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ISSN: 2329-6887
Journal of Pharmacovigilance
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Cradles of Signals for Pharmacovigilance Process

Suman Garlapati1* and Shanthi Priyanka2
1Drug Safety & Pharmacovigilance Officer, Invagen Pharmaceuticals, New York, USA
2Vigilare Biopharma, Pvt. Ltd. Kukatpally, Hyderabad, India
Corresponding Author : Suman Garlapati
Drug Safety & Pharmacovigilance Officer
Invagen Pharmaceuticals, New York, USA
Tel: 1-914-486-1898
E-mail: [email protected]
Received December 18, 2014; Accepted December 18, 2014; Published December 25, 2014
Citation: Garlapati S, Priyanka S (2015) Cradles of Signals for Pharmacovigilance Process. J Pharmacovigil 3:e126. doi: 10.4172/2329-6887.1000e126
Copyright: © 2015 Garlapati S. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Editorial
Adverse effects are manifold and diverse. Pharmacovigilance and signal detection are the lifetime activities to do for a drug (both pre and post marketing) to determine adverse events & to suggest a new potentially causal association or a new aspect of a known association. Anything which is new is considered as signal, it should be validated taking into account other relevant sources of information.
Signal Detection
The WHO defines a safety signal as
“Reported information on a possible causal relationship between an adverse event and a drug, the relationship being unknown or incompletely documented previously” [1]. Usually more than a single report is required to generate a signal, depending upon the event and quality of the reports available. When a signal is detected, further investigation is warranted to determine whether an actual causal relationship exists.
Signal Detection Tools
Single cases, aggregated data, literatures, databases
Sources of Signal Detection
The sources for identifying new signals are diverse. They potentially include all scientific information concerning the use of authorized medicinal products including quality, non-clinical, clinical and pharmacovigilance data. Sources for signals include spontaneous reporting systems, active surveillance systems, non-interventional studies, clinical trials and other sources of information.
Spontaneous reports of adverse reactions may be notified to pharmacovigilance systems, poison centers, teratology information services, and vaccine surveillance programs.
Signals in pharmacovigilance are usually derived from studies/ post market survilliers or experiments. They have both quantitative and qualitative aspects [2].
In case of qualitative reports ,single case may be a valid signal depending on the nature of the effect, quality of reports ,consistency of data ,biological plausibility of drug, previous experiences with the drug, time relatedness and possible evidence from other sources. Qualitative signals mainly concerns about the number of case reports and statistical considerations.
Marketing authorization holders should check internet or digital media under their management for potential adverse effects which may characterize a new signal
Important data which helps in finding signals are recent reports, dechallenge, rechallange, time relationship, geographical evaluation [3], biological plausibility, informative reports.
Qualitative signals
Spontaneous reports, Literature reports, Intensive hospital monitoring, Prescription event monitoring, Follow-up studies.
Quantitative signals
Large data resources, Case control studies, Intensive hospital monitoring, and Prescription event monitoring, Follow-up studies.
Experimental
• Clinical trials, Animal studies.
Quantitative strength of the association
• Number of individual case reports
• Statistical disproportionality
Consistency of the data (pattern)
• Exposure-response relationship
• Site, timing, dose, reversibility
• Biological plausibility of hypothesis
• Pharmacological, pathological
Experimental findings
• e.g. dechallenge, rechallange, blood levels, metabolites, drugdependent antibodies
Nature and quality of the data
• Objectivity, documentation, causality assessment
Three main sources of evidence for drug safety [4]:
–Controlled clinical trials –epidemiological studies –Statistical analysis
Besides the traditional review of spontaneous cases and other safety information by trained medical personnel, “data mining” [5] may also be carried out. This is the process of applying sophisticated statistical algorithms to large safety databases to determine whether certain adverse events (AEs) are being reported for a medicine with a greater frequency than expected (i.e., a signal of disproportionate reporting [6], or SDR), based on a statistical model. Statistical methods and epidemiological methods are mainly used to for large amount of datasets.
Discussion
Earlier there are no sophisticated data collection systems for adverse drug effects reporting. Now a days it’s a major concern to report the drug related adverse effects for the better life of the public and the drug. Drug starts with absolute no adverse events. As the drug passes through development process and post market application, adverse effects starts appearing. Then pharmacovigilance and signal mechanism comes into picture to collect, detect, analyze, report and treatment of adverse drug effects.
The relation between drug and event is difficult to finalize because of complex, confounding factors. It requires varied data from spontaneous reports, non-clinical, clinical trial reports to know the pharmacological effects of drug and its effects in human beings, data from market authorization holders to know the post authorization history of the drug. Different adverse effects require different methods of signal detection. Besides varied data expertise and better understanding of scientific methods is necessary for rationale decision making in pharmacovigilance and signal detection. Although statistics deal with large amount of data, it’s the medical and scientific judgment of expert pharmacovigilance professions decision makes the priority. For this decision making various sources are necessary.
Conclusion
Signals in pharmacovigilance have variety of sources. A better understanding of signal detection may enable further improvements in pharmacovigilance, drug regulation and recommendation of action for risk minimization.
References






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