Smart MoleculeAI involves in-silico testing to help early-stage drug discovery companies reduce significant time and cost to test new molecules.
The development of new pharmaceutical drugs is a risky process. And it requires significant time and money to acquire and test every potential candidate. Typically, it takes pharmaceutical companies 12 years and $1.8 billion in costs to launch a new drug.
To speed up the drug discovery process by narrowing the molecular search space.
Reduction of testing sample space from clustering and predictive modeling, which would reduce overall time and cost.
Develop a generic platform that will accomplish these objectives for psychedelics, cannabis, and cancer drugs.
Using Artificial Intelligence, we have been able to reduce the assay testing space by up to 90%, allowing biopharma clients to focus on targeted molecules with the highest probability of success and save significant time and money.
Ability to predict if a compound exhibits toxicity (12+ cytotoxicity metrics), binding affinity on receptors of interest, prodrug-like properties
Grouping and reducing the overall candidate testing space (cost savings); Ranking compounds by prioritizing the most desirable candidates for testing (time savings)
Providing the ability for users to modify compound structures on the fly and compare compound properties
Automatically generate completely novel compounds with desired properties based on compound similarity or by specifying substructural features
