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Stay updated on Click.mAb. news, technology progress, and industry insights
Deciding whether a new target is worth pursuing usually means digging through scattered literature, databases, patents, and pipeline data. Click.mAb.'s new target research feature turns a single target name into a full, continuously editable research report across 10+ core dimensions.
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As candidate pools grow, the real question becomes which candidates are worth advancing. Click.mAb. now offers candidate list management and five-dimensional developability risk analysis, helping R&D teams centralize candidate sequences and assess potential risks across aggregation, chemical modification, humanness, polyreactivity, and viscosity to support candidate selection and optimization decisions.
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The 2026 Biophysics Congress was recently held in Hainan, where Clickmab presented its proprietary Click.mAb. AI antibody R&D platform and shared its technical explorations in epitope-specific de novo design, affinity maturation, and humanization. During the congress, Zhang Hong, academician of the Chinese Academy of Sciences and president of the Chinese Biophysical Society, visited Clickmab's booth for an in-depth exchange.
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Recently, Dr. Tianyuan Wang, CEO of Clickmab, conducted a special exchange session at the Hangzhou Institute of Medicine Chinese Academy of Sciences, delivering a keynote titled "Epitope-Specific AI De Novo Antibody Design for Antibody Drug R&D — Technical Principles, Current Applications, and Breakthrough Strategies." He shared the latest explorations of AI in antibody drug R&D and engaged in in-depth discussions with researchers on new trends, methods, and practical applications of AI-empowered biomedical R&D.
Read Full ArticleOn July 9–10, the AsiaBIO 2026 Innovation Summit (North China) was held in Beijing. Clickmab presented the Click.mAb. multi-agent AI antibody R&D platform, with CEO Dr. Tianyuan Wang delivering a keynote. Here we summarize the five questions we were asked most often on-site, along with our thoughts.
Read Full ArticleTo address the challenges of low efficiency and high randomness in CDR diversity library construction, Click.mAb. has officially launched CDR Diversity Engineering, using structure-guided design to help R&D teams obtain high-quality candidate libraries that balance diversity and developability.
Read Full ArticleDr. Tianyuan Wang, CEO of Clickmab, delivered a keynote at Guangzhou Laboratory, sharing the latest R&D practices and progress in AI-driven de novo antibody design, directed optimization, and the multi-agent platform.
Read Full ArticleOn June 11, 2026, the "AI-Driven Future: AI × Frontier Protein Technologies for Challenging Targets" summit co-hosted by Clickmab, Kactus Biosystems, and Sanyou Bio was successfully held in Shanghai, exploring new AI-driven antibody R&D paradigms and industry practices.
Read Full ArticleOn May 21-22, the "Antibody 3.0 | 2026 BioPlus Antibody Annual Conference" hosted by BioPlus Partners was successfully held in Suzhou. As a Gold Sponsor, Clickmab showcased its AI-driven antibody drug R&D platform and delivered a keynote in the oncology forum, exploring new trends, models, and opportunities in next-generation antibody R&D.
Read Full ArticleClickmab showcased its multi-agent AI antibody design platform Click.mAb. at CBA-China 2026, sharing the latest practices in de novo design, affinity maturation, humanization, and R&D collaboration.
Read Full ArticleLed by Hualan Shares with follow-on investment from XtalPi and Xichuangtou, this round will accelerate Click.mAb. platform iteration and proprietary data flywheel building.
Read Full ArticleJikang Bio and BioAge reached a strategic preclinical collaboration on a novel APJ agonist antibody, with Clickmab's AI platform playing a key role in discovery and optimization.
Read Full ArticleClickmab's NAVIGATOR workflow for GPCR agonist antibody optimization won the Chinese Antibody Society Poster Presentation Award again.
Read Full ArticleClickmab is dedicated to empowering antibody discovery through generative AI and welcomes partners across the ecosystem.