what is

smart molecule ai?

Smart Molecule AI uses artificial intelligence and machine learning to significantly reduce drug development time. Our system is designed to analyze hundreds of millions of drug candidates and narrow down the candidate space by assessing relevant biochemical properties, powered by our higher performance models and scientific biochemical calculations.

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.

our goals

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.

early success

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.

see features

Smart Molecule AI Features

Predictive Modeling

Ability to predict if a compound exhibits toxicity (12+ cytotoxicity metrics), binding affinity on receptors of interest, prodrug-like properties

Compound Clustering

Grouping and reducing the overall candidate testing space (cost savings); Ranking compounds by prioritizing the most desirable candidates for testing (time savings)

Compound Modification

Providing the ability for users to modify compound structures on the fly and compare compound properties

Auto-Generation

Automatically generate completely novel compounds with desired properties based on compound similarity or by specifying substructural features

Smart Molecule AI Continuous Learning Process

Step 1

Model Training
Using known data sets and assay testing results

Step 2

Predictions
‍Compound property predictions from trained models and calculations

Step 3

Reduced Testing Space
Through user-enabled compound clustering and ranking

Step 4

Assay Testing
‍Using reduced testing space where results are fed back into the models

case study

molecule AI

Cognistx's solution allows Kroll to proactively detect the occurrence and mitigate the severity of data breaches for it's clients. Using machine learning to scan and extract meaningful information from Deep Dark Web (DDW) data, the tool prevents data losses from escalating into major events.

Analytical Objectives:

Deep Dark Web Classification and Junk Filtering
Breach Detection and Loss Mitigation
Manual Task Reduction

By integrating Kroll’s investigative expertise with cutting-edge AI and machine learning from Cognistx, Kroll is able to help organizations better understand and address their data’s exposure on the DDW. As the tool continues to refine the model and methodologies, we will be able to help organizations proactively detect data loss and prevent those data losses from escalating into major events that can harm their operations, finances and reputations for years to come. Read more about the Kroll/Cognistx solution.

$1M+

records analyzed/day

22M+

files analyzed

2M+

credit cards tracked

60%

analysts time saved/day

Can Smart Molecule AI Help Your Business?

request a demo

If you'd like to see Smart Molecule AI in action, please use the form to request a demo or learn more about how our AI products can power your business.

Or if you'd like to schedule an appointment to discuss how Smart Molecule AI can help your organization, click here.

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