New AI Software Cuts Chromatography Review Time by Half
Waters Corporation updates its Empower platform to reduce manual data interventions by 95 percent starting in late 2026.
Updated on Oct. 28, 2026 in Artificial Intelligence
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Waters Corporation has announced a new AI-powered feature for its Empower software designed to automate chromatography data review. The system, which is currently in the late-stage evaluation phase, utilizes machine learning to handle routine baseline editing and noise removal.
Why it matters
By reducing the reliance on manual data processing, this tool aims to accelerate pharmaceutical drug development timelines and improve the consistency of quality control testing for manufactured molecules.
The AI models achieve these gains by training on data from individual laboratories to automate complex tasks, including removing noise peaks and aggregating high-molecular-weight peaks. The tool resulted in 72% lower variation between human reviewers in 2026 evaluations.
The players
Waters Corporation
An analytical instrument and software company that specializes in chromatography and mass spectrometry solutions for pharmaceutical quality control.
The details
The software integrates into the existing Empower platform to streamline chromatography—a laboratory technique used to separate and identify components in a mixture. It uses machine learning models trained on site-specific data to autonomously identify and edit baselines or strip out signal noise. By performing these repetitive adjustments, the software shifts the operator's role from data entry to exception management.
Timeline
2025: Internal pilot study conducted with a global pharmaceutical partner.
2026: Customer evaluation of the software tool.
December 2026: Early customer access availability.
Mid-2027: Planned release for validated, compliant deployment.
The Tech Race
This integration moves the Empower platform toward fully autonomous laboratory workflows, competing with broader industry efforts to automate pharmaceutical quality control. It marks a significant shift in data integrity tools by moving from rule-based automation to adaptive, laboratory-specific machine learning models.
Lab technicians and quality control teams can expect to see reduced manual workload as the software begins early customer access in December 2026. The tool will eventually require a transition to a validated, compliant environment, expected to reach full commercial deployment by mid-2027.
The takeaway
This automation tool signals a shift toward AI-assisted data review as a standard in pharmaceutical manufacturing. Interested teams should watch for the mid-2027 validated release, which will serve as the benchmark for integrating these models into regulated, compliant workflows.
What happens next
Early customer access is scheduled for December 2026, with a full rollout of the validated and compliant software deployment targeted for mid-2027.
Further reading
Learn more about Artificial Intelligence developments impacting industry standards and data automation.
Source note: This article includes information reported by TokenPost.
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