Pharmacovigilance is essential for monitoring adverse drug reactions (ADRs) and ensuring the safety of medicinal products. Traditional methods of data analysis in pharmacovigilance can be limited in handling complex relationships between drugs and ADRs. Graph theory, a branch of mathematics concerned with the properties of graphs, offers a promising alternative approach.

This presentation aims to explore the general application of graph theory in pharmacovigilance, particularly in understanding complex drug-ADR relationships and enhancing the effectiveness of drug safety surveillance systems.

We utilized graph theory to construct and analyze networks of drug-ADR interactions. Data was gathered from pharmacovigilance databases, focusing on reported ADRs and their associated medicinal products. The networks were analyzed using various graph theory metrics such as connectivity, centrality, and community structure to identify significant patterns and relationships.

The application of graph theory facilitated the visualization and analysis of complex relationships in pharmacovigilance data. It revealed additional insights into the interconnected nature of drugs and reported ADRs, identifying key nodes (drugs and ADRs) that play critical roles in the network. This method also helped in detecting clusters of ADRs associated with specific drugs, which might not be evident through traditional pharmacovigilance methods.

Graph theory offers a valuable tool for the analysis of pharmacovigilance data, providing a deeper understanding of drug-ADR interactions. Its ability to represent and analyze complex relationships in a comprehensive manner can enhance the detection and evaluation of drug safety issues. The insights gained from this approach could lead to more effective strategies for managing drug-related risks and improving patient safety.

Peter brings over two decades of extensive experience in life sciences, specializing in pharmacovigilance (PV) and clinical trials. With a background as a Medical Doctor and Medical Computer Scientist, he has collaborated with various clients, including top pharmaceutical firms and health authorities.

His primary focus lies in introducing innovative technologies to advance drug safety assessment and monitoring. His expertise centers on developing analytical approaches for automated interpretation of safety signals, contributing significantly to the field.

In his current role as Senior Director of Innovation Lab & PV Products, Peter leads efforts to integrate emerging technologies into pharmacovigilance practices. His dedication to scientific rigor and practical application continues to shape advancements in PV product research.