About the Institution

Di Venere Hospital, located in Carbonara di Bari in southern Italy, is a regional medical centre offering a broad range of healthcare services. The hospital has developed a specialised programme focused on the diagnosis of rare genetic disorders, serving patients who often arrive after years of inconclusive testing and unanswered questions.

The Challenge

Genetic testing generates enormous volumes of data. For the clinical genetics team at Di Venere, the challenge was never the testing itself, it was what came after. A clinician could easily spend hours reviewing more than 100 variants for a single patient, searching manually for the markers that might explain a disease. That kind of workload is not sustainable as case volumes grow, making it challenging to work at the pace patients need.

What the team needed was a platform that could keep pace with their clinical workload while maintaining the rigour their work required. 

Finding eVai

Dr. Romina Ficarella, senior medical geneticist at Di Venere, first encountered eVai at a conference organised by the Italian Society of Human Genetics. The demo was immediate and convincing.

What stood out was not just the speed, but the approach. eVai's ability to rank variants by pathogenicity score - the likelihood of causing disease - matched exactly how the team wanted to work. The platform's AI-driven prioritisation did not simply filter data; it reasoned through it, surfacing the most clinically relevant findings and significantly reducing the manual workload.

The relationship with enGenome was also a natural fit. As Dr. Ficarella put it, the two organisations shared a belief: that genetic testing, done well, should relieve uncertainty - not add to it.

The Results

The impact of implementing eVai at Di Venere was felt immediately and across the entire workflow.

The time required to review variants for a single patient dropped from approximately 50 hours to just a few hours - a transformation that freed clinicians to focus on interpretation and patient care rather than data processing. In the two years following implementation, the hospital increased its patient testing throughput tenfold.

A Case That Stayed with the Team

Behind the numbers is a story that illustrates what these changes mean in practice.

A patient had spent more than eight years seeking answers. He had seen multiple doctors, undergone numerous tests, and together with his wife lived with the anxiety of not knowing what was wrong or whether it could be passed on to their children.

Using eVai, the team was able to quickly identify the cause: retinitis pigmentosa. The diagnosis was recessive, meaning the couple could be reassured that the condition would not be inherited by their children.

"No patient should have to suffer with uncertainty for years. Using enGenome, we can relieve uncertainty. It's not a game changer - it's a life changer." — Dr. Romina Ficarella, Senior Medical Geneticist, Di Venere Hospital

Key Takeaways

• Variant review time reduced from approximately 50 hours to a few hours per patient
• Tenfold increase in patient testing throughput within two years of implementation
• AI-driven prioritisation aligned naturally with the team's existing clinical workflow
• eVai surfaced clinically relevant findings that manual review alone would have taken significantly longer to identify