Sapio Sciences announced the availability of Exemplar Biomarker Discovery LIMS. This release is the result of Sapio’s extensive experience in implementing LIMS with biomarker discovery at leading pharmaceutical and biotech companies. Exemplar Biomarker Discovery addresses these clients’ needs for a single, integrated solution to a breadth of requirements.
It has been known that the idea that a “one size fits all” application of a drug to a disease is not practical. Each person has a unique response to a medication that will determine whether that particular drug will work for them or not. Ideally, certain biological markers, a.k.a. biomarkers, would be known that could be measured and used to predict the efficacy of any particular drug for a particular patient. This is the promise of personalized medicine.
With advances in genetics, genomics, proteomics, and metabolomics over the last two decades, it is now possible to perform detailed profiling of study subjects’ response to treatments. The proper tracking and interpretation of this data can lead to the aforementioned desired patient profiling for a particular drug to have the best chance of success.
Proper interpretation of this data can also lead to the success or failure of a drug in clinical trials. Certain drugs may appear ineffective, but in fact are working for a small subset of the patient population with some combination of biomarkers. If these markers could be discovered, then the patient population can be preselected for suitable candidates, and the drug trial has a greater chance of success, whereas it may fail without such a predictor in place.
While the promise of personalized medicine is great, little actual progress has been made. One of the major reasons for this is the lack of tools to help manage the diverse and voluminous study data, and to interpret that data. At most companies this important data is spread across the organization in various applications, data stores, and spreadsheets. This means that making discoveries becomes extremely costly, time consuming, and sometimes impossible because of the lack of a single integrated view of the data.
Companies developing pharmaceuticals need to be able to track samples in the sense of traditional LIMS applications, but also want to be able to track treatment regimens, subjects and their phenotypic attributes, and assay data. Within the same application there is also the need to take this aggregated data and perform data mining queries and statistical analysis on it.
A comprehensive Biomarker Discovery application should include all of the following:
• Flexible data model to adapt to client data tracking needs
• Sample Management including storage management, derivative\aliquot creation, mass\volume\slide\concentration tracking
• Tracking of Studies, Treatment Groups, Subjects, Samples and Assay Data
• Data Loaders for common assay types such as PCR, RPPA, FACS, Western Blot, etc.
• Data Loaders for standardized formats such as SDTM
• CRO data interaction template creation and loaders
• Highly scalable Assay Data Management
• Assay Data QC
• Built-in and easy to use data mining tools
• Custom statistical algorithm implementation support. e.g. – Data Normalization, Delta CT, etc.
• Built-in informatics tools
• Workflow Driven
• Integrated and robust Application Programming Interface
Exemplar Biomarker Discovery LIMS addresses each of these needs while allowing for configuration/customization meeting each company’s specific requirements.