Research & Innovation


Innovation Coupons

The research project is about the know-how tranfer of the implementation of data mining and machine learning techniques on Galen Medicines. It is carried out by Infolab, the Laboratory of Informatics in Economic Sciences of Aristotle University of Thessaloniki. The project started on October 2020 and ends in 12 months.

Our overall goal is to apply disruptive technologies on Galen's knowledge base and user log to derive real-time insights of the pharmaceutical market. Upon the completion of the project, Ergobyte will develop a new, innovative product which will be addressed to pharmaceutical companies.

More information are available at the project description.


About the action

The action aims at empowering micro, small and medium-sized enterprises, through the purchase of innovative consulting services and transfer of know-how from recognized innovation institutes, in order to develop innovative products, services or operation processes. The project is co-financed by the European Regional Development Fund (ERDF) of the European Union (ΕΕ), under the action "Innovation Vouchers for small, micro and medium-sized enterprises of the Region of Central Macedonia", under the framework of the Operational Program "Central Macedonia" 2014-2020.

Research Project "Panacea"

Targeting the transition from mere information into knowledge, the project "Panacea" developed an integrated system for management and exploitation of health information at a semantic level. In particular, Ergobyte in collaboration with the Centre for Research & Technology - Hellas (CERTH), built an intelligent recommendation system to effectively propose drug therapies that will support and facilitate health professionals, ensuring faster and safer administration of drugs. For this purpose, Panacea makes use of Semantic Web technologies for the formal representation of the involved knowledge in order to provide automated inference.

For building the knowledge base, part of the medical knowledge was made available after transformations and editing of existing medical data. Furthermore, specially developed interface allows the further enrichment and introduction of new knowledge, while also controlling the overall coherence and consistency of the new knowledge. At the core of the project lies the semantic inference engine, which analyzes requests to the knowledge base and provides relevant suggestions and recommendations. As the volume of the involved knowledge imposes requirements on a large scale, emphasis is given on developing appropriate reasoning methodologies to ensure the efficiency of the system in terms of responsiveness. Finally, a graphical user interface for interaction with the system was developed which applies all the needed semantic transformations in a manner transparent to the user.

By providing an integrated recommendation system for medical content data that supports all stages of development, verification and management of the involved semantic knowledge, the project Panacea provides essential assistance for achieving high levels of care, while promoting interoperability and integration of knowledge.

The project's results are commercially exploited at the RxReasoner medication decision support system.


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