Search

Pharmacovigilance studies based on spontaneous reporting systems use disproportionality analysis methods to identify drug‐event combinations with higher‐than‐expected reporting. Enhanced reporting is deemed as a proxy for a detected signal and is used to generate drug safety hypotheses, which can then be tested in pharmacoepidemiologic studies or randomized controlled trials. Higher‐than‐expected reporting means that the reporting rate of a drug‐event combination of interest is disproportionately higher than the rate in a specific comparator or reference set. Currently, it is unclear which comparator is the most appropriate for use in pharmacovigilance. Moreover, it is also unclear how the selection of a comparator may affect the directionality of the various reporting and other biases. This paper reviews commonly used comparators chosen for signal detection studies (active comparator, class‐exclusion comparator, and full data reference set). We give an overview of the advantages and disadvantages of each method based on examples from the literature. We also touch upon the challenges related to the derivation of general recommendations for the selection of comparators when mining spontaneous reports for pharmacovigilance. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has driven an unprecedented level of global activity in drug discovery and clinical development for effective therapeutics targeting the coronavirus disease. There are currently 744 therapeutics being tested in 2879 clinical trials globally. Almost 90% of these clinical trials are focused on monotherapies. Combination therapies are the mainstay of antiviral therapeutics to increase the potency of the individual compounds and to combat the rapid evolution of resistance, although combination therapies have inherently complex clinical and regulatory development challenges. Increased understanding of the SARS‐CoV‐2 lifecycle and COVID‐19 pathology provides a scientific rationale for evaluating the effectiveness of different combinations. In this paper, we provide an overview of the current clinical trial landscape for combination therapeutics targeting COVID‐19 through weekly scanning of national and international clinical trial registries. Our analysis delves specifically into dual combination therapies in what can be defined as "pivotal clinical trials" (active, randomised, controlled and at least phase II), with a focus on new and repurposed therapeutic candidates that have shown positive signals and/or been granted authorisation for emergency use based on positive efficacy and safety data. [ABSTRACT FROM AUTHOR]

2021; 87 (11): 4334 - 4340. doi: 10.1111/bcp.14851 2 Wysowski DK, Swartz L. Adverse drug event surveillance and drug withdrawals in the United States, 1969-2002: the importance of reporting suspected reactions. Access to de-identified real-world electronic health record databases along with these pharmacovigilance databases and newer statistical methodology in addition has enabled researchers to assess false-positive rates of ADRs attributable to specific drugs or drug classes. The goal of pharmacovigilance is to ensure that therapies are safe to use. [Extracted from the article]