Bengaluru Startup ImmunitoAI Uses Artificial Intelligence to Develop Next-Generation Antibody Medicines

Bengaluru-based biotechnology startup ImmunitoAI is developing a new approach to antibody drug discovery using artificial intelligence (AI). Its proprietary AI platform, AbInitio™, is designed to generate novel therapeutic antibodies targeting proteins associated with human diseases. By combining computational biology, machine learning and laboratory validation, the company aims to accelerate the discovery of biological medicines for conditions including cancer, autoimmune disorders and neurological diseases.

Founded in 2020 by Dr. Aridni Shah and Trisha Chatterjee, ImmunitoAI is part of India’s emerging technology-driven biotechnology ecosystem. The company focuses on designing antibody candidates with specific biological and pharmaceutical properties rather than relying exclusively on conventional laboratory screening methods.

AbInitio AI Platform Designs Antibodies for Specific Disease Targets

ImmunitoAI’s AbInitio platform uses proprietary artificial intelligence models to design antibodies that recognise and bind to selected regions of disease-related proteins.

Antibodies are specialised proteins produced naturally by the immune system. They recognise specific molecular structures, known as antigens, and can help the body identify and neutralise harmful substances. Scientists have adapted these properties to develop therapeutic antibodies for treating several diseases.

Traditional antibody discovery frequently involves screening large collections of naturally occurring or laboratory-generated antibodies to identify molecules capable of binding to a target.

ImmunitoAI follows a different approach. Its AI platform generates new antibody sequences based on the structural characteristics of the target protein and the biological function the resulting molecule is expected to perform.

According to the company, AbInitio incorporates multiple neural networks that analyse interactions between antibodies and their targets. This allows researchers to design candidates intended to recognise specific binding regions, known as epitopes.

The company states that its platform can generate biologically viable antibody sequences within weeks, supporting faster identification of candidates for laboratory evaluation.

Combining Artificial Intelligence with Laboratory Validation

A distinguishing feature of ImmunitoAI’s technology is its integration of computational antibody design with experimental biological research.

The company’s scientific team first identifies the disease-related protein and determines the biological effect required from the antibody. Researchers then use AbInitio to generate molecular sequences with the desired structural and functional characteristics.

The platform incorporates parameters such as binding affinity, specificity, stability and pharmaceutical developability during the initial design process.

These properties are important because an antibody intended for medical use must do more than recognise a particular protein. It must also demonstrate appropriate biological activity, remain stable during manufacturing and storage, and satisfy stringent safety requirements.

ImmunitoAI evaluates its AI-generated candidates through laboratory experiments conducted by its in-house biological research team.

This combination of computational prediction and experimental testing allows researchers to assess antibody performance and use the resulting data to improve subsequent designs.

Developing Antibody Candidates for Cancer and Autoimmune Diseases

ImmunitoAI is developing therapeutic antibody candidates for several disease areas, including oncology, autoimmune disorders, neurological conditions and cardiometabolic diseases.

In cancer treatment, therapeutic antibodies can target proteins associated with tumour growth, immune regulation or other biological processes involved in disease progression.

For autoimmune disorders, antibodies may be designed to influence molecular pathways responsible for abnormal immune activity.

The company is also exploring targets associated with neurological diseases, where the identification of suitable therapeutic molecules presents significant scientific challenges.

ImmunitoAI’s research strategy includes developing both first-in-class and best-in-class antibody candidates. First-in-class medicines act through new therapeutic mechanisms, while best-in-class development aims to improve particular properties of treatments within an established category.

These programmes remain part of drug discovery and development. AI-generated antibody candidates require extensive preclinical evaluation, followed by clinical trials and regulatory approval before they can become medicines for patients.

Indian Startup Receives $6.1 Million Series A Investment

ImmunitoAI announced a $6.1 million Series A funding round, led by investor Ashish Kacholia.

The funding round included participation from 3one4 Capital and AC Ventures, alongside existing investors pi Ventures, Anicut Capital, JITO Incubation and Innovation Foundation, and other investors.

According to the company’s announcement, the investment will support the development of its proprietary antibody discovery platform and the advancement of its therapeutic pipeline.

The funding strengthens ImmunitoAI’s capacity to combine artificial intelligence research with experimental biotechnology and pursue new antibody candidates for pharmaceutical development.

Indian Biotechnology Innovation Gains International Recognition

ImmunitoAI has also received international recognition for its approach to therapeutic antibody discovery.

The company won the inaugural Indo-Boston Biotech Bridge Award, an initiative involving Nucleate India, the Association of Biotechnology Led Enterprises (ABLE) and LabCentral.

The recognition provided opportunities for ImmunitoAI to engage with biotechnology entrepreneurs, pharmaceutical researchers, investors and industry leaders in Boston and Cambridge, Massachusetts.

Through the LabCentral programme, the company gained access to discussions on biotechnology commercialisation, scientific development and international industry partnerships.

Such engagements can help Indian biotechnology startups develop relationships with pharmaceutical companies and research institutions involved in translating early-stage scientific discoveries into therapeutic products.

India Strengthens Its AI-Driven Biotechnology Ecosystem

ImmunitoAI’s development reflects the growing convergence of artificial intelligence, computational biology and pharmaceutical research in India.

AI-based molecular design offers researchers new ways to explore complex biological targets, generate potential therapeutic candidates and assess drug-related properties before laboratory testing.

By integrating AI models with experimental validation, ImmunitoAI is working to improve the efficiency and precision of early-stage antibody discovery.

The company’s AbInitio platform demonstrates how Indian biotechnology startups are developing original technologies for advanced drug research, strengthening India’s capabilities in artificial intelligence, molecular biology and next-generation therapeutic discovery.

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References

1. ImmunitoAI — Official Company Website, AI-Driven Therapeutic Antibody Discovery.
   https://www.immunitoai.com/
2. ImmunitoAI — AbInitio: AI Platform for Therapeutic Antibody Design, official technology information.
   https://www.immunitoai.com/technology
3. ImmunitoAI — About Us, founders and research leadership.
   https://www.immunitoai.com/about-us
4. ImmunitoAI — Official announcement of $6.1 million Series A funding and antibody drug discovery programme.
   https://www.linkedin.com/company/immunitoai/
5. ImmunitoAI — Official company updates concerning the Indo-Boston Biotech Bridge Award and international biotechnology engagement.
   https://www.linkedin.com/company/immunitoai/

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