Tailored for laboratories seeking precision, efficiency, and scalability, Chrom SST is the ultimate tool for streamlining data processing and generating AI-ready insights.<h5>Key Features:</h5><ul><li>Automated Data Processing and Analysis</li><li>Customizable and Re-usable Methods</li><li>Easy-to-interpret Pass/Fail Results</li><li>Compatible with Various Chromatography Systems</li><li>Supports Diverse Output Formats</li></ul><h3>Why Choose Chrom SST?</h3>Chrom SST transforms laboratory operations by centralizing data management and consolidating results from multiple instruments into a unified repository for seamless dashboarding and performance monitoring. It enables 24/7 operations and scheduled tests - eliminating the need for human intervention and minimizing instrument downtime. Designed for scalability, Chrom SST ensures consistent performance across growing workloads, diverse instruments, and expanding teams.By adopting Chrom SST, laboratories can enhance efficiency and productivity while leveraging predictive insights to optimize instrument uptime and maintain uninterrupted operations.Learn more about <a target="_blank" rel="noopener noreferrer" href="https://mestrelab.com/main-product/chrom-sst?utm_source=adv&amp;utm_medium=labrulez&amp;utm_campaign=feb&amp;utm_term=chrom%20sst">Chrom SST</a> and <a target="_blank" rel="noopener noreferrer" href="https://www2.mestrelab.com/l/271522/2025-01-31/3thx58">request a demo</a> to see how it can revolutionize your lab operations.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Introducing_Chrom_SST_Automated_and_Accurate_Instrument_Performance_Insights_af0c39857d.jpg" alt="Mestrelab: Introducing Chrom SST Automated and Accurate Instrument Performance Insights" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Introducing_Chrom_SST_Automated_and_Accurate_Instrument_Performance_Insights_af0c39857d.jpg 245w," sizes="100vw" width="1920" height="1080">

Introducing Chrom SST: Automated and Accurate Instrument Performance Insights

Perhaps the most compelling reason to have <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1492">Chrom SST</a> is to have a dashboard that allows you to track performance across instruments over time, be alerted to any failures requiring action or even to allow preventative maintenance based on trends before an event happens.However, the exact requirements for a dashboard can vary greatly among individuals and companies. Everyone has a slightly different vision of what it should display and how it should appear. This is why many opt for business intelligence (BI) applications like Spotfire or PowerBI to build their dashboards. Indeed, this is the approach we have taken with Chrom SST – Mgears can write the Chrom SST results to a user-supplied database, and then tools like Spotfire can be used to connect to that, allowing users to create whichever visualizations they require. In other words, we focus on what we do best – data processing and analysis – and we integrate with those who excel at dashboarding and visualization.Connecting to a database is easily achieved using Mgears. You can write to most flavors of SQL databases, using a schema we have designed or any schema you require. As this is achieved via the script engine it can be customized as needed.<h4>The SQL plugin&nbsp;</h4>Mnova has a SQL plugin that allows connection to most used database engines such as SQLite, Oracle, Postgres, and MySQL. The SQL plugin acts as a bridge between Mgears and the database, facilitating the writing of results to your chosen database. BI tools like Spotfire readily connect to these standard database sources, so, once data is being written to the DB, connecting it to the data source is straightforward. &nbsp;<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_SQL_plugin_e0c300430d.webp" alt="Mestrelab Research: Mnova SQL plugin" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_SQL_plugin_e0c300430d.webp 245w," sizes="100vw" width="1379" height="365"><h4>Using an output script&nbsp;</h4>To write results to a database, we leverage Mgears’ capability to specify an output script that runs on every sample processed by the system. This allows us to tailor the behaviour of the database write to our exact needs.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Output_script_c7a78115da.webp" alt="Mestrelab Research: Output script" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Output_script_c7a78115da.webp 245w," sizes="100vw" width="967" height="547">The output tab allows an output script to be run on every sample processed – this is set up to call the script that writes to the database.&nbsp;<h4>The suggested schema&nbsp;</h4>Relational databases have a ‘schema’ – the tables and columns where data is stored within the database. We have designed a schema that allows the results of SST to be easily stored, along with an output script that writes the results to that specific schema. This provides an out of the box solution is available for writing SST results to a database. &nbsp;If you prefer to use a different schema, that is also possible. You can design your own schema and adapt the output script accordingly. You can of course use our schema as a template to refine the output to your needs.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_The_schema_used_in_the_out_of_box_solution_9b438e2260.webp" alt="Mestrelab Research: The schema used in the out of box solution." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_The_schema_used_in_the_out_of_box_solution_9b438e2260.webp 180w," sizes="100vw" width="1072" height="929"><h4>Creating a dashboard&nbsp;</h4>BI tools like Spotfire readily connect to standard database sources, so once data is being written to such a DB, connecting it to the data source is straightforward. The details are beyond the scope of this document, but many online tutorials show how to use this inbuilt functionality present in most BI tools. Below is an example of a dashboard created by a customer using Chrom SST and writing results to such a database. &nbsp;Users are free to create one or more dashboards, perhaps a high-level one to show overall status, and more detailed ones for each instrument showing history. Control charts of parameters like peak width over time are very useful in this regard as they allow preventative steps to be taken before specs fail. &nbsp;The limit is only your imagination (and the BI toll you choose!).&nbsp;<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Creating_a_dasboard_overview_543ebfc71c.webp" alt="Mestrelab Research: View in Spotfire showing overall status and control chart, created in Spotfire from data in the SST DB." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Creating_a_dasboard_overview_543ebfc71c.webp 245w," sizes="100vw" width="1280" height="422">

Making a dashboard with Chrom SST results

This case study examines how AstraZeneca integrated <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1492">Chrom SST</a> automation into their purification workflow, enabling daily checks, long-term trend analysis, and preventive maintenance. These advancements minimized downtime and ensured consistent system performance.<h4>Introduction</h4>In early drug discovery, Design-Make-Test-Analyze (DMTA) cycles generate thousands of molecules annually that require thorough analysis. For successful purification, these results must be high-quality, reproducible, and scalable. However, system downtime and the need for re-analysis can significantly slow down the process, making such delays undesirable.<h4>Problem Statement</h4>Manual processing of LCMS data is not only time-consuming but also prone to subjective interpretation. Small fluctuations in peak retention times (RT) are difficult to detect visually, often impacting reproducibility. Additionally, the complexity of ionization processes demands significant operator expertise, presenting further challenges in achieving consistent and reliable results.<h4>Methodology</h4>To address these challenges, AstraZeneca’s analytical and purification lab implemented automated SST analysis using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1492">Mnova Gears and Chrom SST</a>. Mnova Gears, deployed on a server, collects and aggregates raw data from multiple instruments several times a day. Chrom SST then automatically analyzes this data, comparing it against user-defined specification files to ensure objective and reliable results. Processed data is stored in a PostgreSQL database and visualized through Spotfire dashboards, providing a streamlined interface for trend analysis and system monitoring.<h4>Results</h4>The integration of automation improved result accuracy and reproducibility while enabling daily performance checks. The addition of advanced analytics and visualization tools supported long-term trend analysis and preventive maintenance, reducing downtime, and ensuring consistent purification performance.<blockquote>To get the full story, you can <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/4728">check the webinar here</a>.</blockquote>

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