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SCIEX OS Software 1.5 Release: New Features Enhance Productivity

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More samples. Shorter deadlines. Extra assays. The continually increasing demands of a relentless and fast-paced work environment challenge even the most well-equipped analytical mass spectrometry laboratories. SCIEX OS Software handles it all. With the SCIEX OS Software 1.5 release, new advances in quantitative and qualitative data processing and data acquisition streamline your workflow and improve productivity even further than before.

Overview of New Features
Productivity drains can lurk anywhere. Processing methods need to be created. Outliers need to be flagged. Data needs to be reviewed. Even the smallest tasks can undermine your overall productivity. The new SCIEX OS Software 1.5 release is here to help. Now you have the capability to import data processing parameters directly from MultiQuant™ Software. Custom flagging rules can be created to ensure all outliers are immediately spotted. Data can be acquired directly to a network drive and immediately reviewed with one click. These features and more are available with the new SCIEX OS Software 1.5 release.

Table 1: New features within the SCIEX OS-MQ, SCIEX OS-Q, and the SCIEX OS versions of the 1.5 release enhance qualitative and quantitative data processing and data acquisition.

A Closer Look at What’s New

  • User-Defined Flagging Rules and Calculated Columns – Data isn’t always perfect. Low signal, interferences, and contaminants can challenge even the best data processing tools and well-thought-out methods. Now with the SCIEX OS 1.5 release, your data processing can adapt to each unique situation and identify failed data more quickly, without having to change the entire processing method. With the 1.5 release, you can now create custom flagging rules to flag, or highlight, the ion ratio, accuracy, calculated concentration and integration values that fall outside of the set processing method criteria. These are included in the method, so they are applied on processing, thus speeding up data interrogation.

Additionally, new custom calculated columns can be added to the Results Table by selecting functions, columns, and regression parameters in the formula editor.

Results can be flagged on any column, including the custom column, based on criteria such as a minimum or maximum value, a range, a mean, or a standard deviation. Results below the specified value are shown in blue while results above the specified value are shown in red, making it immediately obvious which samples may be problematic and why.

Figure 1. Custom flagging rules allow outliers to be instantly identified. Blue indicates a value below a specified value and red indicates a result above a specified value.

  • Import of Integration Parameters – Creating new quantitation processing methods is a necessary task, but it takes time. Now you can save time by importing processing method parameters directly from MultiQuant into SCIEX OS 1.5 Software. The component list, integration parameters (for MQ4 and Summation integration algorithms), and regression parameters can all be imported. You can choose to import just the components or the components and the integration parameters. This feature facilitates the conversion of MultiQuant software processing methods, the use of MultiQuant methods as the basis for new methods, and the transfer of methods from one processing computer to another.

Figure 2. In addition to text file import and importing components from a library database you can now import quantitation method parameters from MultiQuant Software into SCIEX OS.

  • Reportable Results – Don’t like the looks of something? Don’t include it. Now in the Result Table, in either sample or component view, you can select the results to be included in reports, exports, and LIMS transfers. Simply uncheck a row to have it excluded from the report.

Figure 3. Reportable results functionality offers greater flexibility to include and exclude results for reporting.

  • Direct Link to Data Explorer – You’re reviewing your data, and something looks interesting. With one click, you can open the Explorer workspace to view the peak currently shown in the Peak Review pane of the Analytics workspace. In Data Explorer tools are available that allow you to further interrogate your data such as performing structural elucidation.

Figure 4. A direct link from Analytics to Data Explorer allows currently viewed data to be further interrogated within Data Explorer.

  • Network Acquisition Support for X-Series QTOF MS Systems – Transferring files to and from a network drive is just one more drain on your overall productivity. For X500 QTOF Mass Spectrometer Systems, projects can now be stored on a network resource, data can be acquired directly to a network resource, and you can process data stored on a network resource. This allows for a flexible yet secure means of data management, sharing, and archiving. Project folders reside in network locations for easy data access between processing workstations. Instrument parameters and backup files reside on the local root directory. And file transfer occurs in the background. By centralizing data, this feature facilitates data sharing and backup. If a network interruption occurs, don’t worry. Data acquisition continues locally, and the data is transferred to the network when it becomes available.
  • LC Pressure Trace – LC pump pressure traces for Shimadzu and Agilent HPLC systems are now stored in the data file for X500 series systems, and they can be viewed in the Explorer workspace. This is extremely useful for troubleshooting and quality purposes. For instance, a pressure increase can indicate that it’s time to replace an analytical column.
  • Harvard Syringe Pump Support – SCIEX OS 1.5 now supports additional models of the Harvard syringe pump. X500 system users can now use the Harvard Pump 11 Elite (single and dual), Harvard Pump 22 and Pump 11 Plus, and the Harvard Ph.D. Ultra.

More samples? Shorter deadlines? Extra assays? No problem. The new performance-enhancing features within SCIEX OS 1.5 Software allow you to streamline data acquisition and improve data processing efficiencies making data mining simpler and faster. You asked, we provided. Productivity enhanced.


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