How variant surveillance could drive a sequencing boom
Infrastructure to monitor SARS-CoV-2 mutations could pay dividends for AMR, cancer and the next pandemic
Infrastructure to monitor SARS-CoV-2 mutations could pay dividends for AMR, cancer and the next pandemic.
The push to keep up with COVID-19 variants could be the inflection point that turns genomic sequencing from a sophisticated technique into a widely accessible tool, with companies in the driver’s seat focused on automation.
The global marshaling of next-generation sequencing (NGS) infrastructure to monitor mutations in the SARS-CoV-2 genome is the latest example of how the pandemic is reshaping the diagnostics industry by blurring the boundaries between individual diagnostics and public health research, and widening the scope of where testing happens.
The transition is facilitated by plug-and-play NGS workflows, which are democratizing processes that used to require experts.
“There’s a whole ecosystem of companies that are well poised to make this a reality that wasn’t as possible before,” said Dylan George, VP of technical staff at the national security-focused VC firm In-Q-Tel. “We’re now getting to the point where we can deploy these capabilities across broader jurisdictions.”
With escape variants on the rise, governments are making viral genomics surveillance a top priority, creating new opportunities and challenges as existing NGS labs scale up their throughput, and labs that previously lacked NGS capabilities start taking them on.
Beyond tracking SARS-CoV-2 variants, more NGS capacity means greater ability to conduct multiplexed assays that distinguish COVID-19 from other respiratory infections; identify cases and molecular mechanisms of antimicrobial resistance (AMR); and conduct pathogen-agnostic surveillance to monitor for the next pandemic.
The benefits could even carry over into oncology, where the success of precision medicine hinges on embedding NGS testing in routine care.
But the bolus of government funding will be challenging to digest. On Feb. 17, the Biden administration announced an almost $200 million down payment to expand the CDC’s pathogen genomic surveillance capability; since then, Congress has increased that number to almost $1.8 billion via the appropriations process, said George.
“We’re taking a program that used to be $30 million per year to potentially $1.8 billion,” he said. “I think of it as trying to get a watermelon through a straw.”
“I think of it as trying to get a watermelon through a straw.”
That strain is starting to be felt by companies supplying enabling technologies.
“We’re getting to a situation where our capacity might become the bottleneck. We’re booking for one to two quarters down the road,” said Clear Labs CEO Sasan Amini. Last May, the food safety genomics company raised an $18 million round led by Redmile Group to take its automated NGS platform into COVID-19 testing.
Other questions include whether and how pathogen sequencing information — traditionally the domain of public health officials — gets returned to clinicians and patients; how sequencing data will be structured and accessed, depending on its use case; and who will pay for sequencing as NGS tests take on dual surveillance and diagnostic functions.
“There is a commitment to fund surveillance activities, but how that will be operationalized, that needs to be determined,” said Robert Schlaberg, CMO of metagenomics company IDbyDNA Inc.
Sequence of information
Similarly to how the prevalence of asymptomatic COVID-19 transmission has eroded the distinction between diagnostics and screening tests, the rise of concerning variants is creating pressure to break down the silos between diagnosis and surveillance.
Diagnostics for individual symptomatic patients have long dominated the testing industry. Screening tests to detect disease in asymptomatic individuals, which have historically been limited to a handful of diseases and high-risk populations, are now gaining parallel momentum from COVID-19 and early cancer detection.
Pathogen genomic surveillance sits even further outside the clinical testing paradigm. It is typically only done for a fraction of virus-positive samples, has long turnaround times, and results are not communicated back to the patient.
But as more information emerges on the effectiveness of COVID-19 therapies against different variants, knowing which strain a patient is infected with could become critical for managing care. By incorporating NGS data into clinical care, infectious diseases could “follow in the footsteps of oncology” by adopting a precision medicine model, and align surveillance with diagnosis, said Schlaberg.
“We’re talking about using genomic methods to combine these two activities,” he said. “This is the major efficiency gain and paradigm shift possible with genomic methods.”
Schlaberg said NGS could also replace the array of testing modalities currently used to guide treatment for bacterial infections by determining antibiotic susceptibility, while contributing to public health monitoring for AMR. “It allows for the consolidation of technologies, and reduction in resources needed.”
“It allows for the consolidation of technologies, and reduction in resources needed.”
Bridging the surveillance-diagnostic divide will require regulatory frameworks and public health guidelines on the two-pronged use of sequencing information. The liabilities created by this gap were made clear early in the pandemic, when a University of Washington lab conducting an influenza surveillance study decided to inform individuals infected with SARS-CoV-2 of their results, despite lacking authorization to do so.
