NEW YORK – Nautilus Biotechnology may not hit its previously stated goal of commercially launching its proteomics platform by the middle of the year, GenomeWeb has learned.
While the company reiterated during its Q3 2023 earnings call in October that it planned to launch the platform by mid-2024, CEO Sujal Patel was more circumspect in a recent interview.
"We haven't made a launch announcement yet," he said. "The next steps for us, as we get to US HUPO and World HUPO again this year … [are] to show the scientific progress that we are making and ultimately leading to decoding some number of proteins from a complex biological sample. In our minds, that is the catalyst for us to start talking about exact dates for our early-access program and to start signing up customers."
Patel said that during the company's last earnings call, "we tried to refrain from saying midyear" 2024 would be the target launch date. However, during that call, Patel said in response to analyst questions that "we continue to target roughly the middle of next year, middle of 2024, for the launch of our platform," and that its early-access program would begin roughly three to four months ahead of that launch, with the company at that time starting to use its platform to analyze samples from early-access participants.
He declined to provide an update on when the company expects to start its early-access program or launch the platform, pointing to the upcoming Q4 2023 earnings conference call. "When we get to our earnings call, we'll have a good update," he said.
In March 2023, Nautilus announced the winners of its "First Access Challenge," in which the company selected three labs to receive proteomic analyses of their samples using its technology. To date, none of the three labs have received data generated on the platform.
Joanna Bons and Jordan Burton, postdoctoral fellows in the lab of Buck Institute researcher Birgit Schilling who are hoping to receive data from Nautilus' system for proteomic discovery work in acute kidney injury, said they are "currently at the edge" of obtaining "very exciting data" on the platform.
Brigham Young University researcher Samuel Payne, who with his colleague Pam Van Ry is hoping to use the Nautilus technology to characterize organoid models of pulmonary fibrosis, said that while he has been working with the company over the last year, he does not yet have preliminary data. He suggested that in a few months, he might have data from the platform that he could discuss.
Nicholas Graham, assistant professor of chemical engineering at the University of Southern California, plans to obtain data from the Nautilus platform for proteomic discovery work in glioma. He said that his lab has not yet accessed data from the platform but that in his most recent discussions with the company, they had indicated that he could probably send in his samples for analysis in March.
Graham noted that his discussions with Nautilus have largely centered around sample requirement details, like how much sample is needed at what concentration, as well as what sample processing methods will be compatible with the system.
Parag Mallick, Nautilus' cofounder and chief scientist, said that the company's sample prep process is designed to be straightforward and accessible to users with undergraduate-level training. He added that "at this point, there are no practical constraints on samples types" but that the company does anticipate working with simpler sample types like cells and tissues before taking on biofluids.
He said that the company's discussions with the "First Access Challenge" winners "have focused on cells and tissues as well as having a sufficient amount of non-rare sample on which to test a variety of aspects of the platform." Additionally, the discussions have had "the secondary objective of learning about [the users'] sample types, prep processes, and data normalization needs to ensure good quality data," he said.
Nautilus' platform uses chips functionalized with DNA origami structures that allow researchers to deposit single proteins in extremely dense arrays, enabling single-molecule analysis of as many as 10 billion individual proteins. The company analyzes the arrayed proteins by iteratively staining the sample with semi-specific affinity agents and then using machine learning to make identifications of the individual proteins based on the patterns of affinity agent binding observed. Because the platform uses single-molecule technology, proteins are quantified simply by counting them following identification.
Nautilus presented information on its sample prep process at the 2023 HUPO meeting in October. The company also provided details on its process for producing and validating the multi-affinity probes as well as controlling for the platform's false discovery rate. Additionally, it showed data on the platform's stability, demonstrating that proteins remain bound on the chips across runs of around 100 cycles, and that binding rates and background signal remain stable across that number of cycles. Mallick said the company anticipates the initial version of the instrument will conduct runs in the range of 100 to 200 cycles.
Nautilus has yet to demonstrate how the platform will perform on actual biological samples, Mallick said, noting that this is perhaps the most common question the company is receiving from interested researchers.
They are asking "can you show us some data on limit of detection, limit of quantitation, reproducibility … how many proteins you are going to be measuring in broad scale mode?" he said. "Those are things that we absolutely will be planning to demonstrate."
When the company will do so is unclear, however. Patel cited US HUPO and World HUPO as venues where Nautilus might provide data on its progress that could support a launch. The latter meeting is scheduled for the end of October, well past the company's previous midyear launch target.
Nautilus has pushed back its timelines several times since launching. The company initially said it aimed to measure 2,500 proteins per run by early 2022, to measure up to 10,000 proteins per run by late 2022, and to analyze full proteomes by the middle of 2023. In 2022, it pushed a planned 2023 launch to mid-2024. In August of last year, it announced that while it continued to target mid-2024 for its launch, it was scaling back the specifications for the initial version of the platform.
"What we're doing is a radically different technique, and it's a very hard product," said Patel. "We have the right team, we have the right focus, we have a big balance sheet. So those are all assets, but it doesn't take away from the fact that it is hard and it is taking time."