Signal Detection

With the growing importance of Signal Detection for Pharmacovigilance, MAHs are expected to deploy state-of-the-art methodologies and look for best quality evidence to satisfy the needs and meet the expectation of regulators, patients and the public at large. With electronic data capture and electronic reporting becoming mandatory, there is a fast accruing safety dataset that needs to be reviewed in a structured and auditable manner.

Condensing this large and complex dataset into 2×2 contingency tables for disproportionality analysis, using computer-aided statistical data mining algorithms, is now a necessity than a luxury.

Signals have qualitative and quantitative aspects. In addition to spontaneous reports, clinical study data, both pre- and post-approval, play a key role in understanding a medicine’s benefit-risk profile. Pharmaceutical companies also use this information to detect signals of potential adverse medication effects. Different categories of adverse events need different methods for detection.

PvEdge offers a unique Signal Detection Software tool for Pharmacovigilance, combining advanced data mining algorithms with a qualitative review of each identified ICSR of interest, which is the current industry Gold standard.

Quantitative Signal Detection Software Tool

It calculates the PRR, upper bound – lower bound CI’s and also corresponding Chi-square values, for identifying statistical signals of disproportionate reporting.

Once statistical signals are identified, the database allows clinical evaluation of each ICSR for the identified SDR (Signal of Disproportionate Reporting), thus differentiating true clinical signals from statistical noise or reporting artifacts.

Qualitative Signal Detection Software Tool

In addition, during the initial assessment of ICSRS, PvEdge routinely flashes Targeted Medical Events (TME’s) and Adverse Events of Special Interest (AESI’s) as ‘to be monitored’ Drug – Event combinations, thus facilitating Index or Striking case method of Traditional Signal detection