Nanobodies feature low molecular weight, strong tissue penetration and excellent stability, endowing them with immense potential in diagnostic reagents, targeted therapy and other fields. Nevertheless, bottlenecks including insufficient affinity and lengthy development cycles have long hindered rapid project advancement. Powered by an AI-driven end-to-end solution, AlfaDAX—Daewoong Biotech’s intelligent molecular evaluation and optimization platform—overcomes limitations of conventional development workflows and achieves remarkable results in nanobody optimization.

Library-Free, High-Efficiency Optimization via Two Rounds of Iteration

To address the demands of nanobody projects, the AlfaDAX platform bypasses traditional library construction and surface display workflows. Leveraging AI, it directly designs precise mutations targeting key binding sites, drastically shortening development timelines and enabling high-performance optimization breakthroughs.

▲ Two Rounds of AI-Directed Optimization on AlfaDAX Platform

Project data clearly demonstrates AlfaDAX’s outstanding optimization performance:

· After the first round of optimization, clones with markedly enhanced affinity emerged among synthesized sequences, with several variants exhibiting several-fold higher affinity than the parent sequence, preliminarily validating the reliability of AI-aided design.

· Upon completion of the second iterative optimization, multiple variants achieved over 10-fold affinity elevation, fully meeting the project’s performance targets. Meanwhile, affinity values of optimized sequences showed tighter distribution, delivering far superior overall optimization outcomes compared to the first round.

Core Advantages of the Workflow

Eliminates labor-intensive traditional library generation and surface display screening. Designed sequences are directly synthesized and subjected to affinity testing, cutting time spent on library building and efficiency losses during screening.

AI conducts in-depth analysis of the parent sequence’s structure and binding mechanism to accurately identify key residues governing binding affinity. Optimization is accomplished via two iterative design rounds with a total synthesis volume of merely around 60 sequences.

Starting from the native parent sequence, the full optimization workflow is completed within just 1.5 months, perfectly catering to tight project delivery schedules.

This successful nanobody affinity optimization case only scratches the surface of AlfaDAX’s full capabilities. Boasting three core strengths—intelligent predictive modeling, synchronous 3D structural optimization, and low-cost high-throughput iteration—AlfaDAX accelerates the translation of complex, challenging biomacromolecule programs from lab research to clinical development.

Furthermore, AlfaDAX serves as an integral component of Daewoong Biotech’s PCC Prime Foundry. It empowers clients to finish the development of drug-like PCC molecules paired with high-yield, stable cell lines within an 8-month turnaround.