Air-Lock — LNP Formulation QC Platform

The platform

One record comprehensive and normalized. Every instrument.
Hypothesis linked. Ready the moment you say, “go”.

Air-Lock has two components. OmniNorm is the MVP — the data layer that runs at your internal site, normalizing instrument data from every location. LabMEM is the intelligence layer that runs on top. The scientist does their job. OmniNorm connects the dots.

OmniNorm

MVP — now

Data layer · internal site

Registers samples with hypothesis and expected outcome before instruments run

Generates NanoAssemblr batch CSV — eliminates manual parameter entry

Pre-populates Stunner plate maps and session sheets

Watches instrument output folders — parses FCS, CSV, PDF automatically

Normalizes all outputs to one schema — same units, same field names

Generates complete characterization report with outcome confirmation

Append-only audit log and SHA-256 checksums from record one

21 CFR Part 11 compliance upgrade available — user management, e-signatures, and audit trail viewer

LabMEM

Version 2

Intelligence layer · program level

Automated QC flagging across all parameters: size, PDI, EE%, empty particle fraction

Batch trending and anomaly detection across hundreds of runs

Cross-site analytics — director dashboard comparing all OmniNorm sites

AI-powered locally. It learns from the normalized dataset that OmniNorm builds

External manufacturer reports for CRO, CMO, and regulatory submissions

Five-step workflow

From bench to a comprehensive normalized report

Sample Registration

Scientist fills in the OmniNorm Excel template — hypothesis, formulation parameters, expected outcome. OmniNorm assigns unique IDs (short unique sample and hidden tracking UUID), generates tube labels, NanoAssemblr batch CSV, Stunner plate map, and session sheet automatically.

OmniNorm Excel template

Instruments Run

NanoAssemblr imports the pre-generated CSV — no manual parameter entry. Stunner imports the plate map. NanoFCM and Zetasizer accept the short ID typed or scanned from the tube label. External sites receive a stripped-down run sheet with no internal scientific context.

Hybrid input model

OmniNorm Watches Output Folders

The moment a new file appears — FCS and PDF from NanoFCM, CSV from Stunner, batch record from NanoAssemblr — OmniNorm reads it, finds the sample ID, calculates a SHA-256 checksum, and links the result to the correct record.

Automatic file capture

OmniNorm Normalizes, Links, and Reports

All instrument outputs translated to one schema: same field names, same units, measurement method preserved. Experimental hypothesis and expected outcome attached. Outcome comparison calculated against the reference run. A complete characterization report is generated the moment you say “go”.

Hypothesis confirmed or contradicted

LabMEM Receives the Complete Record

OmniNorm passes the fully assembled record to LabMEM (VERSION 2). When LabMEM launches, it will apply automated QC flagging, batch trending, anomaly detection, and cross-site analytics to your entire dataset. No migration. No rebuilding.

AI QC intelligence

Instrument coverage

Works with every instrument in the LNP workflow

OmniNorm uses a hybrid input model — CSV pre-population where the instrument supports it, short ID from tube label where it doesn't. Every instrument in the workflow is covered.

NanoAssemblr

Precision NanoSystems

↑ Batch CSV input generated by OmniNorm

↓ Batch record: executed flow parameters

Flow NanoAnalyzer

NanoFCM

↑ Short ID typed from tube label

↓ FCS + PDF: size, concentration, payload

Stunner / Lunatic

Unchained Labs

↑ Plate map CSV pre-populated by OmniNorm

↓ CSV: size, EE%, RNA concentration

Zetasizer

Malvern Panalytical

↑ Short ID typed from tube label

↓ CSV: Z-average, PDI, zeta potential

Live demo

This is what OmniNorm generates:

Built from real NanoFCM single-particle data. This report was assembled by OmniNorm from instrument output files, no copy-paste, no formatting. The hypothesis and outcome comparison are populated from the registration template.

OmniNorm

LNP QC Platform

LNP Characterization Report — NanoFCM Single-Particle Analysis

DEMO-20260321-001

Generated: 2026-03-21 · 09:14 UTC

Report Complete

Data file

Sample1_F7-10_4xdilution.nfa

Instrument ID

FNAN30E2012671

Operator

Experiment ID

DEMO-EXP-001

Dilution factor

4×

Gating range

30–300 nm

OmniNorm ID

DEMO-20260321-001

Experimental hypothesis

If PEG-lipid molar % is changed from 1.5% to 1.0%, then a decrease in median diameter is expected (5–15 nm smaller than reference run DEMO-20260320-003). Rationale: lower PEG content reduces steric stabilization and allows tighter particle packing.

Size distribution — events vs diameter

                NanoFCM output — actual instrument export  |  — — gating range 40–120 nm
              

Parameter	Value
Median diameter	66.75 nm
Mean diameter	72.86 nm
Std deviation	18.05 nm
Gating range	30–300 nm
Total events	2,633
Gating events	2,633
% gated	100%

Concentration

Sample concentration

9.92 × 10⁸

Particles/mL (4× dilution corrected)

STD concentration

2.29 × 10¹⁰

Particles/mL

Corrected ratio

100%

2,634 / 2,634 gated events

Outcome comparison — hypothesis vs. result

Parameter	Predicted	Measured	Reference run	Delta	Status
Median diameter	Decrease 5–15 nm	66.75 nm	94.2 nm (DEMO-20260320-003)	↓ 27.5 nm	✓ Confirmed
PDI	—	0.14	0.18	↓ 0.04	No prediction
Particle concentration	—	9.92 × 10⁸ /mL	—	—	No prediction

OmniNorm automated summary

Sample DEMO-20260321-001 tested the effect of reducing PEG-lipid from 1.5% to 1.0% (Experiment DEMO-EXP-001). Median diameter decreased from 94.2 nm to 66.75 nm — a reduction of 27.5 nm, consistent with the predicted direction. PDI improved from 0.18 to 0.14. Sample concentration 9.92 × 10⁸ particles/mL after 4× dilution correction. All 2,633 events within gating range (100% efficiency). Hypothesis confirmed.