HANXBIO-B Forges Strategic Alliance to Pioneer AI-Enhanced Drug Discovery Framework

Stock News
07/07

HANXBIO-B has announced a strategic partnership aimed at harnessing the power of artificial intelligence to revolutionize the drug development process.

The company has entered into a formal agreement with the Frontier Interdisciplinary Research Center of the Huake-Macau City University Advanced Research Institute to establish a joint Artificial Intelligence Drug Discovery Laboratory.

This collaboration leverages the AI platform of the Frontier Interdisciplinary Research Center alongside HANXBIO-B's (03378) extensive expertise in innovative drug R&D and its profound understanding of disease areas. The partnership will focus on antibody discovery and molecule design to create a new generation of AI-driven drug development methodologies.

Key Areas of Collaboration

The joint effort will concentrate on two primary objectives. The first is AI-assisted antibody optimization. This involves utilizing the partner's multi-scale molecular dynamics simulation and deep learning models to digitally screen large antibody libraries and predict affinity maturation. This approach is expected to significantly shorten the antibody discovery timeline, enhance the specificity and binding efficiency of candidate antibodies to their targets, and reduce the trial-and-error costs associated with traditional wet-lab experiments.

The second key area is intelligent molecule design and development. Both parties will collaborate to develop and apply advanced AI generative models for the de novo design of novel molecules. By employing intelligent prediction and multi-objective optimization of molecular structure, physicochemical properties, and ADME (absorption, distribution, metabolism, excretion, and toxicity) characteristics, the partnership aims to accelerate the identification of the most promising candidate drug molecules.

Strategic Benefits

This collaboration is anticipated to optimize the company's antibody screening and molecular optimization workflows. The expected outcomes include increased R&D efficiency and success rates, a significant reduction in the overall development cycle, and lower R&D costs. These improvements will accelerate the company's progress in developing first-in-class and best-in-class therapeutics.

Furthermore, the results from this partnership will enrich the company's R&D pipeline, strengthen its technological edge and core competitiveness, and provide robust support for its long-term development and sustainable operations.

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