Clinical NGS Process Report

The impact of next-generation sequencing on genomic medicine is tremendous - the success of the first era of the human genome revolution created a stable foundation for today’s discoveries. Technology development has allowed us to sequence and uncover mutational events at unprecedented scale and facilitates linking genomic data to high quality clinical data and diagnosis.

As a result, data management and genomic analysis tools are rapidly developed - a critical necessity to manage and make sense of the data to benefit research, the drug discovery process, and, of course, the clinic. Adoption and implementation of NGS and genomics discovery technologies have advanced clinical assessment of genomic alterations associated with oncology, hereditary cancer, cardiology, pediatrics, rare disease, among others.

The next logical goals for NGS solutions, besides risk detection and disease identification, are disease prevention and management. The multi-faceted, complex Clinical NGS Workflow demands powerful, yet user-friendly, solutions across the entire process.

The complex NGS technology bears many challenges beyond overcoming hurdles such as regulatory oversight, reimbursement challenges, or educating the physician/clinician on the benefits of this powerful enablement. While data production is not a challenge anymore, and targeted panels are well adopted, the expected dramatic rise in whole exome and genome sequencing will result in unforeseeable quantities of data at the clinical level that need to be managed, understood, and communicated. Low-cost sequencing of whole genomes, at population scale is already in existence, but not yet widespread in the clinic, as we are still unable to fully interpret what most of the observed changes at the genome level mean, and how they explain an existing phenotype.

Scalable, fully automated analysis and knowledge extraction solutions incorporating rich annotation information are necessary to overcome these challenges. Over time, the clinical variant-to-gene-to-disease knowledge will become available for interpretation, requiring correct, complete, and integrated content for expedited knowledge extraction. With rising, massive quantities of NGS data (linked to different types of data), artificial intelligence and machine learning are hailed as pivotal solutions to address the data interpretation and knowledge extraction challenges and advancing the application of NGS in the clinic.

In line with this demand, the sequence data analysis, knowledge extraction, and clinical reporting space is rich with commercial platforms and software solution providers trying to address this need via a multitude of offerings. Some of these commercial solutions support or overlap with clinical NGS workflow components or features, while others differ substantially in their inherent capabilities. This creates a competitive environment, which presents challenges to the end-users and different organizations seeking the appropriate product for their specific clinical NGS workflow needs. While commercial companies struggle with understanding the competitive landscape or how to best partner for a successful product and business strategy, this report clarifies similarly aligned solutions providers and those providers whose technology may fill a current gap in a company’s portfolio.

Clinical end-user interviews pointed out the challenges associated with received clinical testing results that includes limited annotations, particularly when it comes to VUSs (variants of uncertain significance) and communicating those results to the patient and physician.

The Clinical NGS Workflow Report examines the clinical NGS process and includes a review of the clinical end-users, the current market trends, players across the data analysis and interpretation part of the workflow, their offerings, funding situation, strategic partnerships, mergers and acquisitions, number of patents, and a comparative analysis of a range of capabilities that uniquely address different components across the data analysis and extraction process. This deeper analysis uncovers differences in product characteristics related to data processing, analysis, knowledge extraction and reporting of findings (including type of content integrated for meaningful extraction), and compliance and security mechanisms. Both clinical end-users and commercial companies who require insight into this expanding industry and its providers and products will benefit from our critical, investigative report.

A set of commercial companies was analyzed revealing top players across the entire Workflow: Bluebee, DNAnexus, Edico Genome, Illumina (with BaseSpace), Lab7 Systems, and Seven Bridges Genomics are leading the group with different fast and secure data processing platforms and implementations; Agilent (with Alissa Clinical Informatics), Congenica, Fabric Genomics, Golden Helix (with VarSeq), PierianDx, Sophia Genetics, Station X, Sunquest, Qiagen, and WuXi NextCODE are among the top players on the knowledge extraction and clinical reporting side, integrating and providing different types of content for data interpretation; while Ambry Genetics, Blueprint Genetics, Color Genomics, Fulgent Genetics, Foundation Medicine, Myriad Genetics, and Invitae were the primary choices of genetic testing labs as indicated by clinical end-users.

While this report does not intend to provide direct recommendations on commercial offerings, the deep-dive analysis is an insightful review to help clinicians, researchers, commercial entities, and investors choose the best partner for success.