The Ingenuity Variant Analysis web application, which is currently available in limited access, enables researchers to rapidly weed through millions of variants to identify a few causal variants based upon known relationships with pathways, genes, biologic processes, and diseases.
Ingenuity Systems (Redwood City, CA, USA), a provider of information and analysis solutions for life-science researchers, announced that Translational Oncology at University Medical Center Mainz (TRON; Germany) has used Ingenuity Variant Analysis to identify cancer driver variants that inform on the development of a research customized RNA-based therapeutic agent.
“Individualized therapy development is about speed and accuracy. As scientists and clinicians explore new avenues for truly individualized cancer therapy and personalized medicine, it is critical to have tools that help us quickly prioritize cancer driver variants for treatment of a particular patient,” stated John Castle, co-head of the TRON Biomarker Development Center. “Ingenuity Variant Analysis helped us identify 30 compelling tumor-specific variants in record time that we then used to inform our first experimental therapeutic RNA cocktail.”
“TRON researchers are pioneers in the application of NGS technology,” said Doug Bassett, PhD, chief scientific officer and chief technology officer, Ingenuity Systems. “This is a promising approach that could provide a potent new weapon in the fight against cancer, training patients’ own immune systems to fight tumor cells. We are proud that Ingenuity Variant Analysis is able to play a critical role in the fight against genetic disease.”
Ingenuity Variant Analysis is a web application that enables researchers to identify causal variants from human resequencing data in just minutes using known information about the biological effects of variants. Ingenuity Variant Analysis uses the accurate, curated biologic content in the Ingenuity Knowledge Base, plus many additional sources of variant-level content, to help researchers studying genetics and disease biology quickly sift through millions of variants to identify a few causal variants based upon known relationships with pathways, genes, biological processes, and diseases.
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