Bionano To Accelerate Data Processing Solution For Optical Genome Mapping Workflow With NVIDIA

Bionano-to-Accelerate-Data-Processing-Solution-for-Optical-Genome-Mapping-Workflow-with-NVIDIA

Bionano Genomics, Inc. announced a collaboration with NVIDIA to develop an acceleration platform for use in Bionano’s optical genome mapping (OGM) workflow.

This collaboration is expected to significantly improve data processing speed while reducing the time and cost associated with secondary analysis of OGM data. The computation platform enables a small laboratory and information technology footprint, allowing rapid decentralised deployment.

By combining NVIDIA’s expertise in accelerated computing and the capabilities of the NVIDIA RTX 6000 Ada Generation professional GPU with Bionano’s knowledge in extraction, enzymatic treatment, and analysis of ultra-high molecular weight (UHMW) DNA molecules, the collaboration aims to develop on-premise and cloud-based solutions to keep pace with the anticipated data generation needs of high-throughput OGM workflows. The collaborative solution is projected to support the analysis of 96 cancer workflows or just over 300 constitutional whole genomes per week and be integrated with Bionano’s NxClinical software for variant interpretation and reporting.

“Bionano is focused on continuous upscaling of our end-to-end genome mapping solutions, and we see this collaboration with NVIDIA as an important part of that effort,” said Erik Holmlin, PhD, president and chief executive officer of Bionano Genomics. “We believe the solution we’re developing with NVIDIA will accelerate OGM analysis and enable future expansion into areas including CAR T-cell therapy research and bioprocessing.”

“Bionano’s optical genome mapping platform provides the tremendous capability for genome-wide structural variant detection, which can have a huge impact on cancer research and other areas of human health,” said George Vacek, global head of genomics alliances at NVIDIA. “By accelerating Bionano’s analysis, we will help achieve higher throughput in a smaller footprint at lower cost, enabling the application of this technology to new areas, both at scale and in smaller labs.”