Around 80% of cancers occur because of genetic variants in one's genome. If we can find certain inhibitors that will stop these genetic variants from happening, cancer can become obsolete.
Using sequence deep learning models and historical data on genetic variants and inhibitors, we will train a model to create new inhibitors that will stop all genetic variants from occuring.
Cancer will become a thing of the past. Millions of people will be saved and be able to contribute back to society. We will also get a deeper understanding of how the human genome works.
Using automated web-scraping systems, Zelus creates a comprehensive dataset of millions of vaccine candidate compounds and their molecular properties.
With cutting-edge machine learning (ML) models designed to find complex features in complex data, compounds are narrowed and tested down to a single candidate.
Zelus engineers the future by developing and releasing the first ever effective cancer prevention vaccine - all brought to life in under 5 years.
By validating our process with our MVP, we will be able to conduct more research with ML technologies to find the universal vaccine.