Automating data processing and analysis with Mnova Gears

Significance of the topic

Modern NMR and MS platforms deliver unprecedented sample throughput through high sensitivity, rapid methods, and automated sample changers. However, accelerating data acquisition shifts the main bottleneck to data analysis. To support end-to-end high-throughput workflows, robust automation software is essential for handling large volumes of analytical data.

Objectives and study overview

This article introduces Mnova Gears (MGears), a modular automation framework built on the Mnova platform. It aims to decompose complex analytical workflows into reusable core and peripheral components, enabling both sample-level and batch-level automation across diverse laboratory contexts.

Methodology and instrumentation

Core workflow tasks are broken into minimal reusable units (“bricks”), such as spectral assignment and concentration calculation. Peripheral functions include data selection, grouping, reporting, and review. Workflows operate either at the individual sample level via MyGears or at full batch level via MGears. Instrumentation referenced includes Agilent Rapidfire and Bruker Samplejet for sample handling, while automation relies on the Mnova scripting engine and API for plugin control and custom script integration.

Main results and discussion

MGears provides a palette of preconfigured bricks with sensible defaults, simplifying setup of complex analyses. Sample automation (MyGears) supports template-based processing and reporting, ideal for moderate throughput needs. Full batch automation extends this by offering file-system or database-driven data discovery, real-time data handling, and master-file fallback. Review-by-exception strategies are supported via an intuitive review interface or interactive HTML reports. Custom scripting hooks at each stage ensure adaptability to nonstandard requirements.

Benefits and practical applications

• Reusable building blocks accelerate workflow deployment across NMR/MS applications
• Flexible configuration addresses both small-scale and high-throughput laboratories
• Separate MyGears licensing offers cost savings for limited automation needs
• Scriptable modules enable integration with external systems (e.g., REST services, LIMS)

Future trends and opportunities

As analytical laboratories continue to scale, we anticipate deeper integration of automation with LIMS and ELN systems, expansion of AI-driven data processing bricks, cloud-based batch pipelines, and community-driven libraries of custom modules. Enhanced interoperability and standardization will further streamline end-to-end analytical workflows.

Conclusion

MGears delivers a versatile, reusable automation framework that addresses the evolving bottleneck in data analysis for NMR and MS. By modularizing core and peripheral functions within Mnova, it enables laboratories to implement scalable, adaptable sample and batch workflows while maintaining familiar user interfaces.

References

No references were explicitly provided in the source text.