
By delivering autonomous, interoperable robots, ABB enables labs to scale operations, reduce manual error, and accelerate data‑driven research, reshaping the pharmaceutical and biotech automation market.
The laboratory automation sector is undergoing a rapid transformation as artificial intelligence and collaborative robotics converge to meet the demand for higher productivity and data integrity. Companies are moving beyond isolated pilot projects toward fully connected, AI‑ready environments that can orchestrate instruments from multiple vendors. In this landscape, ABB Robotics positions its Autonomous Versatile Robotics (AVR) platform as a catalyst for change, promising to bridge the gap between traditional bench work and digital, end‑to‑end workflows.
At SLAS 2026, ABB demonstrated three integrated process cells that illustrate the practical benefits of this approach. A multi‑step analytical workflow, built with Mettler Toledo hardware and LabX software, leveraged GoFa robots to perform pipetting, decanting and vial handling, delivering consistent results and freeing operators for higher‑value tasks. A gas chromatography sample‑preparation line showcased the same robots managing both dry and wet operations, while the OptiFact platform aggregated real‑time data for traceability. The Agilent collaboration extended these capabilities to plate‑hotel logistics, proving that ABB’s robots can seamlessly operate across disparate ecosystems.
The implications for biotech, pharmaceutical and contract research organizations are significant. Interoperable, AI‑driven robotics reduce cycle times, improve reproducibility, and generate richer datasets that accelerate decision‑making. ABB’s partnerships with industry leaders such as Agilent and Mettler Toledo signal a broader shift toward open automation standards, encouraging vendors to design compatible interfaces rather than proprietary silos. The roundtable hosted on February 10, featuring experts from Sanofi and Atinary, underscores the strategic importance of these technologies and hints at a future where autonomous labs become the norm rather than the exception.
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