Candidate Drug Discovery
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.
AI Platform Functions
literatures, patents and
other latest medical
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AI Platform Capabilities
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.
Advanced algorithms and
statistical models used to
Analyze the structural
numerous drug targets
and small molecule drugs
Greatly reduce the
inefficiency and number
of the design-test cycles
in the lab
Automatic Design Ability
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.
Efficient AI Applications
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