Graphen, a startup specializing in AI systems inspired by full brain functionality, has released its AI gene evolution pathway analysis of COVID-19 as the new coronavirus spreads across the globe.
The company modeled the spread and severity of COVID-19 by analyzing the variants of each reported whole genome sequencing from more than 30 countries and regions to date. Graphen then used the data to identify the virus’ mutations as they spread. Graphen’s AI-driven analytics visualize how the virus propagates, mutates, and spreads throughout the world.
“We are pleased to share that Graphen analyzed the evolution of COVID-19’s virus SARS-CoV-2 with more than 370 strains of viruses from all over the world. Our team worked tirelessly and mapped out the evolution of the virus reported so far. We now have a better understanding of the propagation paths of the epidemic that has broken out around the world since Dec 2019,” said Dr. Ching-Yung Lin, founder and CEO of Graphen.
By understanding the mutation of each virus and locating where those variants are in its nearly 30,000 genetic locations, the virus’ evolution chain and significant clusters can be identified. Those types of mutation and propagation patterns can then help pharmaceutical companies better identify targets for drug development, help predict the spreading speed of the virus, or even help predict the harmfulness of specific variants that may cause symptoms beyond those observed from the original strain.
So far, Graphen’s data has helped identify two super-spreaders—individuals who infect large amounts of people. For example, a virus strain isolated from the confirmed case on January 5, 2020 in Wuhan later appeared in Taiwan, Belgium, and Australia, and has since evolved into the strain of most initial cases in the State of Washington.
“We are continuously working with new data to show inductive analyses and more visualization as well as cross-media information as the virus propagates. What we have now can already provide researchers with references for clinical treatment, medicine and vaccine development,” added Lin. “Finding out the relationship between the sequence changes and the disease epidemic development is very helpful for subsequent prevention and control. This is an example of the future of AI-powered precision medicine.”