[Resources](/#library) E-Book # Your Cell Count Is a Safeguard How debris changes the answer—and what you can do about it [Download PDF Version](https://precisioncellsystems.com/wp-content/uploads/2026/02/Your-Cell-Count-is-a-Safeguard.pdf) ## Table of contents The debris problem in cell counting 03 What's at stake in your workflow 07 How three methods handle debris 04 Turning debris into an advantage 08 Where current methods fall short 05 Key takeaways 09 The impedance approach 06 Next steps 10 2 INTRODUCTION ## The debris problem Cell counting is a safeguard step. Every downstream assay—from CAR-T expansion to single-cell genomics chip loading—depends on getting the count right at the start. Membrane fragments, aggregates, media residue, and lysed cell debris are present in virtually every biological preparation. How does your counting method distinguish a cell from a piece of debris? The answer depends entirely on the physics of the measurement. ### The cost of getting it wrong ⚠ $8–12K Cost per 10X chip load at risk from inaccurate starting counts 10–15% Extra error from debris in image-based counters 85% → 75% Viability overestimate when debris inflates the denominator SOURCE: INTERNAL ANALYSIS OF ANONYMIZED CUSTOMER DATA, Q4 2025 3 Method comparison Counting accuracy by method type Hemocytometer 15–30%+ error Image-based (AI) 10–35% error Moxi GO II (Impedance) 3–5% CV #### Debris visibility Hemocytometer ✘ Cannot detect debris Image-based ✘ Cannot quantify debris Moxi GO II ✔ Measures debris concentration SOURCE: INTERNAL ANALYSIS OF ANONYMIZED CUSTOMER DATA, Q4 2025 ONE ## How three methods handle debris The accuracy of your cell count depends on how your instrument distinguishes cells from debris. Each method uses a fundamentally different approach. Hemocytometers rely on human visual identification. Image-based counters use AI segmentation of 2D images. The Moxi GO II measures electrical impedance of each particle—cells and debris have distinct physical signatures. #### Why it matters If your method depends on algorithms or human judgment, every sample variable introduces potential variability. 4 TWO ## Where current methods fall short Image-based counters encounter three key challenges in practice: #### 1. Baseline error is difficult to eliminate Even under ideal conditions, 3–4% error per image averages ~10% across a run. #### 2. Debris adds invisible variability Total error can reach 10–35% in debris-heavy samples. You can’t tell how far off. #### 3. Focus dependency adds variance Optical focus is critical and varies between operators, compounding other errors. ### Total counting error with debris present Error range by counting method 30%+ Hemocytometer 10–35% Image-based 3–5% Moxi GO II SOURCE: INTERNAL ANALYSIS OF ANONYMIZED CUSTOMER DATA, Q4 2025 5 01 ## A different approach Impedance-based counting measures the electrical impedance of each individual particle. A cell’s nucleus, membrane, and volume create a distinct signature. Debris lacks these properties. 02 ## The viability gap Most acellular debris does not stain with viability dyes. When debris is overcounted as cells, the denominator is inflated with unstained particles. #### ⸻ Key advantages - No AI segmentation step needed - No focus adjustment required - No algorithm retraining when sample composition changes - Measures debris alongside cells #### ⚠ The compounding error You think you have 85% viable cells. You might actually have 75%. The counting error and viability error compound each other—and the data informing your release decisions may not reflect what’s in the tube. 6 Downstream impact When counting errors propagate #### ○ CAR-T manufacturing Miscounted starting material shifts efficacy curves and can affect patient treatment timelines. Patient cells cannot be re-collected. #### ⚗ Single-cell genomics Each 10X chip costs $8–12K. A 20% CV means underloading (wasted depth) or overloading (doublets). Labs report 1–5% of grant budgets lost to failed re-runs. #### ♦ Drug screening Counting error changes effective drug-to-cell ratio, potentially generating false positives or false negatives in dose-response assays. SOURCE: INTERNAL ANALYSIS OF ANONYMIZED CUSTOMER DATA, Q4 2025 THREE ## What’s at stake in your workflow Counting errors don’t stay at the bench. They propagate—and the impact grows with each downstream step. #### ☑ Regulatory advantage The Moxi GO II is designed for 21 CFR Part 11 compliance with audit trails, secure mode, and stored gate presets. At every QC checkpoint—from initial cell isolation through expansion to final product release—the instrument delivers reproducible, auditable data. 7 FOUR ## Turning debris into an advantage Most labs treat debris as noise. The Moxi GO II turns debris into a quantifiable, trackable data point. #### ◉ Sample quality gating Preset gates define acceptable debris thresholds. #### ◉ Go/no-go decisions Quantify sample quality before expensive steps. #### ∿ Drift detection Track debris-to-cell ratio to catch prep drift early. ### The results labs are seeing ✳ ±18% → ±5% Seeding protocol variance reduction 1–5% Grant budget saved on failed genomics re-runs 15% → 3–5% Cross-institution counting variance reduction SOURCE: INTERNAL ANALYSIS OF ANONYMIZED CUSTOMER DATA, Q4 2025 8 ## Key takeaways Actionable recommendations for improving counting accuracy in your lab. #### Quantify your debris Measure debris concentration alongside cell counts to enable go/no-go gating. #### Track prep drift over time Monitor debris-to-cell ratios as part of your SOP to catch process changes early. #### Standardize across operators Preset gates and stored SOPs deliver the same result regardless of who runs the test. #### Choose physics over algorithms Impedance-based measurement doesn’t need retraining when sample composition changes. #### Protect expensive downstream steps Assess sample quality before committing $8–12K to a chip load or starting a CAR-T expansion. #### Build regulatory confidence 21 CFR Part 11 compliance with audit trails and secure mode supports GMP documentation requirements. 9 ## See how it performs on your samples See how the Moxi GO II performs on your samples. Run your standard preps, measure cells and debris, store your gates, and decide whether debris quantification changes your workflow. [Request a Quote](https://precisioncellsystems.com/request-a-quote/) 10 precisioncellsystems.com For Research Use Only. Not for use in diagnostic procedures. © 2025 Precision Cell Systems. All rights reserved.