Scientists from MedAI use AI technologies to transform the way medicines are discovered, developed, tested and brought to market. Our platform integrates AI strategies at every step of the drug discovery process. This very quickly jumps programs ahead – to the lead design and optimization stage, within a matter of months, not years. The important goal for early drug discovery is to design candidate molecules that can selectively bind to a certain target using artificial intelligence platform.
Academic conferences, literatures, patents and other latest medical information
Advanced algorithms and statistical models used to perform candidate screening
Analyze the structural characteristics of numerous drug targets and small molecule drugs
Greatly reduce the inefficiency and number of the design-test cycles in the lab
Artificial intelligence can extract a large number of key information about compounds, toxicity and effectiveness through the integration of existing compounds database information, data extraction and machine learning, which not only avoids the trial and error path, but also greatly improves the success rate of screening using advanced AI algorithms.
Automatically design millions of small molecular compounds related to specific targets based on existing drug development data, and screen compounds according to efficacy, selectivity, ADME and other conditions. The selected compounds will be synthesized and tested, and then the experimental data will be fed back to the AI system to improve the selection of the next round of compounds.
In the drug screening stage, there are two applications of AI, one is to develop virtual screening technology with deep learning to replace high-throughput screening. The other is to optimize the high-throughput screening process with AI image recognition technology. MedAI’s AI team can perform both virtual screening and image recognition on compounds to improve the speed and success rate of candidate drug discovery.
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