Drug blueprints to
treat and cure all
diseases for all
people

POLARIS^qb will use Quantum Computing to search unstructured, exponentially large datasets to explore novel chemical space, and create new drugs. Artificial Intelligence tools, especially Machine Learning (AI/ML) algorithms utilizing Big Data, are used to remove drug toxicity effects. Platform automation and scale will bring the power of these tools to bear on our mission.

The cost of personal genome sequencing is decreasing and is projected to be less than $1,000 per person by 2020. This allows for a better understanding of disease biology, and discovery of more specific disease pathways leading to smaller and more precise patient groups. This Precision Medicine toolbox identifies the proteins that POLARIS^qb will use to create the drug blueprints in our portfolio.

Most drugs are small molecules that have been optimized to manipulate the right biology (alter disease state) without harming the rest of the body. Developing drugs is currently a lengthy (10 years) and expensive (> $1B) process. At POLARIS^qb, automation and scale will significantly shorten and lower the cost of the process. Reducing cost and time to market of our drug candidates enhances the value of our IP portfolio.