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Antiverse Targets Drug Discovery's "Undruggable" Frontier with AI-Driven Antibodies

AI-designed antibodies could unlock more than half of GPCR targets that have long resisted traditional drug discovery.

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The Untapped Potential of GPCRs

More than half of all G-protein-coupled receptors (GPCRs) remain unexplored as drug targets, representing a vast frontier of untapped therapeutic potential. Based in Cardiff, Wales, Antiverse is one of the few companies tackling this challenge head-on, using proprietary generative AI to design antibodies for biological targets that have confounded traditional drug discovery for decades.


GPCRs are among the most important protein families in human biology, influencing hormone signalling, immune responses, neurological pathways and more. Their relevance spans oncology, inflammation, metabolism, and rare diseases, making them prime candidates for new medicines. Yet despite their clinical significance, 56% of GPCRs have never progressed to clinical development - not for lack of scientific interest.


Why GPCRs Are So Difficult to Drug

The reason is technical. These membrane proteins are notoriously difficult to target with conventional small molecules or biologics.


"GPCRs have this reputation as being incredibly challenging targets," explains Antiverse co-founder and CEO, Murat Tunaboylu. "The failure rates in early research and clinical stages have historically been very high. Our approach differs from conventional methods by using generative AI and advanced computational techniques to design novel, epitope-specific antibody candidates capable of targeting complex GPCRs and other biological targets previously considered undruggable.


Antiverse’s AI-Driven Approach

Antiverse's platform combines generative AI with advanced computational biology to predict and design antibody candidates that bind complex GPCR structures. Instead of screening millions of pre-existing antibodies, Antiverse generates structurally plausible, epitope-specific, novel candidates, dramatically accelerating the discovery timeline whilst improving success rates.


From Data to Discovery: Closing the Loop

The AI models learn from data generated in Antiverse’s own wet lab, enabling continuous refinement and improving results based on real-world experimental feedback rather than idealised datasets.


Growing Industry Interest and Partnerships

The approach has attracted attention from multiple top-20 pharmaceutical companies. Antiverse collaborates with pharmaceutical partners through research collaborations and licensing deals, applying its generative AI antibody discovery platform to address pharma’s most challenging multipass membrane proteins. Analysts have identified GPCR-targeting technologies as key disruptors in biotech's next wave of innovation, and Antiverse’s traction reflects the growing consensus that AI-designed antibodies may succeed where traditional approaches have failed.


Scaling from Wales to the World

The company has scaled rapidly beyond its Welsh origins, with teams now established in Boston and Prague, whilst maintaining its Cardiff headquarters. Wales’s emerging innovation ecosystem, recently profiled in The Economist, boasts strong university research programmes, supportive government policies and funding, and lower operational costs than traditional biotech hubs like Cambridge or Oxford.


"We’re building a world-class computational and wet-lab capability to transform how antibody therapeutics are discovered...by combining advanced AI-driven modelling with iterative experimental validation, we can design antibodies against challenging targets more rapidly and precisely, compressing early discovery timelines and improving the quality of candidates entering preclinical development” says co-founder and CTO Dr Ben Holland.


Antiverse's programmes are now advancing towards key clinical milestones, with the company positioned to demonstrate whether its AI-designed antibodies can succeed where traditional approaches have failed. If successful, the implications extend beyond Antiverse's pipeline. The technology could unlock an entire class of therapeutic targets for diseases that currently lack effective medicines.


For patients with conditions linked to unexplored GPCRs, that possibility represents more than a technical achievement. It's the difference between having treatment options and having none at all.

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BioFocus Newsroom

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