Many applications—from drug discovery and diagnostics to cell engineering and gene modulation—require delivering biomolecules into large numbers of cells and rapidly evaluating the outcomes. The challenge is twofold: achieve intracellular delivery at scale across diverse cells and cargos, and obtain quantitative results fast enough to keep pace with that delivery.

The device guides cells through an array of up to 62,000 tiny through-holes that are narrower than the cell diameter. A brief, gentle squeeze creates transient membrane pores that admit biomolecules into the cell interior, then reseal, allowing cells to recover. In validation studies, the team delivered gene‑silencing RNA (siRNA) and plasmid DNA across multiple cell types, including human gingival fibroblasts (hGFs), demonstrating broad utility for cell engineering and personalized therapies.

To keep up with the fast delivery, an automated analysis system uses the same microscope images labs already acquire. A deep‑learning model looks at those images and, in a single pass, reports four readouts: cell size, the fraction of cargo‑positive cells, the fraction of viable cells, and per‑cell fluorescence intensity. What used to take hours of manual counting now takes about 83 seconds on a representative dataset of roughly 500 cells, with accuracy comparable to human review. Large cohorts were processed—for example, 1,980 cells (6‑FAM siRNA) and 1,184 (EGFP plasmid). These sample sizes make the results statistically robust and turn high‑throughput delivery into high‑confidence decisions. 

“Our goal was simple: get molecules inside many cells quickly and gently,” says first author Pulasta Chakrabarty. “Seeing the device work across different cell types points to real potential in cell engineering and personalized therapies.” Co‑author Ryoma Suzuki adds, “The automated model looks at the same images labs already use. It does the counting and measuring—cell size, delivery efficiency, viability, and per‑cell fluorescence—in one pass, so the evaluation keeps pace with the experiments.” “High throughput alone isn't enough,” notes Prof. Moeto Nagai. “What matters is the speed at which results can be trusted. By unifying high‑throughput delivery with automated quality control, we move from proofs‑of‑concept to practical workflows—and closer to systems that prepare a patient’s cells on‑site.”

By coupling scalable intracellular delivery with rapid, automated evaluation, the platform expands what can be accomplished in a single day—from large‑scale screening and diagnostics to practical cell manipulation and future point‑of‑care gene‑editing workflows.