Using Golden Helix CancerKB to Accelerate NGS Cancer Testing

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About this webinar

November, 17 2021

Presented By: Julia Love, Product Quality Manager and Genomic Curator 

Next Generation Sequencing is being rapidly integrated into the oncology field. From the clinical perspective, both somatic and germline NGS results are informative for hereditary cancer risk and treatment strategies. There are numerous scattered resources that inform the clinical significance of a somatic mutation for a patient’s tumor type. Similarly, there are many FDA-approved anti-cancer agents and drugs with changing indications, and opportunities for off-label use. Even more, there are clinical trials all over the world that though they require specific genetic alterations for enrollment eligibility, they could provide more treatment options for cancer patients. 

What’s the bottom line? It is certainly a huge undertaking to evaluate a gene or biomarker’s role in cancer or clinical significance. It requires sifting through trials that are relevant for the patient from the abundance of literature available, not to mention staying well-informed on new research as it is published. 

Golden Helix CancerKB offers a solution. In this upcoming webcast, I plan to demonstrate the application of CancerKB and how easy somatic variant analysis can be in VSClinical. Namely, I will deep dive into the following topics: 

  • The process our expert curators use to produce high-quality cancer interpretations
  • Examples of complex biomarker interpretations simplified using CancerKB 
  • Report content filled in by CancerK, even for rare genes  
  • Integrating customer feedback and the future of CancerKB  

As the CancerKB team lead and Product Quality Manager at Golden Helix, I am very excited to host this webcast where I can elaborate on the value of CancerKB and how it can streamline your cancer variant analysis. I hope you all will enjoy this exciting webcast!

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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.