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As gene panels increase in size, comprehensive genomic profiling and variant interpretation becomes more complex and time-consuming, which places tremendous burden on labs needing to scale and grow case volume. QIAGEN Clinical Insights (QCI) Interpret for Oncology is a clinical decision support platform powered by augmented molecular intelligence that enables rapid, evidence-powered comprehensive genomic profiling at scale. QCI Interpret for Oncology is supported by the world\u2019s most comprehensive, manually curated knowledge base and dynamically computes variant classifications according to AMP\/ASCO\/CAP and ACMG\/AMP guidelines with transparency. Users also get access to over 500,000 pre-formulated, oncologist-reviewed variant interpretation summaries and can build customizable, oncologist-ready reports with the latest diagnostic and prognostic information, as well as biomarker-directed therapeutic information and clinical trial recommendations. With its latest release, QCI Interpret for Oncology adds several new capabilities that further enhances the platform\u2019s scalability and flexibility, and enables users to significantly reduce variant research and review time.<\/p>\n

In this webinar, attendees will learn how QCI Interpret for Oncology enables you to:<\/p>\n

Navigate from VCF to final report with speed, precision, and confidence;<\/li>\n
Easily issue report addendums without the need for re-running a VCF;<\/li>\n
Streamline structural variant filtering based on user set thresholds and hence reduce the time and effort needed to eliminate noise and identify truly relevant variants for reporting;<\/li>\n
Utilize built-in AI capabilities to identify all the literature, case reports, drug therapies, and clinical studies relevant to a patient\u2019s tumor type with just one-click.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"As gene panels increase in size, comprehensive genomic profiling and variant interpretation becomes more complex and time-consuming, which places tremendous burden on labs needing to scale and grow case volume. 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