Our Mission
Our mission is to create an expansive, AI-driven knowledge platform, meticulously crafted from diverse, publicly available datasets with goal of revolutionizing patient care and safety.
What is medicX?
medicX is a groundbreaking digital platform blending healthcare and technology to revolutionize access to medical information. Utilizing AI, it offers healthcare professionals accurate, current, and clear insights into medicines and drug interactions, enhancing patient care and safety.
medicX Preview (coming soon)
The research and development of medicX is an ongoing innovation endevour. In this initial release, we've integrated data from several pharmaceutical data sources into our own knowledge framework. Additionally, we offer an advanced drug drug interaction service, enabling the clear and precise identification of interactions between multiple drugs.
More Information
medicX started as a research project in 2018 at the Department of Artificial Intelligence within the University of Malta focusing on the use of AI to reduce the problems that might result from polypharmacy.
medicX Knowledge Graph
medicX leverages on the curation and provision of extensive medical knowledge, meticulously harvested from a multitude of publicly available data sources. The Knowledge Graph transforms how healthcare information is accessed and utilized, enabling a deeper understanding of drug related knowledge.
AI-driven Services
medicX is revolutionizing healthcare with AI-driven solutions, harnessing the power of machine learning and knowledge graphs to deliver advanced, personalized medical insights. Our technology empowers healthcare professionals to make more informed decisions, enhancing patient care and advancing the future of medicine
medicX Facts
medicX through numbers
Medicinal Products
Active Ingredients
Drug-Drug Interactions
Adverse Drug Events
Publications
In this paper, we propose medicX, a system that can detect DDIs in biomedical texts by leveraging on different machine learning techniques. The main components within medicX are the Drug Named Entity Recognition (DNER) component and the DDI Identification component.
Lizzy Farrugia, Charlie Abela
In this paper, we propose the medicX end-to-end framework that integrates several drug features from public drug repositories into a KG and embeds the nodes in the graph using various translation, factorisation and Neural Network (NN) based KG Embedding (KGE) methods. Ultimately, we use a Machine Learning (ML) algorithm that predicts unknown DDIs
Lizzy Farrugia, Lilian M. Azzopardi, Jeremy Debattista and Charlie Abela
This paper presents the development of the medicX-KG knowledge graph, that is tailored to the pharmaceutical landscape. Our KG serves as a centralised resource, integrating data from multiple authoritative sources, including information from DrugBank, PubChem and the British National Formulary (BNF). Furthermore, individual countries provide medicine-related information that is more specific to that country through the relevant Medicines Authority (or Agency).
Lizzy Farrugia, Lilian M. Azzopardi, Jeremy Debattista and Charlie Abela
Journal of Biomedical Semantics, 2025
Latest News
8th Annual Rare Disease Colloqium
We presented how the medicX approach can be used for drug repurposing during this annaul colloqium held in June 2023.
University of Malta research Expo 2023
We presented medicX during the 1st University of Malta research Expo. This was an important occasion where we discussed our research with several interested parties.
MedTech World 2022
The medicX team had the opportunity to present during the event as well as exhibit a poster at the Med-Tech World Summit 2022.
Team
Meet the medicX team
Charlie Abela
Principal Investigator Expert in Knowledge Graphs and AI
Lilian Azzopardi
Expert in Pharmacy
Lizzy Farrugia
Research Support Officer