Engineering the future of
drug discovery
Designing functional antibodies for the most challenging targets.
WHAT WE DO
Machine Learning Makes Antibody Design Possible.
We are developing the next-generation of computational antibody design technology to enable discovery and design for the most challenging drug targets, including G-protein coupled receptors (GPCRs), transmembrane proteins, and ion channels.

>400 GPCRs and ion channels are associated with 60+ human diseases. Yet, there are only 3 FDA-approved antibodies for GPCRs and none for ion channels. Inaccessible, small binding sites makes these targets unavailable for discovery using traditional high-throughput screening and other methods.

Our platform uses proprietary AI and ML algorithms to design de novo epitope-specific antibodies that maintain the desired function and developability parameters. Our in-house wet lab generates unique cell lines that enable us to test the antibodies directly, and in disease-relevant assays.

We have proven our ability to move from target identification to functional, optimized antibody for high-value drug targets in just 4 months. And, our technology has been validated by multiple top pharma companies.
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Machine Learning Design Engine

We design target-specific antibody libraries for every target we pursue.

Our models can intelligently predict sequences with a high binding probability without the need for pre-existing data.

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State-Of-The-Art Laboratory Facilities

We prepare unique cell lines expressing millions of the desired receptor.

Screening our target-specific libraries against cells with high receptor counts improves the likelihood of discovering binders with high efficacy and affinity.

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Screening and Multiparameter Clustering

Panning outputs are sent for deep sequencing. The analytical arm of our platform clusters sequences across 20 different antibody properties.

Predicted lead candidates showing the desired properties are sent for further functional validation.

OUR EDGE
Advance Your Antibody Discovery Programmes
  • 1

    Challenging Epitope Expertise

    Data quality dictates program quality. Over the last 7 years, we have trained our generative models through several challenging target-focused projects, including G-protein coupled receptors and ion channels.

  • 2

    Strategic Antibody Design

    Our multiparameter clustering capabilities means we can select for antibodies with desired and developable properties. We design epitope-specific antibodies, optimize physiochemical properties and ensure high humanness simultaneously.

  • 3

    Personalised Partnerships

    We have developed >400 hyper-expressing cell lines, with demonstrated ability to isolate antibodies for difficult-to-express proteins. This enables us to perform the physiologically realistic validation necessary for GPCRs and transmembrane proteins.

  • 4

    Accelerated Timelines

    Our in silico approach augments the efficiency of the antibody discovery process. We have proven our ability to generate optimized, functional binders in just 4 months.

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PIPELINE

Robust pipeline with wholly-owned and partnered programs

Program
Target Class
Discovery
Lead ID
Preclinical
IND-E
Oncology
Checkpoint
Partnered
Cardiovascular
PAR1*
GPCR
Wholly-owned
Oncology
TMR
Partnered
CNS
GPCR
Partnered
Undisclosed
GPCR
Partnered
Idiopathic Pulmonary Fibrosis
GPCR
Wholly-owned
MASH
Cardiometabolic diseases
PAQR
Wholly-owned
* PAR1 program also has attractive development potential for Triple Negative Breast Cancer (Singh DD et al, 2021). Antiverse has not prosecuted this to date.  
WHAT WE DO
Machine Learning Makes Antibody Design Possible.
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About Antiverse


Antiverse is an artificial intelligence-driven techbio company that specialises in antibody design against challenging targets, including G-protein coupled receptors and ion channels. Headquartered in Cardiff, UK and with offices in Boston, MA, Antiverse combines state-of-the-art machine learning techniques and advanced cell line engineering to develop de novo antibody therapeutics.

Antiverse has collaborated with three top global pharmaceutical companies. They are developing a strong internal pipeline of antibodies against several challenging drug targets across various indications.

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