Co-Development

BioTraxx. Learn More About Our Solution.

Deep learning, the most advanced AI technology in recent years has shown remarkable success in many industries. Since drug discovery is such a data intensive task and a tremendous amount of data has been accumulated, we believe that adoption of AI and big data technology can transform pharmaceutical industry. BioTraxx is an integrated platform of Deep learning, big Data and the Domain knowledge. 

Accurate information of drug-target interaction (DTI) is the most critical element of drug discovery. Both the efficacy and safety of a drug depend on it – the affinity to the intended target affects the efficacy and the affinity to other targets (off-targets) is the major underlying cause of side effect or toxicity. The core of the platform is an AI-enhanced model for accurate DTI prediction which integrates deep learning, molecular docking, and molecular dynamics simulations. Our technology is of much higher accuracy compared to existing in silico drug screening methods. The platform is fast and high throughput — able to evaluate millions of DTIs within days.

BioTraxx. Learn More About Our Solution.

We can rapidly identify potential hit compounds for your desired kinase target. Our artificial intelligence-based compound screening system is able to screen millions of compounds within a week. This state-of-the-art deep learning system is trained by abundant experimental data on compound-protein interactions and this neural network model can accurately predict if a compound binds to a protein target.
The development of new drugs is slow and expensive due to the poor safety profiles and limited efficacy of new compounds. Find new uses of approved drugs is a valuable strategy especially for special, timely needs such as the COVID-19 pandemics and personalized medicine in oncology. Our in silico approach to drug repurposing has advantages over traditional slow and inefficient experimental screening methods to response to the urgent request. We can screen all approved and experimental drugs (over 10,000 drugs) against a target protein within a day.
Off-target toxicity is a common mechanism of action of many failed drugs in clinical trials. To be able to identify off-targets for your drug candidates earlier will save tremendous cost and time for the drug discovery and development project. Our platform is designed to predict the off targets of drug candidates by efficiently searching our drug target database to identify all proteins which potentially interact with the drug candidates in focus.
Lead optimization is time consuming and expensive because a large number of compounds have to be designed, synthesized and tested. Using our platform, novel compounds with better binding affinity can be designed in silico through the integration of drug-target binding affinity prediction and AI-based generative model of lead derivatives. The advantages are twofold: the number of compounds to be synthesized can be greatly reduced, and a much wider chemical space can be explored for the optimal leads.

Latest News.

Press Release: How Local Biotech Company Leverages its Deep Learning Platform to Identify Drugs to Treat COVID

Anthony Marotta3 November 20203 min read
Press Release: How Local Biotech Company Leverages its Deep Learning Platform to Identify Drugs to Treat COVID

VANCOUVER, November 3, 2020 / Pharmasilico, the AI-based drug discovery company, is pleased to announce that they have leveraged their proprietary AI platform to identify 22 candidate drugs that could be effective in combating the current global COVID-19 pandemic. Twelve…

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