Best practices
Verifying and locking in an optimized liquid class
How to prove an optimized class is right, how many replicates to run, precision before trueness, and how to freeze and document it so the tuning is not lost.
Best practices
Field-tested habits and checklists that keep automated liquid handlers accurate, repeatable, and audit-ready day after day.
- Best practices
How to optimize a liquid class, step by step
A practical, repeatable procedure for tuning a liquid class: start close, run a real transfer, change one knob at a time, then measure and correct until it holds.
- Best practices
How to measure a transfer: photometric, fluorometric, gravimetric
You cannot trust a volume you have not measured. The three quantitative methods, photometric, fluorometric, and gravimetric, and when each is the right tool.
- Best practices
Compliance and audit readiness for automated liquid handling
In regulated labs a transfer is not done until it is documented. Audit trails, electronic signatures, and change control for methods and the liquid classes behind them.
- Best practices
Reproducibility across labs: why sharing the definition is not the same as sharing the result
Two labs can run the identical liquid class and get different volumes. Here is what a shared definition leaves out, and how to close the gap.
- Best practices
Dry-running a protocol: simulation before the deck
Most protocol failures are catchable before the robot moves. How simulation and deck visualization surface collisions, shortfalls, and labware mistakes offline.
- Best practices
In-line volume verification: checking the run, not just the class
Validating a class proves it worked once. In-line verification checks volumes during the run itself, catching the failures offline testing never sees.
- Best practices
Washable versus disposable tips: the contamination and cost trade-off
Fixed steel tips you wash, or disposable tips you throw away. The choice shapes carryover risk, cost per run, and how your liquid class has to behave.
- Best practices
Multi-dispensing done right
Aliquoting one aspiration into many wells is fast but tricky. When to use it, why to discard the first and last aliquots, and how to correct a step-down volume series.
- Best practices
Trueness, precision, and the ISO vocabulary
The industry standardized what accuracy means for liquid handlers. Trueness, precision, and accuracy defined, the percent-error and percent-CV formulas, and the ISO documents behind them.
- Best practices
The real cost of a miscalibrated liquid class: rework, reagents, and risk
A slightly wrong liquid class rarely fails loudly. It leaks cost through wasted reagents, repeated runs, and decisions made on quietly bad data.
- Best practices
Build vs. buy: should you write your own liquid classes or adopt a shared catalog?
Every lab decides whether to develop liquid classes in-house or start from a shared catalog. Here is an honest look at the real costs of each.
- Best practices
Porting a manual bench protocol to a liquid handler: what changes when the pipette is a robot
A handheld protocol is full of tacit technique your hand does without thinking. Automating it means turning that feel into explicit, testable parameters.
- Best practices
Connecting a liquid handler to a LIMS: where classes meet sample data
A liquid handler moves samples; a LIMS knows what they are. Linking the two turns a worklist into a tracked result rather than a plate of anonymous wells.
- Best practices
Barcode tracking and sample identity in an automated run
Automation only scales if the robot knows which sample is which. How barcodes, autoloaders, and positional tracking keep identity attached to every well.
- Best practices
Troubleshooting a liquid handler: reading symptoms back to parameters
Most pipetting faults show before you measure. Read dripping, bubbles, short fills, and carryover back to the property and the one parameter that fixes each.
- Best practices
Validating a liquid class: gravimetric calibration, step by step
A liquid class is a hypothesis until you weigh it. How to verify accuracy and precision gravimetrically, adjust with a calibration curve, and re-check over time.
- Best practices
Versioning liquid classes: why provenance beats a shared drive
Undocumented parameter tweaks are how methods silently drift. How versioning and provenance turn liquid classes into trustworthy, auditable lab assets.
- Best practices
The standards behind automated liquid handling: ISO 8655, ANSI/SLAS, and why they matter
A tour of the standards that make pipetting comparable across labs and instruments, from volumetric accuracy to the microplate footprint your deck depends on.
- Best practices
From default to validated: the liquid class development workflow
A five-step routine for building a class: understand the liquid, start from a predefined class, inspect, change one parameter at a time, then verify with a correction curve.
- Best practices
Serial dilution without carryover
Serial dilutions multiply small errors and invite carryover. Fresh tips, thorough mixing, sensible mix volumes, and dropping the over-aspirate keep a series honest.
- Best practices
When your automation scientist leaves: capturing liquid-class knowledge before it walks out
The hardest-won pipetting knowledge lives in one person's head. How to capture liquid-class expertise as engineering, so a resignation is not a reset.