NIH Direct-to-Phase II Award Backs Automated Extracellular Vesicle Isolation at Scale

Pulse 2.0 reported that Everest Biolabs has received a $2.1 million Small Business Innovation Research (SBIR) grant from the National Institute of General Medical Sciences. The grant will fund automated technology for isolating extracellular vesicles at clinical research scale ^[1]. The award is a Direct-to-Phase II grant, which Pulse 2.0 describes as an NIH mechanism open to small businesses that have already shown their technology is feasible ^[1]. The company plans to spend the funds on an automated, plate-based isolation platform for plasma biomarker studies and on next-generation Apex columns intended to yield higher-purity vesicles ^[1].

The scientific problem the award targets

Extracellular vesicles (EVs) are nanoscale particles released by cells. They carry membrane and cytosolic proteins from the tissues that produced them ^[1]. According to the story, these particles may give researchers information about diseases affecting organs such as the brain and heart, as well as about tumors ^[1].

The obstacle the project addresses is the very wide range of protein concentrations in blood. A small number of abundant proteins make up most of the protein mass and can mask scarcer tissue-derived proteins that may say more about disease ^[1]. EVs can be physically separated from abundant free proteins, so isolating them is one potential route to those weaker signals ^[1]. The article presents this as the rationale for the work, not as a demonstrated diagnostic result ^[1].

Why it matters for research teams and administrators

The funded project centers on making EV isolation reproducible across hundreds or thousands of samples, and the planned platform is meant to process larger cohorts while reducing hands-on time ^[1]. The work therefore sits on the sample-processing side of biomarker research, and the story names no specific disease application for the grant ^[1].

Tal Gilboa, the company's co-founder, head of research and principal investigator, said the aim is a platform any laboratory can run, producing "high-purity EVs from hundreds of plasma samples a day, isolated the same way every time" ^[1]. Gilboa said the team first developed the plate-based approach at the Wyss Institute ^[1].

For grant managers and research administrators, the award shows a small company entering NIH's SBIR program at Phase II on the basis of prior feasibility work, as the article describes the mechanism ^[1]. Chief executive and co-founder George Daaboul described the selection as a strong validation of the technology and team, which is the company's own characterization rather than an external assessment ^[1].

The grant also builds on products the company already sells. Everest came out of stealth in November 2024 and has since brought to market two automated isolation instruments, named Ascent and Summit, along with Apex SEC columns and Atlas ELISA (enzyme-linked immunosorbent assay) kits used to measure EV quantity and purity ^[1].

What to watch next

• Whether the next-generation Apex columns deliver the higher purity described from complex biofluids, including plasma ^[1].
• Whether the automated plate-based platform handles the larger cohorts with the reduced hands-on time the project targets ^[1].
• Whether performance data appear, since the story reports plans and quoted claims rather than throughput, purity or reproducibility figures ^[1].
• Award details, since the article does not report the project period, start date or award number ^[1].
• Whether the work extends to the downstream uses Daaboul listed: biomarker discovery, diagnostics and therapeutics ^[1].

Limitations

This analysis rests on a single business-news report that draws largely on company statements and quotes ^[1]. The story contains no peer-reviewed data, no comparison with other EV isolation methods and no independent evaluation of the technology ^[1]. Claims about purity, scale and consistency should be read as goals of the funded project rather than established findings ^[1].