Life-saving drugs. Faster.
AI-driven drug development means we dramatically shorten long R&D cycles, getting life-saving drugs to patients faster.
AI for Drug Discovery
What is Deep Drug?
Deep Drug is an AI-based platform that is being used to tackle global challenges. The Deep Drug team has been working on the AI for Drug Discovery for drug resistant pathogens for 8 years and had advanced into the semi-final of the IBM Watson AI XPrize competition among 142 teams worldwide.
Skymount Medical is the commercialization partner of Louisiana State University’s renowned Deep Drug AI platform. Deep Drug is an advanced drug discovery system that performs the work of 60-person years per day, greatly reducing the manual labor hours to generate new target molecules from existing, pre-approved drugs.
What is Rapid Drug Discovery?
The Deep Drug platform uses several key components to deliver a state-of-the-art compound and formula generation capability that greatly reduces the time and cost associated with a lengthy drug discovery research process. Our Pharmacology Working Group is comprised of world class virologists, pharmacologists and toxicologists, as well as computer scientists and former defense personnel.
Artificial intelligence helps map known antiviral peptides (AVPs) to different cell mechanisms by analyzing protein-protein interactions. The AVPs are then ranked by how effectively they can slow the propagation of coronavirus in the human body. (Image credit: LSU Office of Research & Economic Development)
How Deep Drug Works
Treatments to patients faster
The Deep Drug platform is able to identify already FDA-approved antivirals—a practice known as drug repurposing—90% faster, from initial discovery through to market.
Automatically synthesize targeted drug molecules
Deep Drug AI uses graph-based search algorithms combined with machine learning-based filters to automatically synthesize targeted drug molecules and filters candidates based on chemical criteria, such as being an antibiotic, toxicity, etc. By analyzing 3D image models of the pathogen for possible drug repurposing, we automate clinical testing for side effects, and predict candidates that are most likely to succeed.