Sanyou Bio Launches 14-Day Antibody Discovery Workflow, Compressing Lead Molecule Identification from Months to Two Weeks
核心洞察
Sanyou Bio's AI-STAL 2.0 (搜索) platform integrates AI-guided digital panning, intelligent sequence-structure analysis, and eukaryotic expression to deliver validated candidate antibodies in just 14 days.
The platform draws from ten super-trillion-scale specialized sub-libraries and has completed over 1,300 molecule discovery projects, with more than ten advancing to clinical stages.
The workflow addresses industry pain points including lengthy timelines, limited library coverage, and insufficient early developability assessment by creating a closed-loop "in silico and in vitro" system.
SHANGHAI, April 15, 2026 — Sanyou Biopharmaceuticals (搜索) has announced the official launch of its "14-Day Lead Molecule Discovery Workflow," powered by the AI-STAL 2.0 (搜索) platform, a breakthrough that compresses the entire process from library panning to validated candidate molecule delivery into just two weeks. The workflow, applicable to antibodies, peptides, and binding proteins, represents what the company describes as a fundamental reengineering of early-stage biologic drug discovery.
The announcement addresses long-standing industry frustrations. "Traditional molecular discovery processes have long suffered from an imbalance between 'time line' and 'quality,'" Sanyou Bio stated. Conventional screening methods often require months to complete, and when confronted with ultra-large libraries, the throughput of wet-lab screening becomes disconnected from digital evaluation systems, leaving high-affinity, high-specificity molecules buried in massive datasets.
A Four-Station Intelligent Workflow
The AI-STAL 2.0 (搜索) platform operates through four sequential intelligent workstations that together form a complete closed loop from molecule generation to functional validation.
The process begins with AI-guided activity screening and digital panning, which replaces traditional phage display physical selection. The platform uses intelligent algorithms to perform virtual screening on super-trillion antibody libraries, rapidly identifying promising core molecules while simultaneously integrating solubility prediction and real-time affinity validation. This eliminates molecules prone to expression difficulties or aggregation at the earliest screening stage.
The second station employs "intelligent sequence-to-structure mapping" technology, converting selected amino acid sequences into three-dimensional structural models. For peptides and single-domain antibodies whose biological function depends on correct spatial folding, this step also involves binding epitope analysis, enabling R&D teams to understand molecule-target interactions early and avoid investing resources in ineffective candidates.
The third station uses AI-optimized production pathways to design optimal expression and preparation schemes, followed by validation in eukaryotic expression systems. Unlike prokaryotic systems, eukaryotic expression more accurately reproduces complex post-translational modifications such as glycosylation, which is critical for the activity of IgG antibodies and binding proteins.
By Day 14, the R&D team receives high-quality candidate molecules that have undergone real affinity validation, structural mapping confirmation, and eukaryotic expression optimization.
Platform Foundation and Track Record
The core capability of AI-STAL 2.0 (搜索) rests on a molecular repository comprising ten highly specialized sub-libraries, including the Super Trillion Fully Human Antibody Library, Super Trillion Common Light Chain Antibody Library, Super Trillion 2C-Type and 4C-Type Single-Domain Antibody Libraries, Super Trillion Cyclic Peptide Library, and Super Trillion Novel Targeted Protein Library, alongside Magnetic Array immune antibody libraries from mouse, alpaca, rabbit, and canine sources.
To date, the platform has completed over 1,300 molecule discovery projects and successfully advanced hundreds of preclinical candidate (PCC) projects, with more than ten having entered clinical development stages.
Case Data and Performance
According to Sanyou Bio, most antibody candidate molecules obtained through AI-STAL 2.0 (搜索) screening exhibit strong protein-level binding activity as measured by ELISA, with all candidate antibodies demonstrating binding to their target antigens. Similarly, cell-level activity analysis using FACS confirmed that all candidate antibodies bound to overexpressing cell lines.
GEOTA (搜索) Platform Expansion
In a related development, Sanyou Bio also unveiled the GEOTA (搜索) intelligent program tool matrix, a core module of its SAI-DA (搜索) (Sanyou AI-Drug Accelerator) platform. GEOTA comprises five interconnected modules — Generation, Evaluation, Optimization, Target, and Advance — that collectively cover the full drug R&D chain from target identification through clinical advancement.
The AI-Advance module specifically targets the "Valley of Death" in drug development by enabling parallel acceleration of clinical translation and CMC process development. On the CMC side, it intelligently predicts critical parameters for formulation development and process scale-up while performing virtual simulations of production workflows. On the clinical side, it proactively evaluates in vivo safety and efficacy translation risks to accelerate the transition from preclinical development to IND submission.
Sanyou Bio, headquartered in Shanghai with global business centers across Asia, North America, and Europe, has established collaborations with more than 2,000 pharmaceutical and biotech companies worldwide, empowering over 1,200 new drug discovery projects. The company has filed over 170 invention patents, with more than 30 granted, and has completed more than 50 collaboration projects, over 10 of which have advanced to IND approval.
Looking ahead, the company plans to achieve a fully automated closed loop for R&D processes by 2026 and aims to complete full integration of AI tools into an "Agent" R&D model within the year.