Leveraging Pharmacovigilance Data Mining with “The Patient” in Mind

Through decades of spontaneous adverse drug event mining, the largest global database has accumulated more than 20 million individual case safety reports (ICSRs), providing the World Health Organization with the ability to actively generate signals using validated algorithms. With this maturity of Pharmacovigilance, ensuring” the patient” is the focus of the process is critical. ICSRs are flawed by not only under-reporting, but lack capture of patient specific factors which current evidence confirm association with negative pharmacological outcomes. The realization that genetic and ethnic differences in drug metabolising enzymes may be more relevant than previously perceived, the impact of patient adherence factors on adverse event outcomes, the unwillingness of patients accepting dependence on medication for life are just a few examples that have not been adequately documented in adverse event occurrences. There is therefore a need to examine the significance of enriching the pharmacovigilance process with more patient factors.

The specific aim of this research topic is to explore the need to integrate more patient specific factors in the ICSRs collection process. This will be achieved with articles that focus on relationships of adverse outcome of drug therapy with these factors. Articles can examine any aspect of pharmacovigilance; that is, detection, assessment, understanding, and prevention. The articles should highlight data that would not normally form part the current databases, for example, biomarkers, genetic profiles, sociological factors, such as culture and religion.

Priority consideration will be given to articles which highlight aspects of Pharmacovigilance research appropriate to the following themes:

• Pill burden & Medication adherence
• Pharmacogenetics/Toxicogenetics associations
• Integration of Biomarkers
• Maximizing small dataset: the underrepresent patients (children, ethnic minorities)
• Repositioning Real World Data Sources (social media chatter, EHealth tools, YouTube, Influence of patient religious and cultural beliefs).

All paper types are eligible; patient case reports must be of adverse drug reactions and should support the concept of adding patient specific factors to the reporting process.

Topic editor Maribel Salas is employed by Daiichi Sankyo. All other Topic Editors declare no competing interests with regards to the Research Topic subject.