Software accelerates screening for contaminants and illicit drugs

SCIENTISTS and lab technicians can now screen hundreds of samples for hundreds of potential contaminants and residues, using customised compound libraries, thanks to a new software application from AB Sciex.

LibraryView, when  coupled with QTrap and TripleTof mass spectrometry technologies, adds a new dimension of speed and reliability to screening workflows says the company.

From today, the software is available for evaluation from any location, using AB Sciex’s cloud-based virtual demo site.

This new application will enable faster and more reliable identification of contaminants in food, environmental, clinical research, and forensic toxicology samples, says the company.

LibraryView exploits the qualitative and quantitative functionality of QTrap and TripleTof mass spectrometry, enabling acquisition of full scan MS/MS spectra of compounds or contaminants present in a sample at high sensitivity.

The full MS/MS spectrum delivers all of the significant fragments of the compound of interest, creating a compound ‘fingerprint’.

It enables more reliable compound identification compared to standard identification with only one or two fragments or MRMs. Library searching against the full MS/MS fingerprint is said to produce more robust library comparisons and more reliable identification of compounds.

It also helps to minimise false positive identifications from sensitive samples.

LibraryView may be of interest to high-throughput labs wishing to improve workflows and processes, facilitating the creation of custom libraries with retention time information, LC conditions, and associated matrices.

Labs interested in smaller, more targeted compound screenings can establish custom libraries for that targeted list. For example, if a food or environmental lab is targeting a short list of pesticide compounds, LibraryView allows a custom library to be set up to search only for compounds of interest, eliminating the need to go through an entire, comprehensive library.

This should streamline data analysis, reducing processing and so boosting productivity.


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