Signal Management Definition: A set of activities performed to determine whether, based on an examination of individual case safety reports (ICSRs), aggregated data from active surveillance systems or studies, scientific literature information or other data sources, there are new risks associated with an active substance or a medicinal product or whether known risks have changed, as well as any related recommendations, decisions, communications and tracking.
Activities include:
- Signal detection
- Signal validation
- Signal prioritization
- Signal assessment
- Recommendation for action
- Exchange of information
Signal detection: The process of looking for and/or identifying signals using data from any source.
The data retrieved on a per-product basis depending on the maturity of the safety profile and number of case reports for the concerned product. Signal detection follow a methodology which takes into account the nature of data and the characteristics (e.g. time on market, patient exposure, target population) as well as the type of medicinal product concerned (e.g. vaccines and biological medicinal products). Clinical judgement should always be applied.
Safety data to be monitored for Signal detection:
- Spontaneous reports (health authority or company database)
- Non clinical/pharmacology studies
- Clinical trials
- Adverse event reports (ICSRs)
- Published literature
- Non Interventional studies
- Periodic safety reports/Aggregate reports and RMPs as applicable to the medicinal product
- Information on other drugs in the same class
- Other relevant information
Methods to detect Signal:
Traditional PV methods:
- By reviewing each ICSR or case series
- Aggregate analysis of case report data
- Literature search and review.
Data mining algorithms:
- Proportional reporting ratio (PRR)
- Multi item Gamma poisson Shrinker (MGPS)
- Bayesian confident propagational neural network (BCPNN)
A new or potential safety signal is:
- New AEs, not currently documented in the RSI or in the package insert, specially if they are serious and have occurred in rare sub-populations.
- An apparent increase in the severity of an AE that is included in the RSI or in the package insert.
- Occurrence of serious adverse events (SAE) known to be extremely rare in the general population.
- Previously unrecognized interactions with other products, supplements or food.
- Identification of a previously unrecognized at-risk patient population or subgroup of patients, such as patients with specific medical conditions, comorbidities, or with specific racial or genetic predispositions.
- Adverse events arising from the way a product is being used either on or off-label (e.g. adverse events seen at doses higher than those normally prescribed or in sub-populations not recommended in the label.
- Adverse events arising from user errors, or from medication errors.
- Concerns arising from potential inadequacies of a currently implemented risk minimization action plan (RiskMAP), as for example reports of a serious adverse event that appears to indicate failure of a risk minimization goal.
Once the signal is detected it will be validated to verify that the available source documentation contains sufficient evidence demonstrating the existence of a new potentially causal association or a new aspect of a known association, and therefore justifies further prioritization and assessment of the signal.
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