Carterra and AstraZeneca are collaborating to develop laboratory hardware and software for AI-driven biologics discovery, focusing on generating standardised experimental data at scale.

Connecting AI models with laboratory experiments

The research collaboration will bring together Carterra’s engineering and software teams with AstraZeneca’s scientists and automation experts to develop systems that connect laboratory equipment, software and data infrastructure with artificial intelligence (AI)-driven discovery workflows.

The approach, known as lab-in-the-loop drug discovery, links computational design with physical experiments. AI systems propose potential drug candidates, laboratory experiments test those designs, and the resulting data feeds back into the models to inform subsequent rounds of design.

The process creates a feedback loop between computational predictions and experimental results, with the aim of improving how candidate molecules are assessed and refined.

For the approach to work effectively, researchers need consistent, comparable experimental data that can be used across large numbers of experiments. Carterra and AstraZeneca will focus on developing laboratory systems capable of generating standardised data at scale, alongside software designed to make those results usable in AI and machine learning workflows.

Standardised data is a key challenge

The collaboration addresses a technical challenge in applying AI to biologics discovery: ensuring that experimental results can be integrated into computational workflows without losing consistency or comparability.

AI models can propose potential candidates, but experimental validation is needed to determine how those candidates perform in the laboratory. The quality and consistency of the resulting data can influence how effectively models learn from each round of testing.

High-throughput surface plasmon resonance (HT-SPR) is one technology used to analyse molecular interactions. Carterra develops HT-SPR platforms for antibody and small molecule discovery, providing technology relevant to the measurement and characterisation of potential drug candidates.

By combining laboratory systems with software and data infrastructure, the companies aim to make experimental results more directly accessible to AI-driven discovery processes.

Collaboration focuses on discovery infrastructure

Josh Eckman, CEO of Carterra, said: “Working with one of the world’s leading biopharmaceutical companies to help shape the next chapter of drug discovery is exactly the kind of collaboration our industry needs.”

He added: “AstraZeneca brings deep experience running biologics discovery at scale, and the willingness to commit real scientific and automation resources reflects how urgently the field is moving toward a truly connected, AI-enabled discovery loop.”

The announcement does not identify a specific drug candidate, therapeutic target or development programme. It also does not disclose a timeline or milestones for the hardware and software development work.

The collaboration therefore focuses on the underlying technology and data infrastructure needed to support AI-driven biologics discovery, rather than announcing a new medicine or a clinical development milestone.