Samsung Bioepis and Professor Baek Minkyoung’s Seoul National University Team Join as Co-Research Institutions
Combining AI, Ultra-High-Speed Validation, and Global Capabilities
Protinah, a new drug development company specializing in protein-protein interaction (PPI) big data, announced on November 5 that it has been selected as the lead research and development institution for the national project “Development and Demonstration of Antibody Biopharmaceuticals Using Artificial Intelligence (AI) Models,” overseen by the Ministry of Health and Welfare.
Protinah will lead the project, with Samsung Bioepis and the research team of Professor Baek Minkyoung, a globally renowned expert in AI-based antibody design from Seoul National University, participating as joint research and development institutions.
The consortium aims to develop 10 AI-designed antibody drug candidates over a period of 2 years and 3 months, until the end of 2027. Of these, three candidates are targeted to reach the preclinical stage, and one candidate is expected to complete the application for a Phase 1 clinical trial (IND).
The traditional approach to antibody drug development requires enormous costs, averaging 3 trillion won. The success rate in the early stages is low, and the process is time-consuming. Although AI technology has recently been introduced, the probability of successful design remains below 1%. Bottlenecks in large-scale experimental validation have limited the reduction of development timelines.
To overcome the limitations of existing methods, Protinah, Samsung Bioepis, and Seoul National University have collaborated to establish a seamless development platform that connects each stage of drug development. Through this, they aim to transform the paradigm of antibody drug development and secure a competitive edge in the global technology race.
The core drivers of the project are “AbGPT-3D,” a world-class AI for antibody design co-developed by Protinah and Seoul National University, and Protinah’s proprietary ultra-high-speed, high-throughput antibody optimization and performance measurement platform “SPID (Single-Protein Interaction Detection).”
AbGPT-3D consists of three AI modules: ▲designing antibody structures that precisely bind to a given antigen, ▲generating sequences optimized for the designed structures, and ▲comprehensively evaluating the developability of the designed antibodies.
The SPID platform is a “game changer” technology that brings the speed of AI design into reality. It has reduced the verification process, which previously took several months, to just two weeks. More than 5,000 antibody sequences can be analyzed simultaneously each week. Using only minute, unpurified samples, it can quantitatively measure seven key developability indicators at once, including ▲binding affinity (KD), ▲productivity, ▲thermal stability, and ▲aggregation.
Using the SPID platform, Protinah succeeded in improving the performance of the autoimmune therapy “Humira” (ingredient: adalimumab). Within three months, they identified a biobetter candidate with 20 to 100 times the efficacy of the original antibody in animal models. In animal studies, the candidate demonstrated equivalent or superior therapeutic effects at doses up to 100 times lower than existing drugs. They also confirmed the potential to extend the dosing interval from two weeks to several months and to reduce the risk of side effects.
Within the national project, Samsung Bioepis is responsible for transforming antibody candidates discovered by the consortium into biopharmaceuticals suitable for clinical trials. By utilizing state-of-the-art automated equipment, they will rapidly develop cell lines with high productivity and stability, and optimize both upstream (cultivation) and downstream (purification) processes. They also plan to establish large-scale production (CMC) processes for clinical sample manufacturing.
Samsung Bioepis will also oversee the entire process from non-clinical toxicity testing (GLP-tox) to the final clinical trial application (IND). Samsung Bioepis has so far obtained IND approvals for 11 products in 39 countries from major regulatory agencies such as the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA). The company has a record of zero IND rejections.
Protinah and Samsung Bioepis have built a comprehensive joint research system over the past year through close collaboration. By fully introducing AI design technology into the antibody biopharmaceutical development process through this project, they aim to present a proven case of global AI-based antibody drug development.
The consortium’s goal goes beyond simply discovering new drug candidates; it aims to develop “best-in-class” biobetters that surpass the performance of existing blockbuster drugs. By entering already validated markets, they seek to reduce development risk and overcome the limitations of current therapies, thereby creating high market value.
Protinah CEO Yoon Taeyoung began laying the foundation for the high-speed antibody screening platform technology with five years of support from the Samsung Science & Technology Foundation, operated by Samsung Electronics to foster future scientific and technological advancements, from 2014 to 2018.
CEO Yoon stated, “Being selected for this national project marks the starting point for writing a new chapter in global AI drug development, combining Protinah’s SPID platform, Seoul National University’s AI technology, and Samsung Bioepis’s global development capabilities.” He added, “Within the challenging 27-month period, we will develop 10 antibody drug candidates and complete IND applications, thereby proving the innovativeness of our platform technology and contributing to providing better treatment options for patients.”
Kim Yooncheol, Executive Director at Samsung Bioepis, said, “Being selected for this national project is a recognition of the ‘process optimization’ we have accumulated through biosimilar development,” and added, “We plan to address unmet needs by discovering candidates through antibody design AI and analysis platforms.”
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