DaltonTx Launches Advanced Antibody Discovery Platform

LONDON, Oct. 01, 2026 /CourierPR/ -- DaltonTx, the decision engine for drug discovery, today announced the launch of advanced antibody discovery capabilities within the Dalton platform. The new capabilities bring together antibody design, structure prediction, and validation tools into a single workflow, enabling researchers to analyze, characterize, and prioritize antibody candidates at scale. By continuously testing AI-generated outputs against real experimental data, researchers can identify candidates that are not only scientifically plausible but more likely to succeed in development.

The platform, which operates through a chat interface, captures the rationale behind each decision, including why candidates were discarded and how priorities were set. A purpose-built ontology links scientists' observations and decisions to the specific antibodies designed and selected, ensuring that project knowledge accumulates rather than being lost between meetings, handovers, and team changes.

The platform can evaluate antibody repertoires comprising millions of sequences in a matter of hours. Recently, Dalton used the platform to fold the entire 2.6 million paired OAS space at a rate of 87,000 structures per hour. Researchers can use the platform for hit identification and optimization all the way to candidate discovery and design of complex antibody formats, such as bispecifics. The outputs are designed to inform scientific review and experimental planning, helping teams focus laboratory resources on the candidates with the strongest rationale for progression.

The launch is the latest step in DaltonTx's strategy to build intelligent drug discovery workflows that connect advanced AI, experimental data, and human expertise. The company continues to collaborate with the University of Oxford and other academic researchers to evaluate emerging approaches in antibody modeling and analysis.

DaltonTx is building the intelligence backbone for modern drug discovery, combining AI, human expertise, and experimental data into one continuous learning engine. The platform works across the entire drug discovery process for small molecules and biologics, capturing what worked, what failed, and why, with full context and perfect memory so that judgement compounds over time. Agents propose strategies, evaluate trade-offs, and autonomously orchestrate a comprehensive suite of AI, physics, and ML tools and models.

The outcome is smarter decisions, fewer wasted experiments, and the confidence to tackle more complex biology, knowing that every cycle improves the next choice. Founded on research from the University of Oxford and built by leaders with decades of experience behind AI discovery platforms at AstraZeneca and Exscientia, DaltonTx delivers state-of-the-art scientific AI with secure, enterprise-quality engineering.