Good Pharmacovigilance Practices (GVP) to Address Adverse Events

According to the FDA, pharmacovigilance refers to the activities related to detecting, assessing, and understanding drug adverse events to reduce their frequency and severity. From a broader perspective, pharmacovigilance also encompasses the study of drug interactions, abuse and misuse of medicines, counterfeit medicinal products, dosage errors, and lack of efficiency. In this article, we outline certain Good Pharmacovigilance Practices (GVP) that allow pharmaceutical manufacturers to meet the expectations of regulatory bodies.

Case Reports are the Basis of Good Pharmacovigilance Practice

Spontaneous reports, clinical studies, and medical literature are useful to identify potential adverse effects of drugs. A good pharmacovigilance practice is to make a complete case assessment and recommend partnering with trained healthcare professionals to interview reporters.

Good pharmacovigilance Practices rely on high-quality case reports, which should include:

• Description of the adverse event, including time to onset of symptoms.

• Suspected product(s) details (i.e., dose, lot number, schedule, dates, duration), including over-the-counter medications, dietary supplements, and recently discontinued medications.

• Patient characteristics, including demographic information,  medical conditions, medications, family history of disease, and risk factors.

• Documentation of the diagnosis of the events, including the diagnosis process.

• The clinical course of the event and patient outcomes.

• Relevant therapeutic measures and laboratory data before, during, and after therapy.

• Other information relevant to the case.

Once multiple case reports indicate potential adverse effects, they are compiled into a case series for further evaluation. This involves reviewing all available cases, removing duplicates, and assessing factors such as:

• Patient demographics.

• Exposure duration.

• Time to onset of symptoms.

• Dosage.

• Use of concomitant medications.

• Comorbid conditions, particularly if they relate to the adverse event.

• Route of administration.

• Product information such as lot number.

• Frequency of case reports over time

Leveraging Data Mining to Identify Adverse Events

The FDA has pointed out Data Mining as another tool to achieve good pharmacovigilance. Data mining can ease the identification of potential adverse event cases, and assess patterns, time trends, and events associated with drug-drug interactions. That being said, data mining on its own is not a tool for establishing causal attributions between a particular medication and suspected adverse events.

While data mining results are not required to identify and evaluate adverse events, they can enrich reports if they are presented within a larger clinical data context. 

Categorizing Potential Risks

A safety signal is the determination of a potential adverse effect resulting from analyzing case reports and other data. Manufacturers should classify safety signals in order to track and address them. Some examples of safety signals are:

• New adverse events.

• Previously identified adverse events which have increased in severity.

• New adverse interaction.

• At-risk population.

• Unclear medication name, labeling, and packaging.

• Product misuse.

• Concerts arising from an implemented risk mitigation plan.

Regulatory agencies and drug sponsors must weigh the benefits of the drug against potential risks to determine whether further action is needed.

Recommendations for manufacturers to successfully adhere to GVP

To adhere to GVP, manufacturers can build a robust pharmacovigilance system by designating a qualified person, developing Standard Operating Procedures (SOPs), and setting an Adverse Event (AE) reporting system. This system must:

• Ensure that adverse events are reported following regulatory timelines. 

• Maintain thorough and accurate documentation of all pharmacovigilance activities, including adverse event reports, risk management activities, and communications with the regulatory agency.

• Implement and use advanced tools and data mining to identify potential safety signals.

• Review ongoing risk assessment and signal prioritization based on factors such as severity, frequency, and the potential impact on public health.

To address potential adverse drug events, manufacturers should also make a pharmacovigilance plan that monitors risks and addresses concerns. A robust pharmacovigilance plan includes:

• A clear, expedited approach to reporting that promotes the prompt submission of adverse event reports to regulatory agencies.

• Active surveillance, through systematic efforts to collect and analyze adverse event case reports and their data.

• Risk minimization strategies through actions such as modifying drug labels, issuing safety communications, or implementing restricted distribution programs.

In addition, manufacturers should seek continuous improvement by training and educating all employees involved in pharmacovigilance. This push should include internal audits evaluating pharmacovigilance practices and the fulfillment of regulatory requirements. Aside from internal review findings, pharmaceutical companies should also apply the feedback from regulatory inspections, external audits, and application comments to improve their manufacturing practices.

By constantly working on GVP, manufacturers can mitigate the risks associated with their products as well as help build a more robust healthcare system for everyone.