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  • In the News
  • Dr. Claire Frazer’s lab at the Institute for Genome Sciences at UMAB Medical Center has licensed Exemplar LIMS Read Article.
  • ExonHit Selects Exemplar LIMS. Read Article
  • Childrens Hospital of Pennsylvania Selects Exemplar LIMS. Read Article
  • Sapio Sciences Announces Exemplar LIMS Version 2 Read Article

Modern pharmaceutical and non-commercial laboratories often have to track many important data items relating to the hundreds or thousands of samples they process annually. This can include:

  • The results of an experiment on a sample such as:

    • SNP's calls, which can number in the millions for each sample
    • Gene Expression values
    • Proteomic values
    • Metabalomic values
    • Sequencing values
  • Documents relating to the sample(s), such as:

    • Image files
    • Work documents like consent forms, etc.
    • Vendor produced files like Affymetrix CEL files

Exemplar LIMS allows for the seamless loading of experimental results and can easily scale to handle millions of data points for each of tens of thousands of samples. Exemplar associates the data with the proper sample and allows for viewing of the data within the LIMS. Importantly, Exemplar LIMS allows the LIMS user to create point and click generated queries to export the data based on phenotypic or clinical data from the underlying sample. As an example, the researcher may want the following request fulfilled:

"Send me a file formatted for use with analytics tools that only has the data for the samples who were males under the age of 55 and non-smokers."

With Exemplar, this request can be fulfilled in minutes with our powerful query engine and intuitive design.

Exemplar also allows for documents of any type to be uploaded to the LIMS DB and associated with the proper sample. Furthermore, Exemplar users can easily add any forms and data fields to these attachments to describe them in as much detail as they would like. This is accomplished with no programming by authorized users and the new fields will automatically be applied to existing data and will be immediately available throughout all features of the LIMS.