GGC Reduces Turn Around Time on Genomic Analysis by 75% With Emedgene's AI Platform

09.12.19

Greenwood Genetic Center utilizes Emedgene’s AI to slash turnaround times, improve diagnostic yield and return answers to patients faster. Emedgene’s platform
automates much of the genomic analysis workflow, allowing Greenwood to reduce time-per-test by 75%.

Greenwood Genetic Center is a nonprofit organization advancing the field of medical genetics and caring for families impacted by genetic disease and
birth defects based in South Carolina. The center is actively investing in technology initiatives that faculty have deemed critical to improving
patient care and remaining at the forefront of genomic medicine, with the ultimate goal of increasing diagnostic yield and ending the diagnostic
odyssey for more patients. Their diagnostic lab offers an extensive menu of genetic tests, among others, diagnosing patients served by South Carolina’s
Department of Disabilities and Special Needs.

Analyzing genetic tests, and in particular, exome tests, was a time consuming and labor-intensive effort performed by Greenwood’s highly skilled personnel.
The analysis process required them to review dozens of variants. Specifically challenging was searching for recently discovered gene-disease connections
in databases and the literature. Facing longer turnaround times, Greenwood’s lab directors set out to incorporate advanced technology that would
help prioritize variants, provide access to an up-to-date database of gene-disease associations, and shorten analysis time.

Emedgene’s AI Solves All Test Cases During Evaluation

The team evaluated a dozen genomic analysis platforms according to a stringent set of criteria, and 4 platforms were selected for a performance assessment
on a set of 10 previously solved cases, some of which were intentionally complex. “Emedgene was the only vendor able to automatically solve all
10 cases,” says Julie Jones, PhD, Greenwood’s Clinical Genomic Sequencing Program Director. “Other vendors’ prioritization algorithms were successful
in roughly 30% of cases.”

Emedgene’s interpretable machine learning algorithms provide a short-list of causative variants, along with supporting evidence. The evidence includes
current information curated from the literature using Natural Language Processing, as well as information from databases, animal models and pathways,
providing a comprehensive – yet completely automated – review. “Emedgene’s machine learning simplifies the highly complex task of variant analysis,
allowing us to handle more tests every day,” says Ray Louie, PhD, Assistant Director in the Center’s Molecular Diagnostic Laboratory.

“It’s been a pleasure to collaborate with such an excellent team of scientists, supporting the advanced work they are doing in clinical interpretation,
and constantly pushing the boundaries to meet a higher diagnostic yield. We consider scaling genomic interpretation a key factor in enabling advanced
genomic medicine to patients in need, and have found with Greenwood a true partnership for advancing this goal,” says Einat Metzer, CEO of Emedgene.

About Emedgene:

Emedgene is the world’s first completely automated genetic interpretation platform, using AI to dramatically
scale genetic interpretation. Clinical labs using Emedgene reduce time spent on interpretation and increase yield, and research organizations accelerate
genomic discovery.

Meet Makayla Gunn

Makayla was diagnosed with Rett Syndrome in April of 2015 at the age of two. At about 18 months, we noticed she had started some repetitive hand motions, and her pediatrician was a little concerned that she did not have many words. She had learned some sign language, and was saying ‘mama’ and ‘dada’, but that was it. Then she suddenly stopped all of that. At her 2 year old check-up, the pediatrician referred us to BabyNet, SC’s early interve...

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