Pharmacovigilance processes in low- and middle-income countries: moving from data collection to data analysis and...

The analysis and interpretation of pharmacovigilance data is an essential component of the continuous benefit-risk assessment of authorised medicinal products. Effective pharmacovigilance data analysis starts with data collection and involves critical activities, such as signal detection, that enable the generation of new information on marketed products, and inform safety-related regulatory actions. This real-time pharmacovigilance data analysis, which requires efficient collaboration and exchange of information between the key pharmacovigilance stakeholders, represents a challenge for many low- and middle-income countries (LMIC).Objectives:: To assess the capacity for analysis of pharmacovigilance data in LMIC and to identify mechanisms to strengthen data analysis, interpretation and evidence-based pharmacovigilance decision-making.

We used a convergent parallel mixed-methods study design consisting of qualitative and quantitative methods.

Qualitative and quantitative methods consisted of semi-structured interviews and an online survey, respectively. Quantitative research was complemented by cross-sectional analyses of the number of adverse event reports from LMIC in VigiBase^® from 2019 to 2023.

Nine key informants from eight countries were interviewed and 50 respondents from 34 countries completed the online survey. Four major themes emerged from the data and are proposed as transformative actions to strengthen pharmacovigilance data analysis and interpretation in LMIC: build on existing pharmacovigilance data analysis capacity rather than create new or parallel mechanisms; implement standardised procedures to enable efficient data analysis; augment the work of the safety committees by assigning pharmacovigilance staff to data analysis; and implement mechanisms that allow benefit-risk evaluation and decision-making.

Findings from this research revealed that many LMIC have implemented procedures for reporting and collecting suspected adverse events, but a considerable proportion of the data collected is not analysed in-country due to a lack of requisite knowledge, processes and structures to support such analysis. Establishing the four essential elements proposed by this research will equip LMIC for efficient data analysis, thereby supporting consistent decision-making through pharmacovigilance.