title: Signal detection in post-marketing surveillance for controlled substances.
abstract: Signal detection for pharmaceutical controlled substances presents unique challenges compared to other pharmacovigilance programs because risks are present in the patient and non-patient populations. Defining signals for controlled substances has been difficult because no specific empirical criteria have been established through regulatory actions or guidances. We start with a review of data sources available for decision making to regulators and industry. In this paper we present a framework for processing signals received during post-marketing surveillance: signal identification, verification and assessment, followed by intervention and evaluation. Signal identification involves processing qualitative and quantitative information in order to generate hypotheses describing concerns with controlled substances. Integration of heterogeneous data sources makes this process difficult and we describe multiple approaches utilized in practice today. Signal verification currently relies heavily on telephone interviews with stakeholders in local communities. Once information on a potential signal has been gathered signal assessment is a higher order process conducted with an eye towards broader societal expectations and the ability to intervene or further study the problem. Intervention and evaluation complete the cycle of signal assessment and triage. This paper is intended as a primer of the current practice of signal assessment in the post-marketing surveillance for controlled substances.
authors.affiliation: Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA.
authors.forename: Nabarun
authors.initials: N
authors.lastname: Dasgupta
authors.forename: Sidney H
authors.initials: SH
authors.lastname: Schnoll
mesh_terms: D016208:Databases, Factual; D004335:Drug and Narcotic Control / Q000379:methods*; D006801:Humans; D011358:Product Surveillance, Postmarketing / Q000379:methods*; D018570:Risk Assessment / Q000379:methods; D017603:Signal Detection, Psychological