Where The Worlds of Technology and Science Intersect

Applying an analytic framework to genomics

Set a Demo

Where the worlds of Technology and Science Intersect

Applying an analytic framework to genomics

Set a Demo

Advanced Technology Guided by Deep Scientific Context

Emedgene is a next-generation genomics intelligence platform, incorporating the most advanced artificial intelligence technologies to significantly streamline the interpretation and evidence presentation process. Using Emedgene, healthcare providers will be able to provide individualized care to more patients through significantly improved yield.

The Science

The Emedgene research arm is focused on developing new methodologies to identify the clinical impact of different types of variants in both known and unknown genes. With an average of only 30% of cases solved, and high variance in the resolution rate of different genomic interpreting teams, there is a clear need for new and consistent scientific methods. The challenge is even more important when considering that most genes functionality has yet to be discovered, and there are some 4000 genetic diseases with unknown causes.

Our model relies on years of work at the intersection of academic research and clinical care, and brings the vigorous attitude and “know-how” of researchers as they analyze unknown genes, to the practical results required in clinical care.

The Emedgene research arm utilizes advanced machine learning and artificial intelligence technology to generate new insights, which are then reviewed by our scientists in order to find new avenues of research, typically unavailable to the sole researcher or geneticist focused on a single case. As a result, customers using the Emedgene platform, have been able to achieve diagnostic yield as high as 60%.

Some of our developments include:

  • Adding proprietary statistical, biological, and molecular models to gain insights on properties of the various genetic elements.

  • Multifactorial model for analyzing unknown variants and unknown gene influences on clinical symptoms.

  • Determining indirect connections between the different genomic elements, including: variants, genes, diseases, and phenotypes.