A newly developed AI tool can dramatically speed up the search for the genetic causes of rare diseases, a process that often takes years and frequently ends without answers. The tool analyzes how genes have evolved across many species to uncover hidden clues about which gene is responsible for a patient’s symptoms. In tests, it successfully identified the disease-causing gene in most cases, even when that gene had never previously been linked to a disease. This approach could significantly shorten the diagnostic journey and help guide doctors toward effective treatments much sooner.

For families of children living with rare diseases, the search for a diagnosis is often long, uncertain, and deeply exhausting, marked by years of unanswered questions, repeated tests, and the absence of clear medical explanations.

This journey, often called the “diagnostic odyssey,” can last nearly a decade. Even in the age of advanced genetic sequencing, most patients remain undiagnosed, leaving families without clarity, treatment, or closure.

A new study led by Dr. Christina Canavati and Prof. Yuval Tabach from the Faculty of Medicine at the Hebrew University of Jerusalem, published in Genetics in Medicine, may finally change that. It builds on earlier research conducted with Nobel Prize laureate Prof. Gary Ruvkun, published in 2013.

At the heart of the breakthrough is EvORanker, an artificial intelligence algorithm designed to enable identifying which gene, among thousands of possibilities, is actually causing a patient’s disease.

Instead of relying only on existing medical knowledge, EvORanker looks across evolution. By comparing genetic patterns across more than 1,000 species, the algorithm detects hidden relationships between genes, even those that science has never linked to disease before.

In clinical testing, the algorithm identified the correct disease-causing gene as the top candidate in nearly 70% of cases, and placed it within the top five in 95% of cases, outperforming existing tools, especially in the most challenging scenarios involving poorly understood genes.

But beyond the numbers are real patients.

In one case described in the study, a child with a complex neurodevelopmental disorder had undergone extensive testing without a diagnosis. Using EvORanker, researchers identified a previously unrecognized gene as the likely cause, opening the door to understanding the disease and, potentially, treating it.

In another case, the algorithm revealed the genetic basis of a severe multisystem disorder affecting multiple organs. The discovery not only provided answers to the family, but also pointed researchers toward possible therapeutic strategies.

“These are thousands of cases like that around the world that fall through the cracks of current medicine,” said Prof. Tabach. “Our goal was to give patients and clinicians a tool, that can find fast and accurate answers where none existed before.”

The implications go even further. By uncovering new disease genes, EvORanker also helps identify existing drugs that could be repurposed, a shortcut that could save years of development time and bring treatments to patients faster.

The research builds on more than a decade of work combining evolutionary biology and computational science. Earlier discoveries by Prof. Tabach and collaborators demonstrated how genes that evolve together often function together, this leads to dozens breakthrough. EvORanker turns that principle into a powerful and fast diagnostic engine.

And while rare diseases are the immediate focus, the team is already looking ahead. The technology is now being applied to cancer, where researchers are using it to uncover why some tumors unexpectedly regress, and how those mechanisms could be harnessed for treatment of stage 4 cancer patients.

Globally, rare diseases affect up to 5% of the population. In Israel, the burden is even higher, reaching as much as 8%, due in part to genetic factors within certain communities. For these patients and families, faster diagnosis brings renewed hope for treatment.

EvORanker is now available as an accessible tool for researchers and clinicians, with additional studies already underway and new clinical applications emerging.

For families still waiting for answers, tools like EvORanker may help turn years of uncertainty into clearer, faster diagnoses.