The Next Generation Sequencing market is growing at a rapid rate. Fortune Business Insights said the market was at $6.3 billion in 2018 and will surpass $31 billion by 2026, with a third of this market from NGS services. Contributing factors to this growth include drug discovery applications, diagnostic tests based on sequencing, and a rapid pace of new test kits and testing services.
Challenges of Genomic Testing
The rapid growth of the NGS market is not without challenges. Some examples include:
- The amount of data being produced daily in genomics is doubling every seven months. Within the next decade, genomics is expected to generate between 20 exabytes to 40 exabytes per year. For reference, one exabyte is the size of approximately 366 billion digital pictures with an average file size of three megabytes.
- With the evolution of the NGS industry and continual regulations, reimbursement has become increasingly more tied to clinical utility. Today, however, fewer than 200 CPT codes exist for about 70,000 genetic tests, leaving no straightforward way to bill from any tests or for payors to identify what genetic tests were given.
- The rapid rise in genomic testing affects physicians, who may not have the time to keep up with the latest diagnostic test available.
- For NGS labs, ensuring that the streamlined workflow incorporates genomic data in the right places and at the right time is critical. However, many data systems, including those that house patient’s genomic data, are siloed. These systems include EHRs, sequencing platforms, bioinformatics solutions, spreadsheets, and laboratory information systems.
Key LIS Capabilities for NGS
For your lab to launch next-generation sequencing, it is critical to have a strong NGS reimbursement strategy, along with an NGS-specific LIS strategy.
According to Joe Nollar, XIFIN AVP, LIS Product Development, who leads the development of XIFIN's LIS solution, labs understand the profitable opportunity NGS offers. Still, they are struggling with fully understanding the environment, the investment, and getting reimbursed.
“Ultimately, successful execution of an NGS strategy requires an LIS that is flexible and addresses key requirements,” said Nollar. Those critical requirements include:
“An LIS purpose-built to support these requirements is a linchpin to a successful NGS program,” he said.
Along with the technology side of NGS, there are analytics applications, like AI-driven genomic interpretation from Fabric Genomics, which supports known reimbursable NGS assets and offers an analytics package that can be added to the LIS relatively easily to do analysis and report on those reimbursable assets.
The Requirements of a Scalable NGS Reporting System
Successful NGS testing with LIS-integrated analytics lets the lab take advantage of improved case throughput, batch processing, quality control, reporting, and billing. The NGS space is relatively new and rapidly changing — especially within a clinical context — so flexibility and choice are critical for both the LIS and bioinformatics aspects of NGS. This means handling copious amounts of rapidly evolving data not just from the test itself but from supplementary databases used in test interpretation.
“In addition, a multitude of sources, such as literature searches and patient and family member metadata, may need to integrate in real time,” said Brent Lutz, Director of Product Manager, Fabric Genomics. “You also need the ability to change and control your workflow and then automate those workflows to minimize errors. The ability to integrate artificial intelligence (AI) is essential. Fabric Genomics has been a leader in introducing AI technology to help speed the process of finding that needle in a haystack of mutations, which helps you finish reports faster.”
Lutz said that interpretations can take a very long time. A host of different types of information must be fed into the system so geneticists can adequality determine whether thousands of mutations are relevant to a particular case. In this example, AI helps speed up the process. Instead of spending hours, interpreters are using AI to get their work done in minutes.
“AI is used to replicate what clinical geneticists would do, but before AI, it would take them several hours," Lutz said. “We're shortening that cycle and then allowing geneticists to maximize their knowledge base and scale their capability to generate reports faster. In the context of our system, that's what we're doing with AI and NGS.”
When it comes to reimbursement, Lutz said his company offers expertise when it comes to performing a panel of tests. For example, in NGS, running a whole genome or exome translates into running and sequencing thousands of genes, which all may not be reimbursable. It can be costly to sequence all of them and do the bioinformatic analysis and reporting, as well.
“There’s just a couple of mutations in one or two genes that might be relevant for a patient,” Lutz said. “And you want to focus on those. Usually, doctors will have a phenotype from a patient of a disease state, so they want to make clear that they're doing the test in the context of that phenotype. That helps confine the cost of NGS and then also helps to focus where the reimbursement should go.”
Finally, integrating NGS testing and associated analytics into your LIS lets labs take advantage of improved case throughput, batch processing, quality control, reporting, and billing.
About The Experts
Joe Nollar, AVP, LIS Product Development, leads the development of XIFIN's LIS solution. He has nearly 20 years of experience designing laboratory systems.
Brent Lutz, Director of Product Manager, Fabric Genomics, is an accomplished product leader with 14 years’ experience building and commercializing automation systems for molecular biology and diagnostic applications.