin F Rousseau

doi:10.1093/jamiaopen/ooab089

A dashboard for exploring clinical trials sponsorship and potential virtual monopolies

JAMIA Open. 2021 Oct 29;4(4):ooab089. doi: 10.1093/jamiaopen/ooab089. eCollection 2021 Oct.

Authors

S Scott Graham¹, Zoltan P Majdik², Joshua B Barbour³, Justin F Rousseau^{4

5}

Affiliations

¹ Department of Rhetoric & Writing, Center for Health Communication, University of Texas at Austin, Austin, Texas, USA.
² Department of Communication, North Dakota State University, Fargo, North Dakota, USA.
³ Department of Communication Studies, Moody College of Communication, University of Texas at Austin, Austin, Texas, USA.
⁴ Department of Population Health, Dell Medical School, The University of Texas at Austin, Austin, Texas, USA.
⁵ Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, Texas, USA.

Abstract

Objective: To create a data visualization dashboard to advance research related to clinical trials sponsorship and monopolistic practices in the pharmaceuticals industry.

Materials and methods: This R Shiny application aggregates data from ClinicialTrials.gov resulting from user's queries by terms. Returned data are visualized through an interactive dashboard.

Results: The Clinical Trials Sponsorship Network Dashboard (CTSND) uses force-directed network mapping algorithms to visualize clinical trials sponsorship data. Interpretation of network visualization is further supported with data on sponsor classes, sponsorship timelines, evaluated products, and target conditions. The source code for the CTSND is available at https://github.com/sscottgraham/ConflictMetrics.

Discussion: Monopolistic practices have been identified as a likely contributor to high drug prices in the United States. CTSND data and visualizations support the analysis of clinical trials sponsorship networks and may aid in identifying current and emerging monopolistic practices.

Conclusions: CTSND data can support more robust deliberation about an understudied area of drug pricing.

Keywords: clinical trials; data visualization; health policy informatics; network modeling; research funding.