Carterra is working with AstraZeneca on a research collaboration focused on developing the laboratory hardware and software needed to support more connected, AI-driven approaches to biologics discovery. The Salt Lake City-based company, which develops high-throughput surface plasmon resonance (HT-SPR) technology for antibody and small-molecule discovery, said the collaboration will combine the expertise of its engineering and software teams with AstraZeneca scientists and automation specialists.

The goal is to strengthen the connection between computational models, laboratory experimentation and the data generated during drug discovery. The approach, commonly described as "lab-in-the-loop," involves using artificial intelligence to propose potential drug candidates or experiments, testing those predictions in the laboratory and then feeding the resulting experimental data back into AI models. The process can then be repeated to guide subsequent rounds of discovery. Interest in this model has grown as drug developers look for ways to combine advances in AI with the experimental capabilities needed to validate computational predictions.

A key challenge is the quality and consistency of the experimental data available to these systems. Data generated across large numbers of laboratory experiments needs to be sufficiently standardized and comparable if it is to be used effectively in machine-learning workflows. Carterra and AstraZeneca are therefore targeting both sides of that challenge, with work spanning laboratory systems and the software infrastructure used to handle the resulting data. The companies aim to develop systems capable of generating standardized experimental data at scale, while making that information more readily accessible to AI and machine-learning applications. Such infrastructure could help drug discovery teams move toward more automated cycles in which computational design and experimental testing are closely integrated.

The collaboration comes as pharmaceutical companies increasingly explore autonomous laboratory platforms and ways of connecting computational drug design with high-throughput experimental validation. "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," says Josh Eckman, CEO of Carterra.

For Carterra, the collaboration represents an expansion beyond the role of analytical instrumentation toward the broader infrastructure required for increasingly automated drug discovery workflows. If successful, the work could help address one of the practical limitations of AI-led discovery: ensuring that algorithms have access to reliable experimental data quickly enough to inform the next stage of design.

For more information, visit www.carterra-bio.com.