Agilent Technologies Inc. (NYSE: A) today announced an agreement for global distribution of Cartagenia’s cloud-based software for copy number variation (CNV) analysis. This agreement will enable Agilent to sell usage-priced annual licenses for Cartagenia’s Bench Lab CNV module to small and medium-sized cytogenetic laboratories. The use-based licenses allow labs with limited budgets and little or no bioinformatics resources to gain access to a powerful interpretation support module to draft clinical grade reports.
“Cartagenia is pleased to work with Agilent on this distribution agreement of our Bench Lab CNV module,” said Herman Verrelst, chief executive officer, Cartagenia. “Patient-centric interpretation of microarray data can be greatly facilitated by adopting automated data analysis pipelines and workflows, increasing lab efficiency.”
“With expanded distribution capabilities, we can now reach small- to medium-sized labs more efficiently and provide them with our data analysis platform,” Verrelst added. “The CNV module is a proven platform, offers standardized workflows, and automated SOPs for fast turnaround times. Since it is a cloud-based platform, it allows for rapid installation, integration with legacy data, and provides labs with greater access to our product without adding bioinformatics resources.”
Cartagenia supplies interpretation support software, database systems and related services to genetic labs and clinicians, enabling them to perform clinically relevant analysis of genetic findings quickly and efficiently.The Cartagenia Bench CNV platform is built in collaboration with genetics labs and clinical experts involved in routine medical practice. Because of this, Bench Lab CNV addresses the specific needs of genetic diagnostic labs and clinicians. “Agilent is the first worldwide reseller to offer the Cartagenia Bench Lab CNV, and we are excited to provide this solution,” said Jacob Thaysen, Agilent’s vice president and general manager, Diagnostics and Genomics Group. “Labs with minimal software budget and resources can now afford to implement proven, standardized processes to analyze, interpret, and report their CGH data and generate precise draft lab reports with minimal disruption to their analysis workflow and staff.”