AWS launches “Amazon Bio Discovery” to revolutionize antibody research

USA—Amazon Web Services (AWS) has unveiled plans to launch a new artificial intelligence (AI) platform to accelerate and improve the development of novel drugs.

The system, known as Amazon Bio Discovery, provides researchers with direct access to a wide range of specialized AI models trained on extensive biological datasets.

Researchers build these biological foundation models (bioFMs) to analyze complex biological data and support the development of antibody therapies.

In addition, the platform offers a comprehensive suite of tools, including a library of AI models, advanced analytics packages, and an AI-powered agent that assists researchers in designing experiments.

AWS has also integrated lab partnerships into the platform, enabling a more seamless transition from computational research to practical testing.

As a result, scientists can move more efficiently from hypothesis to validation.

Advances in generative AI transform research
Recent progress in generative AI has significantly expanded the capabilities of machine learning in drug discovery.

For instance, modern models can now predict protein structures and assess drug candidates based on their chemical and biological properties.

These capabilities allow researchers to evaluate potential treatments earlier and with greater precision.

According to Rajiv Chopra, vice president of AWS Healthcare AI and Life Sciences, AI agents are making advanced scientific tools more accessible.

He explained that these systems can design drug molecules, coordinate testing processes, and continuously learn from experimental results.

Consequently, each iteration becomes more refined, enabling faster and more informed decision-making.

Chopra also emphasized that AWS’s secure infrastructure supports regulated industries, allowing researchers to accelerate innovation while maintaining compliance.

Real-world applications in oncology
Researchers at Memorial Sloan Kettering Cancer Center (MSK) are already applying this technology in antibody drug development.

Dr. Nai-Kong Cheung, who leads pediatric oncology research at MSK, has used similar tools in developing an antibody-drug candidate.

Cheung noted that traditional drug development timelines are extremely long, often taking decades to move from discovery to regulatory approval.

He explained that it took 20 years to validate the first generation of an antibody and another 13 years to prepare it for human use before receiving FDA approval.

Therefore, he welcomed the collaboration with Amazon Bio Discovery, highlighting the urgent need to shorten development timelines and deliver results faster for patients.

Growing industry investment in AI
Meanwhile, the broader pharmaceutical industry continues to invest heavily in AI-driven innovation.

Earlier this week, Novo Nordisk partnered with OpenAI to develop new treatments for obesity and diabetes.

Similarly, Eli Lilly has signed multiple AI-focused discovery agreements throughout 2025.

Experts previously told Pharmaceutical Technology that AI’s ability to narrow the search space for drug candidates remains one of its most valuable contributions.

By focusing on the most promising options early, research teams can reduce time and costs.

Data from GlobalData further shows that venture financing in the pharmaceutical sector increased by 48% in 2025 compared to 2024, reflecting growing confidence in AI-powered drug discovery.