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AI in drug discovery

Structure prediction, generative design and virtual cells: verifiable progress for AI in discovery and the clinic.

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141–142 of 142
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  1. mp.weixin.qq.com81

    Peking University Team and Collaborators Publish ContactSeek in Nature, Using AlphaFold3 Contact Probabilities to Improve Base-Editing Specificity

    Yi Chengqi's group at Peking University and collaborators published a study in Nature describing ContactSeek, an AI framework based on AlphaFold3 contact probabilities that systematically identifies amino acid residues determining editing specificity in base editors. The work combined AlphaFold3-predicted contact probabilities with off-target editing data from high-throughput sequencing, then engineered Cas proteins and deaminases accordingly, markedly improving editing specificity and establishing a new paradigm for precision design of gene-editing tools.

    Why it matters: The coupling of AlphaFold3 contact probabilities with high-throughput off-target data can be transferred to specificity engineering of other base editors or Cas proteins.

  2. mp.weixin.qq.com73

    Alphamab Onciation Licenses TROP2/HER3 Bispecific ADC JSKN016 to Pathos AI Outside China

    Jiangsu Alphamab Oncology has granted Pathos AI exclusive rights to develop and commercialize JSKN016, a first-in-class TROP2/HER3 bispecific antibody-drug conjugate, outside China. The deal includes $125 million upfront and up to $2.09 billion in development, regulatory and sales milestone payments, plus tiered royalties after launch. JSKN016 was developed in-house using Alphamab's single-domain antibody and glycosite-specific conjugation platforms. Next steps are Pathos-led ex-China development and commercialization.

    Why it matters: Large out-licensing deal for a first-in-class bispecific ADC by a Chinese biotech.

CBACBA Frontier Insights (CFI)Chinese Biopharmaceutical Association (CBA)www.cba-usa.org

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