

Value Proposition
Proprietary AI Models can address biopharma R&D issues

Platform
We take pride in our AI4D™ platform and comprehensive AI models
AI for Drug Discovery, Design & Development
Discovery
Development
Design

Models
Silexon has 4 various AI models for virtual high-throughput screening and Drug-Target interaction/affinity predictions.
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SILEXON aims at developing practical AIDD models
SILEXON’s solutions for challenges in AIDD
Model designs based on biological and medicinal chemical knowledge
Rich experience and systematic methodologies on biological tasks (including modeling sequences, structures, compounds, omics and network data and related problems)
Iteratively updated key models with superior performance and successful application cases;
Four generations of DTI models with high hit identification rates, for targets of all categories (first-in-class, difficult-to-drug targets, allosteric modulators, fast follow and repurposing)
Two developing DTI models with novel improvements: 1) an AI+CADD model learning from molecular dynamics (MD) to achieve both efficiency and accuracy (one million times speed-up); 2) an integrated model for SBDD+FBDD+LDBB+interaction
AI4Pat (automatic patent analysis) for extracting valuable data from patents: combined with high-throughput techniques and in vitro biochemical assays, the obtained data can be used to iteratively optimize the models (forming up a model-data-drug-model loop)