Syntekabio Secures 8 Biobetter Candidates with AI Antibody Design...Pipeline Expands to Metabolic, Muscle Loss, and Autoimmune Disorders

Syntekabio (226330) has expanded its biobetter pipeline beyond immuno-oncology to include metabolic diseases, muscle loss, and autoimmune disorders by utilizing its artificial intelligence (AI)-based antibody design platform. The company is strengthening its competitiveness in next-generation antibody drug development by validating its technology through a global contract research organization (CRO).

On August 3, Syntekabio announced that it had secured additional biobetter candidates for four target antigens related to metabolic diseases, muscle loss, autoimmune, and inflammatory disorders by leveraging its proprietary AI antibody design platform, 'Ab-ARS®.'

Following its initial proof of concept (PoC) research results released in July for immune checkpoint proteins PD-1, PD-L1, CTLA-4, and HER3, the company has now identified candidates for four additional targets: ACVR2B, IL-4Rα, IL-1β, and BTLA. As a result, the company has secured at least one biobetter candidate for each of eight total targets. This validation study was conducted independently by a global antibody-specialized CRO.

The company explained that this research demonstrates the AI-based antibody framework redesign technology is a versatile platform not limited to specific cancer applications but applicable across a wide range of therapeutic areas.

The research targets included distinct indications such as muscular and metabolic diseases, immune modulation, allergy, and inflammatory disorders. The company evaluated that, by securing biobetter candidates regardless of therapeutic area using the same AI design technology, it has proven the scalability of its platform.

In particular, the ACVR2B target is highlighted as a case with high commercialization potential. The originator antibody, bimagrumab, is used for patients with sarcopenia and muscle wasting, but it is currently administered only via intravenous injection. Syntekabio expects that if it succeeds in developing a biobetter formulation that enables subcutaneous (SC) injection, this could reduce the burden of hospital visits for patients and improve treatment accessibility.

The company also presented commercialization potential for the IL-4Rα and IL-1β targets. In chronic disease fields that already use subcutaneous formulations, delivering higher drug doses or increasing dosing intervals with the same injection volume can enhance both patient convenience and therapeutic efficiency.

For the BTLA target, for which no approved therapies exist yet, the company expects that securing high-solubility antibodies with minimized aggregation and stability issues from the early stages of development will boost the likelihood of successful drug development and position it competitively for future licensing and co-development negotiations.

The research team noted that all candidate antibodies secured for the four targets maintained antigen binding affinity that was equivalent to or greater than that of existing antibody drugs. The company explained that the key point in this research is not simply enhancing binding affinity, but that candidates were secured by redesigning antibody frameworks to target a high solubility level of 150–200 milligrams per milliliter while maintaining the existing level of binding affinity. Quantitative evaluation of solubility improvement effects will be carried out in subsequent studies.

Syntekabio plans to apply the AI antibody design technology accumulated through this research to the analysis of an antibody sequence library comprising hundreds of thousands of sequences. Based on this, the company aims to accelerate biobetter candidate discovery and further expand its pipeline into various therapeutic fields.

A Syntekabio official stated, "This study demonstrates that AI-based high-solubility antibody design technology can be applied across diverse therapeutic areas, not just limited to specific diseases," adding, "We will continue to expand our biobetter pipeline and strengthen our competitiveness in developing high-concentration formulations and next-generation antibody modalities."

This achievement demonstrates the versatility of Syntekabio's AI-based antibody design platform and is expected to serve as a catalyst for the company to expand its biobetter development and technology commercialization opportunities in a variety of therapeutic fields.

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