George thinks one way to navigate this challenge is to adopt a “blanket CLIA approval” model piloted by states including Massachusetts and Rhode Island, which enables sites not officially set up for diagnostic testing to return results to patients.
Combining surveillance and diagnostic functions also raises questions about who will pay for NGS tests. While public health agencies generally pick up the tab for surveillance, using the same tests for diagnosis pulls them into the realm of healthcare payers.
So far, insurance coverage for NGS infectious disease testing has been a “total wild card,” but reductions in sequencing costs, combined with the greater risk that epidemics could become more common as a result of globalization, could change the calculus for payers, said Benjamin Briggs, associate director of medical and scientific affairs at IDbyDNA.
Another issue is making the collection and storage of pathogen NGS data fit-for-purpose. For example, diagnostic results are subject to stricter privacy controls than surveillance data, and require different sets of metadata to draw actionable conclusions.
George thinks the public and individual good of pathogen NGS tests could justify a “blended model” for payment, where the government subsidizes certain diagnostic tests, and makes portions of that data available to public health agencies.
“My fear is our highly federated systems of healthcare, and how our data systems are put together, are going to be a friction point to overcome for how to make it happen,” he said.
The plug-and-play NGS testing systems being deployed for COVID-19 are benefitting from recent developments in bioinformatic and wet lab automation.
“If you go back five years, NGS testing was confined to a handful of expert centers around the globe, and the workflows took brute force to finish in a couple of days or so,” said Briggs. “Now it’s routinely accessible to any lab that wants to do this, has been accelerated dramatically” on the order of hours.
He said the data analysis side, which used to be the biggest challenge, was now “push-button” for applications like pathogen identification.
IDbyDNA’s cloud-based Explify platform analyzes sequencing data in the context of the company’s database, which contains tens of thousands of pathogen sequences.
With Illumina Inc. (NASDAQ:ILMN), IDbyDNA is using its software for both “shotgun metagenomics,” a hypothesis-free sequencing approach that can identify novel pathogens and host responses to infection, as well as target-enrichment, which forms the basis for a kit the partners developed to detect hundreds of respiratory pathogens.
Illumina and Helix Opco LLC, a population genomics company administering COVID-19 tests, are collaborating to track the emergence and prevalence of novel SARS-CoV-2 strains, with support from the CDC.
Another accessible NGS analysis tool for pathogen surveillance is Nextstrain, a platform developed by academic researchers including Trevor Bedford, an associate member at Fred Hutchinson Cancer Research Center.
Automated liquid handling instruments that simplify wet lab workflows for COVID-19 surveillance are also emerging, including from companies not originally focused on diagnostics.
In January, food safety company Clear Labs launched Clear Dx, a whole-genome sequencing (WGS) COVID-19 diagnostic platform that automates the entire NGS workflow, including library preparation, cDNA synthesis, target amplification, nucleic acid cleanup, sequencing and analysis.
Clear Labs’ Amini said the machines are being adopted by both established NGS labs seeking to lower costs and increase consistency compared with manual processes, and labs that are setting up NGS testing for the first time in response to calls from the CDC.
Another company deploying its wet lab automation capabilities for COVID-19 testing is synthetic biology company Ginkgo Bioworks Inc. Instead of distributing instruments, the company is connecting with labs generating RNA samples that lack sequencing capabilities, and running the tests in-house.
Other examples of companies contributing to the growth of global sequencing capacity for COVID-19 are Thermo Fisher Scientific Inc. (NYSE:TMO), which is providing its automated Genexus Integrated Sequencer devices to research consortia at a reduced price, and Pacific Biosciences of California Inc. (NASDAQ:PACB), which is expanding the number of machines used by Laboratory Corp. of America Holdings (NYSE:LH) to sequence COVID-19 patient samples.
According to George, there’s no one answer about whether NGS testing for COVID-19 is better conducted on-site across a wide network of labs, or in a centralized facility that can do testing at scale. “It depends on the use case, and who pays for it,” he said.
In cases where labs are setting up their own NGS systems for the first time, whether the benefits will translate to other indications like oncology comes down to logistics, said IDbyDNA’s Schlaberg.
“Sometimes it’s in a facility where different institutions have access, and sometimes it’s siloed in a microbiology lab,” he said. “In general it will increase access to NGS, but how much so will depend on where it is implemented.”