Pharmacovigilance focuses on drug quality, medication errors and adverse drug reactions which impact the health care system by affecting a significant patient population.
WHO defines pharmacovigilance as “the science and activities relating to the detection, assessment, understanding, and prevention of adverse effects or any other medicine-related problem”
Ultimately, pharmacovigilance is regarded as the constant process of identifying the safe use of pharmaceutical products and helps in minimizing the risk of any harm that may come to patients. Pharma Companies must conduct a comprehensive drug safety and pharmacovigilance audit to assess their compliance with worldwide laws, regulations, and FDA guidance. Below are a few challenges to Pharmacovigilance.
Inconsistent reporting of Adverse events
The occurrence of an adverse event is not always during a visit to the Healthcare Center. It can occur after several hours of administering the drug. Patients fail to remember all the relevant information about the adverse events and are not able to report it accurately.
Patients are anxious and report all their discomfort as adverse events. Adverse drug events (ADE) reported are not always serious and may be symptoms of a disease. Other incidents where a patient has not followed instructions during medication or patient has had side effects caused by concomitant medicines taken along with the study drug could be reported as adverse events. Such wrong reporting can lead to drug safety committees to incorrect conclusions which in turn lead to the suspension or withdrawal of drugs.
The Adverse drug event study by Tufts University in Sep. 2015 indicates the following:
- 40% of HCP’s have never reported an ADE
- 60% of HCP’s report it is difficult to determine if the drug has caused the ADE
Challenges in Spontaneous reporting
Adverse events can be reported voluntarily by the patient, companies, or the HCP. The major drawback of the system is the under-reporting of adverse events to the post-marketing databases. The medical staff does not prioritize reporting and may neglect symptoms that are not serious.
Data analysis may produce more signals than that can be analyzed from the available resources. The adverse event workload has been rising to more than 50% yearly in a few companies. This might delay the focus on potential serious adverse events requiring immediate action.
Another concern is the misreporting and miscoding of adverse events. The fields in reports about dosage, formulation type, time and length of exposure to adverse events are not clearly reported and coded leading to challenges in managing and analyzing the data.
This also leads to the generation of false alarms for non-existent adverse events. HCP’s generally select treatments based on their own practice preferences also the inadequately adjusted algorithms could produce errant false signals. Inadequate analysis of such signals may lead to early refusal of useful drugs.
Priority of efficacy over safety
Smaller drug companies may prioritize efficacy over safety in clinical trials leading to a compromise in drug quality. The signal detection is not utilized by few sponsors to detect and effectively solve the issues in a timely manner. Drug development relies on balancing efficacy and safety equally.
Limitations in Published case reports
Reports in medical journals about the suspected adverse effects are an established way to alert about drug hazards. These reports are one of the signal generating reports easily accessible by the general population. Limitations in these include:
- A small number of cases are published.
- Reports are poorly documented.
- Delay in occurrence and publication of adverse events.
Analysis of Electronic health records (EHR)
EHR provides a great wealth of information about real time and real world medication usage. A few limitations include the unstructured narrative information that is complicated to analyze. There may be few cases in EHR to analyze a particular drug but more number of cases are required to generate a signal. Another challenge is the lack of access to medical records due to patient privacy systems.
Integration between the various systems such as the clinical trial management system (CTMS), clinical data management system (CDMS), product performance system, clinical coding application, and CRO systems is crucial for pooled data analysis. Standardizing the medical domains, signal definitions, adverse events, and medical coding ensure quality in signal analysis. Standardization is a challenge as there is no standard framework to allow system integration. Though the default file format XML is agreed it is not implemented. Thus clinical data is collected by the current sponsor in separate EDC or via paper-based case report forms.
Apart from the limitations listed above one of the major roadblocks for conducting effective PV is the increasing amount of unstructured information originating from several sources.
The growing complexity in Pharmacovigilance services is leading to outsourcing of PV as a whole or part of it. Pharma industry is still leveraging 10+ years old legacy systems to monitor safety and drug misuse. The technical advancement such as Cloud-based solutions, Mobile health devices, Artificial Intelligence, Blockchain, and Machine learning will not only improve the effectiveness of PV but also helps us improve the efficacy of drugs.
By Mythri Raghunandan