Pharmacovigilance signaling

Pharmacovigilance signaling is an important aspect of pharmacovigilance. In simple terms, it is the detection of a new safety finding within a set of safety data which requires further investigation. The World Health Organization (WHO) defines pharmacovigilance signaling thus: ““reported information on a possible causal association between an adverse event and a drug, the relationship being unclear or incompletely documented previously”.

Why is pharmacovigilance signaling important?

For a drug to enter the market, it should have gone through a series of clinical trials and tests that establish its intended use and effect. These are very stringent and should take all aspects of the drug development into consideration. They are essentially aimed at making the drug and its manufacturing process documentable, verifiable, reproducible and predictable. These trials involve the collection of a huge amount of data pertaining to important aspects of the drug. Adverse events are one of them. Pharmacovigilance signaling establishes the link between an adverse event and the data, and hence is of pivotal importance to the clinical trial.

Categories of pharmacovigilance signaling

Pharmacologists usually classify these findings into three categories:

a)     Confirmed signals: in this scenario, data indicate that there is a causal relationship between the drug and the adverse effect (AE);

b)     Refuted (or false) pharmacovigilance signaling: this is a type of signaling in which the investigation shows no causal relationship between the drug and the AE;

c)      Unconfirmed signals: this is a type of finding in which the pharmacologists decide that there is need for further investigation. This investigation is done using more data. A prime example of this is the data that is got from carrying out a post-marketing trial to study the relationship between the drug and the AE.

Data mining

Having said this; pharmacovigilance signaling goes beyond just data used at the clinical trials. Since at least the 1990’s, statistical data mining emerged as a method of pharmacovigilance signaling. These are some of the kind of databases that are used for pharmacovigilance signaling:

  • Spontaneous reporting system (SRS) databases
  • Prescription event monitoring databases
  • Electronic medical records (EMR) databases
  • Large linked administrative databases, or electronic health records (EHR) databases

The main aim of mining databases for pharmacovigilance signaling is that they help researchers have a broader set of data for reference, leading to more accuracy of their tests.

References:

http://en.wikipedia.org/wiki/Pharmacovigilance#Signal_Detection

http://isif.org/fusion/proceedings/Fusion_2011/data/papers/200.pdf

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