An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium

Ther Innov Regul Sci. 2024 Jul;58(4):591-599. doi: 10.1007/s43441-024-00631-8. Epub 2024 Apr 2.

Abstract

Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials.

Keywords: Analytics; GCP; Open-source; Quality assurance; Transparency; Validation.

Publication types

  • Validation Study

MeSH terms

  • Adverse Drug Reaction Reporting Systems* / standards
  • Clinical Trials as Topic*
  • Drug-Related Side Effects and Adverse Reactions
  • Humans
  • Software