4.6 Article

Assessment of the Safety Signal for the Abuse Potential of Pregabalin and Gabapentin Using the FAERS Database and Big Data Search Analytics

Journal

FRONTIERS IN PSYCHIATRY
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fpsyt.2021.640264

Keywords

pregabalin; gabapentin; big data; Google search analytics; disproportionality analysis; abuse potential; safety signal; FAERS database

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The study identified a potential for abuse of pregabalin and gabapentin through analysis of FAERS database and big data search analytics. Comparison with clonazepam and levetiracetam showed higher rankings for pregabalin and gabapentin. A correlation was found between FAERS and Google search results, suggesting the potential use of these methods for detecting drug abuse-related safety signals.
Introduction: The latest decade, an emerging issue has been the abuse potential of the gabapentinoids pregabalin and gabapentin. The aim of our study was to assess this safety signal combining two different methods of surveillance: search analytics big data and the FDA spontaneous reporting system database. Methods: Analysis of big data and the FAERS was used to detect pregabalin's and gabapentin's abuse potential in comparison with two controls, clonazepam and levetiracetam, and further, the correlation between these domains was investigated. Data from the United States between 2007 and 2020Q2 were analyzed. Results: The FAERS analysis revealed the following pattern of signals: clonazepam > pregabalin >= gabapentin > levetiracetam, for both the primary term drug abuse and dependence and the secondary terms (withdrawal, tolerance, overdose). The Google domain pattern was slightly different: clonazepam >= gabapentin >= pregabalin >= levetiracetam. A monotonic correlation was found between FAERS and Google searches for gabapentin (r = 0.558; p < 0.001), pregabalin (r = 0.587; p < 0.001), and clonazepam (r = 0.295; p = 0.030). Conclusion: Our results revealed that there is preliminary evidence of a safety signal for the abuse potential of pregabalin and gabapentin. Analysis of the FAERS database, supplemented by big data search analytics, suggests that there is potential of using these methods as a supplementary tool to detect drug abuse-related safety signals in pharmacovigilance.

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