How a Leading CRO Cut Antibody Delivery Timelines in Half_Life Sciences_Galatek

The market for therapeutic antibodies has never been more active. Estimated to approach $700 billion over the next decade, it spans oncology, immunology, and rare diseases - with cancer remaining one of the most heavily targeted areas, driving sustained investment in faster, more scalable discovery capabilities. Yet, for many organizations doing this work, the core workflow - plasmid construction, cell culture, transfection, and purification - remains highly manual, prone to variability, and difficult to scale under competitive pressure.

That tension between market demand and operational reality is where this story begins.

The Pressure on CROs is Real

Contract research organizations (CROs) occupy a unique position in the antibody discovery ecosystem. They are simultaneously accountable to client timelines, quality expectations, and competitive pricing. When throughput is constrained by the number of samples a technician can process in a day, or when batch variability introduces inconsistencies that affect downstream screening, the consequences are real. Projects get delayed. Clients look elsewhere.

A leading antibody discovery CRO came to Galatek facing exactly these compounding pressures: delivery cycle variability driven by fluctuating demand, throughput ceilings imposed by manual processing, batch inconsistencies unacceptable for functional screening or in vivo studies, and legacy automation that lacked the flexibility their workflows required.

The ask was straightforward, even if the solution wasn't: automate more of the workflow, reduce variability, and do it in a way that could scale.

Building From the Workflow Up

Galatek and the client company agreed that the best approach in their situation was to engineer from the ground up rather than retrofit existing automation. Each step of the antibody discovery workflow - from bacterial inoculation and plasmid extraction through mammalian cell transfection, expansion, harvest, and protein purification - was addressed as a discrete unit operation, custom-engineered for that specific process.

An Automated Guided Vehicle connects the unit operations, moving samples between stages without manual intervention. Orchestration software ties everything together: scheduling, instrument control, and real-time deviation flagging, with end-to-end traceability. The result is a platform where process risk is managed systematically. Cell density at transfection, DNA/reagent complex preparation, harvest timing, purification consistency, and sample identity are all governed by software rather than subjective technician judgment alone.

This is the practical meaning of an AI-driven workflow in a high-throughput biologics environment: not automation that runs a fixed script, but a system that monitors, adapts, and maintains data integrity across the full process.

What Changed

The impact across delivery time, batch capacity, productivity, and data quality was exactly what the CRO was aiming for. The full results are detailed in the case study, but the headline is that the CRO was able to cut its customer turnaround timeline in half and substantially expand what it could reliably deliver in a single batch run.

Equally important is what the platform enables moving forward. With 90% of the workflow now automated across five expression formats, the CRO's scientific teams are freed from managing process variability and can redirect their attention to the biology itself. The platform's modular architecture also means expansion into adjacent biologics programs won't require rebuilding underlying infrastructure.

A Blueprint, Not a One-Off

For Galatek, this engagement reflects something broader about how we think about automation in life sciences. The complexity of a therapeutic antibody discovery workflow with the number of unit operations, the sensitivity of biological processes, and the data integrity requirements, demands solutions designed around how research actually works. Cookie cutter automation creates ceilings. Custom-engineered platforms remove them.

If your organization is navigating similar pressures around throughput, reproducibility, or delivery timelines, we'd welcome the conversation.

Download the Case Study to learn more.