2026
Journal
Image Analysis Platform for Comprehensive Quantification of Extracellular Vesicle Morphology
Spark A et al. · PROTEOMICS 2026;26(6):59–67 (e70113)
View paper ↗From raw datasets to quantitative, single-vesicle insight — in seconds, in batch. The entire extracellular-vesicle workflow lives in one platform: upload, analyse, compare and collaborate, from any device, anywhere.
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Nanometrix takes your most complex nanoparticle data from raw localisations to high-throughput, quantitative results — in seconds, in batch. Upload, quality-check, analyse, compare and share, all in one reproducible place.
Aggregate single-vesicle data into group, sample and population insight, with built-in statistics and side-by-side comparison.
The whole EV workflow in one platform — in the cloud, accessible from any device, anywhere.
30+ metrics for every individual vesicle — size, morphology, colocalisation and inter-channel geometry, including a novel morphology-based phenotype.
From raw localisations to quantitative results in seconds — hundreds to thousands of datasets processed in parallel.
Line up anything side by side — samples, patient groups, datasets, whole cohorts or analysis runs — and let the platform surface where they differ. Find groups, clusters and outliers automatically, then turn it into QA/QC readouts and standardised reports in a click. What used to mean days of manual collation in spreadsheets happens in seconds.
Compare anything — samples, patient groups, datasets and analysis runs, side by side.
Find groups & clusters — populations, sub-populations and outliers surfaced automatically, with significance flagged (Cliff's δ, p-values).
QA/QC & standardised reports — one-click readouts and shareable, reproducible report outputs.
Nanometrix runs in the cloud. Reach your data and every analysis tool from any device, anywhere — no installs, no local HPC, no scripts to stitch together. The whole team works from the same data, and the offline software stays fully supported for enterprise deployments in biotech and pharma.
Cloud-based access — from any device, anywhere, with nothing to install.
One workspace — upload, QA, analysis, dashboards and reports, together.
Shared & reproducible — the whole team on the same data, every run kept.
Any SMLM microscope; group and nest into projects.
Inspect channels and auto-align in one click.
Find every vesicle; measure size, shape & overlap.
Overlay groups with significance flagged per metric.
From single vesicles to population dynamics.
Shared workspaces, exports and reports.
Every single EV found in your datasets is characterised individually — size, morphology, colocalisation and inter-channel geometry — and assigned a novel morphology-based phenotype (Spot · Complex · Spread). That per-vesicle depth turns a blurry population average into a precise, quantitative fingerprint you can actually compare and act on.
Re-engineered to run in parallel in the cloud, Nanometrix turns analysis from an overnight chore into something instant — so speed becomes a tool you actually use, not just a number on a slide.
Bulk-analyse hundreds to thousands of datasets in a single parallel run.
Get population-level readouts in real time while you image — decide whether to keep collecting or move on, instead of waiting for an end-of-day batch.
Re-run a whole day's acquisition to test parameters and settings on the spot — no babysitting clunky Python or in-built pipelines to find what works.
Book a 30-minute demo and we'll walk your EV workflow end to end — from raw upload to population-level insight — in the platform, on your data.
Free tier for individual researchers, Plus for working scientists, academic pricing for groups.
Pipeline for moving EV signatures from discovery to validated classifier.
Batch compute and version-controlled analysis to keep pace with discovery cadence.
Pool storage, RBAC, and per-lab billing for multi-group institutional deployments.
Your data is encrypted and access-controlled, with the certifications diagnostics and pharma require.
Group your samples into populations — disease vs control, responder vs non-responder, stage I vs III — and we train a tailored predictive model that classifies new samples from their EV profile alone. Includes consultation, model tailoring, and close collaboration with our science team.
You label the groups. We structure your library around them.
Our team selects and tunes architectures against your signal, not a generic benchmark.
Cross-validation, held-out cohorts, and a classifier you can ship into routine use.
Retrain as your cohort grows. We stay in the loop across the programme.
Spark A et al. · PROTEOMICS 2026;26(6):59–67 (e70113)
View paper ↗
Zanganeh S et al. · STAR Protocols 2026;7(1):104428
View paper ↗
Amin MR et al. · Cell and Tissue Research 2026;403(1):13
View paper ↗Peer-reviewed journals, protocols and conference abstracts.
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