Benchling Launches Biologics Platform to Industrialize Antibody R&D Data and Workflows

New updates have been reported about Benchling.

Benchling has introduced Benchling Biologics, an end-to-end platform designed to handle modern antibody R&D at scale, positioning the company more deeply in data infrastructure for biologics discovery and engineering. The system lets scientists define any antibody format without code, register up to thousands of complex molecules in a single run, and maintain a fully linked design-build-test-learn record, addressing a key bottleneck as the field shifts toward bispecifics, multispecifics, and AI-driven design.

At the discovery stage, the platform integrates PipeBio by Benchling for high-throughput sequence screening, using a no-code interface to process millions of sequences and perform repertoire analytics, developability assessments, and liability checks before hits are moved directly into Benchling for structured registration. During design, users can rapidly configure new formats from modular building blocks, while the system automatically annotates CDR and framework regions, identifies germline genes, and validates constructs, converting what previously took weeks of custom engineering into same-day configuration and significantly improving data quality and reuse.

Benchling Biologics extends through build and test, capturing how each antibody is produced, expressed, and purified so experimental context remains attached to each molecule, and it connects to automated workcells via integrations with laboratory automation systems such as HighRes. For outsourced work, Benchling embeds direct ordering of materials and services, currently supporting partners for gene synthesis, expression, protein engineering, characterization, and developability screening, with all returned results automatically linked back to the originating design to shorten validation cycles and reduce coordination overhead.

On the analytics and learning side, the platform unifies sequences, samples, and assay results into an AI-ready dataset that can be used by discovery, engineering, and downstream development teams, giving organizations a single traceable record from initial concept to candidate selection. Benchling AI can summarize findings across experiments and surface options for next-generation designs, while MCP-based AI connectors enable access to external sequence and structure datasets and integration with PipeBio for combined sequence and assay analysis, reinforcing Benchling’s position as a core data and workflow layer for biopharma R&D and potentially driving deeper adoption among large enterprise customers seeking scalable, automation- and AI-compatible antibody platforms.