Daewoong Pharmaceutical Revolutionizes Drug Development with AI Technology


  • Daewoong Pharmaceutical unveils an AI-driven drug development system, revolutionizing pharmaceutical research.
  • AI technology cuts drug development time to 7 years, reducing costs significantly.
  • Daewoo ng’s AI and human collaboration are set to accelerate new drug discoveries.

In a significant leap forward for the pharmaceutical industry, South Korea’s Daewoong Pharmaceutical announced the completion of a groundbreaking drug development system empowered by artificial intelligence (AI). This innovative approach aims to streamline discovering and developing new medications, potentially transforming the pharmaceutical research landscape.

Innovative AI system and database creation

Daewoong Pharmaceutical has introduced an advanced system comprising two key components: the Daewoong Advanced Virtual Database (DAVID) and the Daewoong AI System (DAVIS). DAVID boasts an impressive collection of 800 million preprocessed molecular models. This database is a product of over four decades of meticulous research and development. By preprocessing these models, Daewoong’s researchers have refined complex compound structures, removing irrelevant information to make the data more compatible with AI-driven drug development processes.

DAVIS, on the other hand, is an AI system tailored to utilize the vast resources of DAVID efficiently. This system guides new drug candidates through the entire development lifecycle, from preclinical studies to commercialization. Integrating DAVID and DAVIS marks a significant step toward automating and optimizing drug discovery and development.

Accelerating drug discovery with virtual screening

A notable feature of Daewoong’s AI-based drug development system is the AI-based Virtual Screening (AIVS) tool. This technology employs 3D modeling to identify active substances that target specific proteins. By focusing on substances with patentable chemical characteristics, the AIVS tool facilitates the rapid discovery of new drugs. This method has already shown promise in identifying potential treatments for obesity, diabetes, and cancer. Additionally, it has accelerated the development of protein degraders, reducing the time and resources typically required for antibody design and stability evaluation.

The application of AI in drug development is not only advancing the discovery of new treatments but also redefining the efficiency of the process. Daewoong’s use of AI technology promises to cut the traditional drug development period from an average of 15 years to just seven years. Furthermore, it is expected to significantly reduce the associated costs from the 2 trillion to 3 trillion won range to approximately 600 billion won ($450 million). These advancements significantly improve the speed and economics of bringing new drugs to market.

A future shaped by AI and human insight

Park Joon-seok, head of the Drug Discovery Center at Daewoong, emphasized the synergy between human researchers and AI technology. He believes the collaborative growth and insights generated from this partnership will pave the way for more successful drug development projects. This approach underscores the potential of AI to complement human expertise, enhancing the efficiency and effectiveness of pharmaceutical research.

Daewoong Pharmaceutical’s introduction of an AI-based drug development system marks a pivotal moment in the pharmaceutical industry. By harnessing the power of artificial intelligence, the company is setting new standards for how drugs are discovered and developed. This innovative approach not only promises to bring new treatments to patients more quickly but also at a significantly reduced cost. As Daewoong continues to refine and expand its use of AI in drug development, the potential for further medical breakthroughs remains vast and exciting.

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Glory Kaburu

Glory is an extremely knowledgeable journalist proficient with AI tools and research. She is passionate about AI and has authored several articles on the subject. She keeps herself abreast of the latest developments in Artificial Intelligence, Machine Learning, and Deep Learning and writes about them regularly.

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