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Artificial intelligence applied to clinical and microbiological data can make a tangible contribution to the fight against antibiotic resistance. This observation is confirmed by a research study coordinated by IDI-IRCCS in Rome and conducted in collaboration with Kelyon, an EHTEL member.

Several other Italian institutions including Italy’s national research council, the CNR, and two universities are involved in the study. It is a response to one of the most significant public health emergencies worldwide – as shown by the WHO’s 2025 report. The work is a fascinating example of the advances and innovations to be made when companies and academic institutions collaborate.

What was this innovative research about?

The research demonstrates that it is possible to predict antibiotic susceptibility with high accuracy through machine learning models trained on clinical and microbiological data collected in everyday hospital practice. The study involved nearly 10,000 patients in Italy. It analysed 15,000+ bacterial isolates from almost 1,000 patients treated between 2018 and 2024 in two Italian hospitals.

The results show that the models developed are able to produce a digital antibiogram – a laboratory test that analyses antibiotic effectiveness – with an accuracy of over 90%. They can anticipate by at least 48 hours the time required to obtain a standard antibiogram. In clinical settings – where timely therapeutic decisions can have a decisive impact on patient outcomes, length of hospital stay, and the appropriate use of antibiotics – this accuracy and speed represent a particularly relevant advantage.

A full report on the research is published in the International Journal of Infectious Diseases.

What is AntiMO?

Against this backdrop, Kelyon – an AI company that works closely with the pharma industry – confirms its commitment to develop advanced digital solutions to support healthcare professionals, and enable a more effective, personalised and data-driven management of bacterial infections.

The company’s experience in digital health and decision support systems is also reflected in the research and development pathway of AntiMO. This solution is designed to optimise infection management, monitor resistance trends, and counter antimicrobial resistance through predictive tools, advanced dashboards, and support for prescribing appropriateness. AntiMO’s key results have been reported in the Italian daily press and regular health and medical news magazines and newsletters.

“This study represents an important step forward because it highlights the tangible value of data and artificial intelligence in improving the fight against antimicrobial resistance and the management of bacterial resistance,” said Stefano Tagliaferri, Chief Technology Officer of Kelyon.

What is Kelyon’s involvement with digital and data?

The study’s aim is not to replace clinicians, but to provide them with faster, more accurate tools that can be integrated into everyday practice and support more timely and informed therapeutic decisions. From this perspective, research helps build increasingly effective models to address a problem that has a direct impact on the quality of care, clinical outcomes, and the sustainability of healthcare systems. The study is part of a line of research aimed at combining personalised medicine, microbiology and digital technologies to make antimicrobial stewardship strategies more effective.

“For Kelyon, contributing to this study confirms the strategic importance of collaboration between clinical research, scientific institutions, and technological innovation in transforming data into practical tools to support medical practice,” added Gaetano Cafiero, Kelyon’s Chief Executive Officer.

The study was based on the same principles which lie behind AntiMO: developing digital solutions capable of integrating artificial intelligence, microbiological data and real-time clinical information to support increasingly timely, reliable and personalised therapeutic decisions.

Kelyon’s goal is to contribute to a new generation of clinical decision support systems, capable of enabling precision antimicrobial therapies and strengthening the fight against antibiotic resistance.

EHTEL looks keenly forward to hearing more about Kelyon’s, and other EHTEL members and friends, experiences and good practices.

For further information

• Kelyon
• AntiMO
• “Investigating Infection and Clinical Data to Predict Effective Antibiotic Therapy and Monitor Resistance Trends”
• WHO – “Global antibiotic resistance surveillance report 2025”
• Kelyon has worked on several other AI-related projects and has had award-related successes. See e.g.,  AI2MED, AboutPharma Digital Awards