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Benchling's Science Foundries: Transforming Scientific Collaboration

In a significant advancement for the scientific community, Benchling has recently introduced Science Foundries, a groundbreaking approach designed to facilitate seamless collaboration between scientists and agents throughout scientific processes. Launched on October 15, 2026, the initiative aims to streamline how research and development (R&D) teams operate, allowing them to run scientific workflows from start to finish with improved efficiency and speed.

A New Era for Scientific Workflows

Science Foundries essentially enable R&D teams to select a specific process or objective to work on, such as protein production, optimizing a promising lead, or enhancing a manufacturing procedure. Teams can specify which steps agents will handle and when scientists are needed for approvals. This collaborative environment ensures that both agents and scientists are working with the same data and context, driving scientific projects forward more rapidly.

To date, Benchling's efforts have focused heavily on integrating AI into scientific endeavors, with agents emerging as the fastest-growing feature the company has released. The introduction of Science Foundries now expands the concept of agentic work to encompass entire scientific workflows, breaking down barriers that have traditionally hindered progress in scientific research.

Enhanced Experimentation Capabilities

What sets Science Foundries apart is their ability to connect various elements within the scientific workflow, including models, contract research organizations (CROs), laboratory instruments, and scientists. This creates an interconnected system where each part of the workflow contributes to the success of the overall process.

One notable example is observed in a collaboration with a pharmaceutical team that specializes in designing, producing, and testing antibodies at a high throughput. Previously, the team had to manually handle data between each step of the process. However, with the Science Foundry, the end-to-end automation significantly reduces the manual workload, allowing scientists to focus on higher-level decisions rather than routine data processing.

For instance, various agents work concurrently in a Foundry:

• - A design agent generates and evaluates sequences,
• - A cloning agent plans assembly strategies and interacts with CROs,
• - A lab agent manages instructions for workcells and quality control, and
• - An analysis agent processes results and updates training datasets.

As a result, scientists are better equipped to direct their attention towards significant decisions that influence project outcomes, leading to improved research velocity. The ability for agents to deliver results in real-time enables faster progression of studies — for example, agents can synthesize data as soon as an assay is completed, potentially allowing scientists to start new experiments by the next working day. Incremental gains in experiment initiation can aggregate into substantial time savings over an extended research timeline.

Furthermore, Science Foundries also encourage broader exploratory capabilities among scientists. Previously, experimental strategies were limited because scientists would have to oversee each setup and monitor outcomes one by one. Now, multiple strategy comparisons against a common goal can be conducted simultaneously, leading to a richer selection of results for scientists to analyze and choose from.

Case Study: Parabilis Medicines

An exemplary case of utilizing Science Foundries is Parabilis Medicines, a clinical-stage biotech developing a new class of peptides. Initially, their team operated using standalone agents for discrete tasks. However, the deployment of Science Foundries has enabled them to integrate complete scientific processes — from protein production to lead optimization. This shift not only increases efficiency but also helps their lean team focus more on decision-making that propels projects forward, reducing downtime between experiments.

John McGee, Scientific Co-Founder and Head of Platform at Parabilis, emphasizes the importance of AI and automation in reshaping drug discovery. By leveraging the capabilities of Science Foundries, he believes researchers can harness the potential of AI to better manage their tasks while enhancing lab operations.

Conclusion: Availability and Future Prospects

As of today, Benchling customers can begin setting up their own Science Foundries. Each implementation process starts with identifying key objectives, after which a conversation with Benchling's AI can initiate the creation of a customized Science Foundry tailored to specific organizational needs. Benchling stands poised to accelerate how scientific discovery is approached by merging technology with traditional R&D processes.

For further information on how to leverage Science Foundries, interested parties are encouraged to reach out to Benchling for personalized consultations. As the company continues to innovate and build upon these foundational tools, the future of scientific research looks brighter than ever.

About Benchling: Benchling is an AI-driven platform specializing in biotech research and development, dedicated to unifying and automating scientific workflows globally. Trusted by over 1,300 organizations including industry leaders like Merck and Moderna, the platform strives to enhance the speed and efficacy of scientific discovery and development.