Qiagen CLC Genomics Workbench 12; QCI Interpret Workflow; QiaAct Myeloid Panel

Qiagen has launched the new CLC Genomics Workbench 12 sequencing analysis software, which incorporates features of two previous Qiagen products: the CLC Biomedical Genomics Workbench and CLC Genomics Workbench. The new product features a streamlined and simple interface designed for scientists with any bioinformatics skill level, Qiagen said. The data footprint is reduced by more than half compared to previous products. In addition, an in-depth reference tool suite allows users to quickly start work on many commonly studied species and genomic panels, the company noted. Current users of the CLC Biomedical Genomics Workbench can choose to upgrade to the new product free of charge.

The firm also launched a new workflow for the Qiagen Clinical Insight Interpret web-based clinical decision support platform for hematological malignancies. Qiagen designed the workflow to work with the heterogeneous nature of and provide actionable information for the sub-classification and prognostic assessment of these malignancies, including leukemia, Non-Hodgkin's lymphoma, Hodgkin's lymphoma, and multiple myeloma. QCI Interpret draws upon the Qiagen Knowledge Base to evaluate genomic variants in the context of published biomedical literature, professional association guidelines (AMP/ASCO/CAP and ACMG/AMP), publicly and privately available databases, drug labels, and clinical trials.

Lastly, Qiagen launched the QiaAct Myeloid UMI Panel for the GeneReader NGS system. The panel covers 25 highly relevant genes and their variants, including single nucleotide variants and insertions/deletions of known significance to clonal myeloid malignancy. The gene targets have been thoroughly selected for their occurrence and relevance in myeloid malignancies as stated by international references and organizations, including the 2016 WHO classification categories, National Comprehensive Cancer Network, European LeukemiaNet, MPN&MPNr-EuroNet, and the European Society for Medical Oncology. Among the genes targeted are JAK2, CALR, IDH1/2, FLT3, KIT, SRSF2, and TP53.