PhD Scientific Days 2025

Poster Session I. - F: Pharmaceutical Sciences and Health Technologies

In Silico Pharmacovigilance: from Individual Case Safety Reports to Drug Safety Networks

Előadó neve

Mr. Csernák Áron Márk

Neptun code

B0M0PS

Előadó munkahelye

Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary

Előadó telefonszáma

+36301860435

Előadó e-mail címe

csernak.aron@stud.semmelweis.hu

Az előadás címe

In Silico Pharmacovigilance: from Individual Case Safety Reports to Drug Safety Networks

Szerző(k) neve és munkahelye

Áron Márk Csernák^1,2, Mátyás Pétervári^1,2,3, Olivér Márton Balogh^1,2, István Szepesi-Nagy^1,2, Maurizio Sessa⁴, Péter Ferdinandy^1,2,5, Bence Károly Ágg^1,2,5

1: Cardiometabolic and HUN-REN-SU System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary
2: Center for Pharmacology and Drug Research & Development, Semmelweis University, Budapest, Hungary
3: Sanovigado Kft, Budapest, Hungary
4: Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
5: Pharmahungary Group, Szeged, Hungary

Bemutatás módja

Poszter

Szekció

Poster Session I. - F: Pharmaceutical Sciences and Health Technologies

Language of the presentation

English

Preferred session

Pharmaceutical Sciences and Health Technologies

Összefoglaló szövege

Introduction: Network analysis of real-world drug safety databases is a need yet to be met, even though networks have already emerged as the pinnacle of analytical frameworks in several other fields.

Aims: Our goal is to perform a network analysis on a drug safety database to describe its topological features, clustering possibilities and evaluate approaches for filtering.

Methods: Spontaneous individual case safety reports (ICSR) were obtained from the FDA Adverse Event Reporting System (FAERS), and an undirected network, containing adverse event and drug nodes, was built by our previously developed software. After coding to standardized terminologies, the network topology was assessed by canonical measures (e.g. distribution of node degree, edge weight), clusters were identified by multiple algorithms (e.g. Ensemble Graph Clustering [ECG], Louvain), while different filters were applied (e.g. drug role, seriousness).

Result: 10,512,493 ICSRs were obtained from FAERS dating from Q1 2013 to Q2 2023. The full, unfiltered network contained 39,686 nodes and 15,112,391 edges, while the most rigorous filtering reduced the network to 9,279 nodes and 1,120,930 edges. Node degree followed a surprising stretched-exponential distribution, indicating sublinear preferential attachment. ECG identified 18 clusters, revealing drug classes or adverse events with distinct patterns.

Conclusion: We described topological features of a drug safety network with different quality filters applied, that combined with clustering, revealed well-known medical connections and new, emerging safety concerns. This demonstrates the potential of in silico methods in pharmacovigilance, facilitating novel efforts to improve the safe use of drugs.

Funding: Project No. RRF-2.3.1-21-2022-00003 has been implemented with the support provided by the European Commission, European Union. This project has received funding from the HUN-REN Hungarian Research Network. O.M.B. was supported by the Semmelweis 250+ Excellence Fellowship and the EKÖP-2024-23 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund.

University

Semmelweis University

Supervisor

Olivér M. Balogh MSc, Bence K. Ágg MD PhD

Publication of my abstract

I do not give consent to the publication of my abstract on the website of the congress.

phd.section.field

before finishing undergraduate studies (TDK, MD-PhD)

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

9055

Start

16:36

End

16:42