Updated on 3 September 2026
Expert Systems in the field of Health
Project Manager at Ergobyte Informatics S.A.
Thessaloniki, Greece
About
1. Clinical Decision Support System
Ergobyte has developed an AI-powered service that offers explainable, legally sound medication decision support in real time. The system recommends suitable medications based on patient’s medical conditions and cross-checks them for adverse reactions. It is able to check drug-to-drug and drug-to-disease interactions, suggested medications per disease, detailed treatment posology and relevant advisories in order to produce personalized medical recommendations.
The CDSS works on a knowledge base where all the useful information is stored. Medical rules are created taking into account recent literature and official Summary of Product Characteristics (SmPC) documents. Applicable medication treatments are selected by active ingredient and then adapted to the market’s brand names and specific package concentrations.
Its key features are the following:
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Rich knowledge base of: 25.000+ rules (based on EMA & FDA marketing authorisations), 2.900 active ingredients, 7.600 package inserts (SmPCs), 40.500 international brand names
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Best-in-class medication safety checks (drug-to-drug/-disease/-food), with high value in cases of polypharmacy and multimorbidity
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Adaptability to specific cases, e.g. psychiatry, palliative care, ICU, rehabilitation, patient adherence
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Service accessible via web/mobile/APIs
2. Workflow automation
With its workflow automation component, Ergobyte employs Business Process Modeling Notation (BPMN), an open, well-accepted industry standard, enhances it with custom-built modules that use machine learning to adapt decisions, and couples it with openEHR, an open standard for the structuring of data in electronic health records.
The system addresses a wide range of needs arising within a healthcare or social facility, such as ward management, therapeutic protocols, nursing care plans, call center flowcharts, etc. Any procedure can be formalized into executable diagrams, with benefits stemming from pervasive decision support and implementation transparency.
Topic
- Healthcare innovations: HORIZON-HLTH-2027-01-CARE-02 Personalised approaches to reduce risks from Adverse Drug Reactions due to administration of multiple medications
- Clinical trials: HORIZON-MISS-2027-02-CANCER-03 Phase 1 including first-in-human clinical trials to test biomarker-guided medicines or multi-modal treatment interventions for patients with rare or very rare cancers or cancer subtypes
- Clinical trials: HORIZON-HLTH-2027-01-DISEASE-10 Prevention and management of chronic non-communicable diseases in children and young people (GACD)
- Digital health and AI: HORIZON-HLTH-2027-03-TOOL-04 Virtual Human Twins (VHTs) for integrated clinical decision support in prevention and diagnosis
- Digital health and AI: HORIZON-HLTH-2027-03-TOOL-08 Towards Artificial General Intelligence (AGI) for healthcare
Type
- Partner seeks Consortium/Coordinator
Organisation
Similar opportunities
Project cooperation
(CANCER-03) GMP manufacturing and first-in-human trial delivery for rare-cancer therapeutics
- Partner seeks Consortium/Coordinator
- Clinical trials: HORIZON-MISS-2027-02-CANCER-03 Phase 1 including first-in-human clinical trials to test biomarker-guided medicines or multi-modal treatment interventions for patients with rare or very rare cancers or cancer subtypes
Ilias Nikolinakos
EU Grants and Funding Coordinator at Elpen Pharmaceutical Co. Inc.
Athens, Greece
Project cooperation
- Partner seeks Consortium/Coordinator
- Clinical trials: HORIZON-HLTH-2027-02-DISEASE-01-two-stage Innovative healthcare interventions for non-communicable diseases
- Digital health and AI: HORIZON-HLTH-2027-03-TOOL-04 Virtual Human Twins (VHTs) for integrated clinical decision support in prevention and diagnosis
- Healthcare innovations: HORIZON-HLTH-2027-01-CARE-02 Personalised approaches to reduce risks from Adverse Drug Reactions due to administration of multiple medications
- Digital health and AI: HORIZON-HLTH-2027-02-TOOL-01-two-stage Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
Kai Gand
Grants Manager at Corsano Health
The Hague, Netherlands
Project cooperation
In silico combinatorial therapy ranking
- Partner seeks Consortium/Coordinator
- Healthcare innovations: HORIZON-MISS-2027-02-CANCER-01 Leveraging functional genomics to reveal novel targets for cancer treatment
- Digital health and AI: HORIZON-HLTH-2027-03-TOOL-04 Virtual Human Twins (VHTs) for integrated clinical decision support in prevention and diagnosis
- Healthcare innovations: HORIZON-HLTH-2027-01-CARE-02 Personalised approaches to reduce risks from Adverse Drug Reactions due to administration of multiple medications
- Healthcare innovations: HORIZON-MISS-2027-02-CANCER-05 Pre-commercial procurement of affordable solutions for healthcare systems in the areas of cancer technologies, cancer medical devices, or cancer medicines
- Healthcare innovations: HORIZON-MISS-2027-02-CANCER-04 Improving equitable health outcomes and added value for and with cancer patients through health-economics research, health systems research and outcomes research
- Clinical trials: HORIZON-MISS-2027-02-CANCER-03 Phase 1 including first-in-human clinical trials to test biomarker-guided medicines or multi-modal treatment interventions for patients with rare or very rare cancers or cancer subtypes
Egils Stalidzans
Tenured professor at Rīga Stradiņš University
Riga, Latvia