The first software platform built for fully
automated reanalysis at scale
Clinical guidelines increasingly recommend reanalysis of WES and WGS data, as new genetic insights emerge. But most labs don’t follow through — manual reanalysis is too labor-intensive, too slow, and too expensive.
It’s the first software platform built specifically for fully automated reanalysis of rare disease genomes — at scale, and with clinical-grade accuracy. By effectively turning your archives into answers, Arun enables undiagnosed patients to receive unlimited second chances.
Arun uses advanced language models to mine patient records for relevant clinical information. It automatically builds structured phenotype profiles from reports, notes, or EHR data — no need to manually extract phenotypes or other patient information.
Developed by the award-winning team behind Moon, Arun delivers best-in-class sensitivity and specificity. Due to its accuracy, your team will review 50% less variants than with other solutions*, allowing them to focus on true positive variants with clinical relevance.
*Based on a pilot study at Antwerp University Hospital
Arun is engineered for the genomic era — where WGS is routine. Arun takes only 1 minute to annotate and interpret an exome, and only 5 minutes for a whole genome. That’s at least 100x faster than legacy interpretation tools — with no compromise in accuracy - a new standard in our field.
Arun evaluates its own performance on a case by case basis. Only cases with a high-confidence diagnosis are presented for review. This means your lab can reanalyse thousands of samples regularly — while only spending time on those where the answer has been found.
"In a pilot study performed by our genetic centre, Arun ranked the causal variant in the top 3 in 98.8% of solved cases with 4.8 prioritised variants on average."
Most genome interpretation tools ignore everything outside the coding regions, cutting out large parts of potentially relevant data and leaving you with little more than an expensive exome. Arun is different. It was built to unlock the full power of WGS, providing insights into non-coding, regulatory, and deep intronic variants — so you can detect what others miss.
Despite advances in genetic diagnostics, 60–70% of rare disease patients still receive inconclusive results, leaving centers with vast datasets of undiagnosed cases. Yet with rapidly expanding genomic knowledge, these data hold huge untapped potential. Recent studies show that reanalyzing exome and genome sequencing raises diagnostic yield driven by new gene–disease links, updated variant classifications, better technology, and evolving phenotypes. Guidelines such as ACMG now recommend systematic reanalysis as routine practice, but the burden on labs should be minimized while still maximising clinical impact. That’s where Arun comes in: reanalysis isn’t just a second chance, but a path to more accurate insights, better clinical decisions, and an end to the diagnostic odyssey for many families. Let’s unlock this potential and make sure no genetic story is left untold.
Give undiagnosed patients a second chance