NEW YORK – Next Gen Diagnostics (NGD) is eyeing the clinical microbial genomics market with a highly automated, end-to-end next-generation sequencing and analysis workflow.
The Boston-based company is planning to deploy its technology into hospitals for NGS-based infectious disease control in early 2025, and is developing a sequencing-based diagnostic test to determine microbes' antibiotic susceptibility and resistance.
NGD Founder and CEO Paul Rhodes said the company was established in 2017 with the goal of achieving high-volume and low-cost whole-genome sequencing for routine clinical microbiology applications. Although the cost of sequencing has been going down in recent years, Rhodes said the company has been working to address two other major bottlenecks that hinder the wide adoption of NGS in the field: sample preparation and bioinformatic analysis.
To address these challenges, NGD has automated the sample preparation process, which promises a fast turnaround time while requiring minimal "low skill" hands-on time. It has also developed a fully automated bioinformatics pipeline for outbreak detection and antimicrobial analysis.
More specifically, for sample preparation, NGD has integrated two automation platforms, a robotic system for DNA extraction and a proprietary microfluidic instrument for library preparation.
Starting from bacterial isolates or pellets collected from a positive blood culture, a lab technician loads plated sample aliquots and reagents onto the robotic DNA extraction machine, Rhodes said. After the extraction run, which takes about two hours, the instrument transfers the isolated nucleic acid onto an integrated fluidic circuit (IFC), which is then manually loaded onto the microfluidic platform for library prep.
Developed in collaboration with Standard BioTools, the microfluidic instrument, named NGD-100, carries out automated library prep and barcoding for whole-genome sequencing using tagmentation chemistry, Rhodes said. After that, individual libraries are pooled and cleaned up for sequencing.
Overall, Rhodes said NGD's automated platforms can process 48 samples at once, and the entire sample prep workflow can be carried out within an eight-hour work shift. For sequencing, the company has been using the Illumina platform, though the workflow is theoretically agnostic and can use any short-read sequencers, he added.
As soon as sequencing is completed, the data are uploaded to a secure cloud computing environment for automatic analysis, said Rhodes. Following "many layers" of data quality control, he noted, the pipeline identifies possible outbreaks by examining the relatedness between core bacterial genomes at the SNP level. The pipeline further includes machine-learning algorithms developed by NGD to help predict antimicrobial susceptibility and resistance to relevant drugs.
After data analysis, the findings are presented on the NGD dashboard, where transmission events and antimicrobial resistance prediction, as well as resistance-associated genes and mutations are summarized and visualized.
With its automated WGS workflow, Rhodes said NGD is currently focusing on two major applications. The first is deploying its technology to hospitals or long-term care facilities to help detect and curb healthcare-associated infections (HAIs).
Another target application for the company is to develop WGS-based diagnostics for antibiotic susceptibility testing. While it may take several years for the company to achieve clinical validation for such tests, Rhodes said, the firm is "actively pursuing" regulatory clearance and is "systematically preparing for interactions" with the US Food and Drug Administration.
Additionally, basic and translational researchers can also tap the NGD technology for antimicrobial susceptibility and resistance studies. The company, for instance, has inked a partnership with Japanese pharmaceutical firm Shionogi to develop and validate WGS data to gauge microbial antibiotic susceptibility to cefiderocol, an antibiotic developed by Shionogi that is used to treat infections caused by certain resistant Gram-negative bacteria.
Despite the sample automation platforms the company has developed, Rhodes said NGD does not plan to sell individual instruments to customers. Instead, the company plans to become a service partner and plug the entire NGS infrastructure, including all necessary equipment, into hospitals and public health labs.
According to Rhodes, the per-sample price using NGD's WGS workflow— including sample preparation, sequencing, and data analysis — is $99. Customers can also get a 25 percent discount if they are willing to share the antibiotic resistance data with the company to help it further train its machine-learning algorithms. For those customers who already have a sequencer in-house, they may be entitled to an additional discount, he added.
NGD, which has subsidiaries in England and Israel, currently operates a laboratory for both bacterial sequencing and antibiotic susceptibility testing in Cambridge, Massachusetts, according to Rhodes. He declined to share any information regarding NGD's funding, headcount, and revenue at this point, other than noting the firm remains private and is "not looking to raise money" in the foreseeable future.
"I 100 percent think that we need commercial entities in order to make [NGS-based HAI surveillance] expandable," said Alexander Sundermann, an infectious disease professor at the University of Pittsburgh. Especially for smaller nonacademic hospitals that lack in-house sequencing and bioinformatic resources, commercial companies can help them set up the needed sequencing workflow and infrastructure, which can be a quite complicated process, he noted.
Sundermann's team at Pitt is one of the first in the nation to implement prospective WGS for HAI surveillance. Even for an experienced group like his, commercial partnerships are still "not off the table" to help boost sequencing and bioinformatic capabilities if the team wants to scale up the project, Sundermann said.
Despite the potential commercial need, the uptake and adoption of NGD's technology remains to be seen.
"The idea of a commercial entity for pathogen genomics isn't necessarily new; it's just that I don't think the market has always been there," said Sundermann, who has informally advised several commercial companies in the space, including NGD. However, as mounting evidence has shown the feasibility and potential economic benefit of NGS-based infectious disease surveillance, Sundermann thinks the demand for commercial companies like NGD has also been rising.
A recent analysis conducted by Sundermann and his collaborators, for instance, estimated that the real-time WGS surveillance program implemented at Pitt has averted 62 infections over a two-year period, from which they extrapolated a net savings of $695,706 for the healthcare system.
Even so, surveillance sequencing is currently not reimbursable, Sundermann pointed out, leaving hospitals to eat the cost. Therefore, how to convince hospital administrators to pay for these programs remains a challenge, as Sundermann and other infectious disease experts pointed out in a commentary published last week in the Antimicrobial Agents and Chemotherapy journal.
"We all agree that the evidence is there that by doing genomic surveillance sequencing prospectively, you can find tons of outbreaks that go undetected and that you can stop them," Sundermann said. "The big barrier is financial and [figuring out] how are we going to pay for this."