Efficiently Following the AMP Guidelines with VSClinical and Golden Helix CancerKB

About this webinar

Recorded On: Wednesday, September 11, 2019

Interpreting somatic variants for the clinical genetic testing of tumors requires hands-on time of the most skilled clinical lab personnel. Various clinical and genomic sources must be queried, papers and guidelines referenced, and an evaluation of the clinical actionability of the mutation determined by the following the AMP guidelines. Yet, there is tremendous potential for reuse of this time consuming and valuable work!

Earlier this summer we launched our VSClinical AMP Guidelines workflow which integrates a lab-specific knowledgebase that saves every biomarkers interpretation in up to seven different snippets that are reusable across various genomic and clinical contexts. Furthermore, our cancer workflow is bundled with the Golden Helix CancerKB, our expert-curated interpretations of the most common biomarkers for the most common cancer types, reducing the time to your first precision medicine report.

Join us as we cover:

  • The interpretation of clinically actionable biomarkers for targeted molecular therapy and diagnostic/prognostic clinical reports for cancer
  • The different levels and scopes of re-use of the interpretation for each biomarker
  • Saving, re-using and updating these interpretations over time by multiple users within a clinical lab with an integrated lab-specific knowledgebase
  • The built in Golden Helix CancerKB that provides default interpretations for most cancer genes, biomarkers and many clinically actionable Tier I/II drug sensitivity and resistance interpretations.

In the world of genomics shaping precision medicine in oncology, the limiting factor is the time-to-sign-off on fully interpreted molecular profile reports.

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Find out how Golden Helix software enables users to harness the full potential of genomics to identify the cause of disease, improve the efficacy and safety of drugs, develop genomic diagnostics, and advance the quest for personalized medicine.