In 2025, artificial intelligence (AI) is driving a computing revolution fueled by data and intelligence. From Deepseek’s growing applications in smart healthcare to Huawei’s “Healthcare Corps” advancing AI-driven medicine, AI is transforming the pharmaceutical landscape—streamlining everything from target identification to clinical translation and helping overcome the long timelines and high costs traditionally associated with drug development. As a leader in innovation, Chipscreen Biosciences continues to expand AI applications across drug discovery, data management, and intelligent office systems, accelerating innovation and boosting R&D efficiency.

Pioneering AI-Driven Drug Discovery

Since its founding, Chipscreen Biosciences has been at the forefront of global biotechnology, harnessing microarray biochip technology to study how diverse chemical structures influence human gene expression. This approach generates extensive datasets on drug-gene interactions, target efficacy, and potential toxicity. Using high-efficiency algorithms, the company rapidly identifies compounds with therapeutic potential. The name “Chipscreen” reflects its core technological strength: leveraging microarray gene chips for drug development. The platform excels in both target discovery, through disease-gene analysis, and drug screening, via gene-drug profiling. By integrating its proprietary computer-aided design and chemogenomics platform, Chipscreen has shortened drug development timelines and reduced late-stage risks—an early example of AI and big data applications in pharma.

In 2022, Chipscreen partnered with Huawei Cloud to leverage the Pangu large model for auxiliary drug molecule design, enhancing protein-drug interaction analysis and supporting end-to-end independent innovation in novel drug development. By integrating capabilities such as target pocket discovery, molecular docking, molecule generation and optimization, and molecular property prediction, the collaboration enhances early-stage discovery efficiency and optimizes target-binding affinity. This one-stop AI-aided drug discovery platform accelerates R&D, significantly reduces computational drug design costs, and produces multiple proprietary structural series, expanding options for pipeline advancement.

In oncology R&D, Chipscreen achieved a 33% increase in drug design efficiency and a 40% improvement in target-binding energy after molecular optimization, substantially accelerating the development of innovative cancer therapies.

Collaborating to Shape the “New Paradigm” of AI+Pharma

AI-driven drug discovery represents the deep integration of artificial intelligence and pharmaceuticals, a sector strongly encouraged and prioritized by national policy. In recent years, the State Council and relevant government authorities have issued a series of industrial policies to support and regulate the development of the biopharmaceutical and AI-driven drug discovery sectors. In line with the 14th Five-Year Plan for the Pharmaceutical Industry and the 14th Five-Year Plan for Bioeconomy Development, the government is prioritizing the application of cloud computing, big data, artificial intelligence, and other information technologies in drug R&D, while promoting the rapid growth of AI-powered drug discovery. Earlier this year, China officially inaugurated its first “AI + Pharmaceuticals and Medical Devices Professional Committee” in the Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone. Dr. Lu Xianping, Chairman and General Manager of Chipscreen Biosciences, was appointed Deputy Director of the committee.

“Original drug development often faces limited reference data, requiring scientists to engage in extensive creative design based on existing knowledge. Understanding disease-protein/gene-drug relationships and proactively designing effective therapeutics has long been a central goal of the pharmaceutical industry,” Dr. Lu noted. Furthermore, Dr. Lu emphasized, “The application of AI in pioneering innovation represents a dual empowerment: both as an ‘efficiency tool’ and as a driver of scientific discovery. Moving forward, we will further integrate AI with scientific exploration, continuously contribute end-to-end expertise in ‘AI + drug discovery,’ and promote the high-quality development of the biopharmaceutical sector.”