As coronavirus has become the new reality for every health worker and life science company to fight in the front, it is time to relook the approach being taken by the industry towards pharmacovigilance. Health agencies around the world are evaluating the impact of the virus, clinical trials, and pharmacovigilance systems. The rapidly changing situation with the outbreak of the virus has compelled agencies to be more vigilant and proactive in determining the effects of the pandemic for better patient care. Pharmacovigilance is detection, assessment, understanding, and prevention of adverse effects of the therapeutic product on the patient. A thorough pharmacovigilance strategy is essential to ensure patient safety and protect the reputation of pharma and medical device companies. Pharmacovigilance is the report card that helps us identify the successful patient care of the medicine post its clinical trial.
During the preparation of a drug, it goes through different clinical tests to get approved for patients. Pharmacovigilance helps in knowing about the adverse effect of the therapeutic product after it has been launched in the market. It is an important part, like clinical trials, for the product lifecycle. Pharmacovigilance involves the collection of a large amount of data and analysing the same for better patient care and adverse effects.
The increasing number of data sources used to identify adverse events (AE): call centres fielding reports from patients and healthcare practitioners (HCPs); safety databases such as ARGUS, ARISg, electronic health records (EHRs); clinical trial data; medical insurance claims; contract research organisations (CROs); post-marketing safety (PMS) studies; scientific literature; regulatory and NGO databases; and legal cases play a major role in pharmacovigilance.
Moreover, the process of finding reportable adverse events in such a plethora of information requires significant manual effort. It is also prone to human error, resulting in missed safety signals, very high skilled labour costs and non-compliance risk. The problem of data explosion worsens when you consider pharma and medical device companies operating in multiple geographies, receiving information about suspected adverse drug reactions (ADRs) in various languages across disparate channels. WHO’s Vigibase which is a global dataset that has all the data on adverse drug reactions from across all the major countries works as a key support system for the healthcare industry. While every country has its way to stop the spread of the virus, the healthcare industry must share the success of clinical trials, new symptoms and effects of the virus.
To put that in perspective, pharmacovigilance staff may have to scan through 144,000 to 240,000 abstracts every year to find the literature of interest, which may require anywhere between 8,000 to 20,000 human hours to execute. Out of those abstracts, 72,000 to 120,000 pieces of literature may be of interest, and then only 3,600 to 9,600 may be reportable. All this review requires close to 30,000 human hours to sort out. Assuming the number of abstracts being collated increases every year by 15 per cent, it becomes apparent that legacy pharmacovigilance workflows and systems need a massive overhaul to ensure organisational efficiency and reduce the cost of compliance. Minimising operating costs is particularly of interest to pharma and medical device industries which have an eye on costs driven by the focus on value-based healthcare, and the dwindling blockbuster drug pipeline, which would, in the past, generate global sales of at least $1 billion annually for companies.
Today, the pharma and medical device industries are driving collaboration among industry participants, HCPs, regulators, patients, and academia for boosting the efficacy and safety of their therapeutic products.
Collaborations can demonstrate the value of real-world data, queries of spontaneous databases combined with real-time observational studies using data from big data networks gathered via these collaborations with other scientific originations can allow for more efficient evidence generation to explore any medicines safety issues. Achieving that requires robust integration and standardisation of data sets, enabling data...
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