Synteca Bio Redesigns Blockbuster Antibodies With AI, Demonstrates Potential for High-Solubility Biobetter Development

SYNTECA BIO, an artificial intelligence (AI)-based drug development company, has secured a biobetter candidate with improved solubility over conventional blockbuster antibody drugs by utilizing its proprietary antibody design platform, highlighting the potential for next-generation antibody therapeutics.

On July 24, SYNTECA BIO announced that it had conducted proof-of-concept (PoC) studies on global blockbuster antibody medicines—including Keytruda (pembrolizumab)—using its proprietary antibody design platform 'Ab-ARS®' and had secured candidates predicted to offer higher solubility compared to existing antibodies.

This study was conducted by first screening framework (FR) sequences with high solubility characteristics (150-200mg/mL) and then applying these to existing antibodies. According to the company, by leveraging AI, it was possible to precisely predict protein structures and interactions, thus improving physicochemical properties while maintaining the original antibody's performance.

The study focused on the top 10 best-selling market antibodies targeting different antigens. The research team adopted a strategy of exchanging the framework to increase solubility while maintaining antigen-binding affinity.

AI platform analysis yielded framework sequences expected to deliver at least five to as much as twenty times higher solubility compared to conventional antibodies. The company explained that this increases the potential for developing high-concentration antibodies required for future subcutaneous (SC) formulations.

This study was jointly carried out with Cyron Therapeutics, a specialist in antibody discovery and development. Among the ten target antigens, biobetter candidates were identified for four, with at least one biobetter candidate per antigen; in total, six final candidate antibodies were secured. All six candidates demonstrated antigen-binding performance equal to or greater than that of conventional antibodies, with some showing double the binding affinity of the original antibody.

Specifically, the binding affinities of the PD-1 and PD-L1 target antibodies were enhanced by 2.8-fold and 2.3-fold, respectively, compared to conventional antibodies, while the CTLA-4 and HER3 target antibodies maintained binding affinity at levels equivalent to the original antibodies.

The researchers stated that even after optimizing the framework, the intrinsic binding capacity and function of the antibody were preserved, thereby validating the applicability of this design method. Solubility assessment will proceed sequentially through follow-up research, and if improvements in solubility are confirmed, it is expected to further enhance the likelihood of successful biobetter development.

Currently commercialized intravenous (IV) antibody drugs are administered at concentrations of 25mg/mL for Keytruda and 60mg/mL for Tecentriq. To transition these to subcutaneous (SC) formulations, high-concentration formulation development is essential. Major global pharmaceutical companies are pursuing strategies such as optimizing buffer solutions for high-concentration stock solutions and securing related formulation patents.

SYNTECA BIO, in contrast, focused on solving technical challenges by increasing the solubility of the antibody protein itself. By redesigning existing antibodies with frameworks exhibiting high solubility, the company is raising the potential for developing high-concentration formulations and SC formulation transitions.

For antibody drug candidates, not only efficacy but also solubility, stability, and aggregation—collectively determining developability—are key factors in clinical development and commercialization. Whereas previous approaches required repeated protein engineering and diverse experimentation to improve these physicochemical properties, SYNTECA BIO is building an AI-based platform to efficiently select candidates with optimized physical properties in the early stages of development.

The company plans to expand biobetter development for various therapeutic antibodies based on these PoC results and will also apply the platform to next-generation antibody therapeutics such as high-concentration antibodies and antibody-drug conjugates (ADCs).

A SYNTECA BIO official said, "This study is a proof-of-concept example demonstrating that AI-powered optimization of antibody physical properties can be applied to various antibodies. We will continue to advance our AI-based antibody design technology to further strengthen our competitiveness in biobetter and next-generation antibody drug development."

This research is significant in that it confirms the feasibility of designing biobetters with improved solubility while preserving the binding affinity of conventional blockbuster antibodies using AI.

This content was produced with the assistance of AI translation services.