Next-generation sequencing (NGS)-based diagnostics have demonstrated clinical utility in predicting survival benefits of targeted treatments in various cancer types. Tertiary analysis is a critical component in NGS workflow, but its efficiency and accuracy have remained as the main challenges. Herein, we developed Vela Analytics, a web-based software, that automates NGS data interpretation and reporting to facilitate timely clinical decision-making.
Clinical samples and commercial reference standards were analyzed using OncoKey SL60/525 Plus assays. The sequencing files were then analyzed using Vela Analytics, which utilizes the Vela Knowledge Base integrating information from FDA/EMA-approved labels, NCCN/ESMO-established clinical practice guidelines, registered clinical trials, and public data sources. Reports were generated through matching variants with the Knowledge Base.
Reporting and interpretation of SNVs, INDELs, CNVs, fusion genes, MSI, TMB and oncogenic pathogens from OncoKey Plus assays were completed within 2-10 minutes. Fourteen actionable variants with 13 matched therapies and 185 clinical trials were identified in C3 reference standard (Horizon) and categorized into Tier I based on their strong clinical significance. Two immunotherapies were recommended based on MSI-High and TMB-High statuses detected. Reporting of therapies was customized for regions following ESMO or NCCN guidelines. The software interpreted HPV 16 findings in a head and neck sample with its clinical implications. There were no approved therapies targeting the detected variant PIK3CA R88Q. However, 11 active matched clinical trials suggested possible treatment benefits from investigational therapies.
Vela Analytics can efficiently and accurately provide clinical insights through identifying actionable genomic alterations and oncogenic pathogens, reporting up-to-date therapies and clinical trials, providing comprehensive literature interpretation, and categorizing variants according to AMP/ASCO/CAP guidelines.
Vela Genomics.
Has not received any funding.
Y. Yu, O. Scully, T. Zhang, Z.H. Kyaw, V.Y. Chung, D. Tay, C. Lee, P. Ariyaratne, M.K.K. Aye, M.Q. Yee, Y.L. Kok, E. Wee, C. Lee: Full/Part-time employment: Vela Research Singapore Pte. Ltd.