This video demonstrates an example of epitope-specific antibody de novo design completed through teamwork based on a large language model (LLM)-based multi-agent system. In a typical AI antibody de novo design project workflow,
1. Users articulate their requirements for antibody design targeting a specific antigen in natural language.
2. The Team Manager Agent is responsible for understanding the requirements and transforming the problem, formulating an execution plan for the entire antibody de novo design, and assigning tasks to other agents in the team.
3. AI Agents with expertise in different domains, including a Bioinformatics Expert Agent, Computational Structural Biology Expert Agent, Computational Antibody Design Expert Agent, and CRO Management Expert Agent, utilize respective AI models and tools to communicate and coordinate among themselves and interact with users to gather necessary information. They ultimately complete the computational task, performing statistical analysis and presentation of the results.
4. After the computational design of the antibody, the CRO Management Expert Agent sends out the requirements for wet experiments to CRO to complete the experimental validation and feedback the results to the users.
The Agents possess short-term and long-term memory, accumulating more antibody design knowledge through completing multiple projects, thereby improving their efficiency and effectiveness in subsequent tasks. Clickmab's multi-agent platform offers you cutting-edge technology in generative AI-based epitope-speicific antibody design, helping you to more quickly obtain antibodies with significant clinical advantages.

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