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Liquid Handling · Automated pipetting · Incubation · Microscopy integration · Personal Pipetting Robot · 2022 · Nature Communications

Open-source personal pipetting robots with live-cell incubation and microscopy compatibility

Compact liquid handling robot for automated pipetting/aspiration during live-cell incubation and microscopy

Performance the paper reports

2 of 5
  1. Motion0.1 mmMotion accuracy: reported
  2. Volume1µlVolumetric accuracy: reported
  3. Viability—Cell viability: not reported
  4. Unattended—Unattended operation: not reported
  5. Standard—Standard compliance: not reported
  • Motion / positional accuracy0.1 mm
    [curated metric] ~0.1 mm pipette positioning accuracy above well bottom (96-well plate, validated via fluorescence imaging)
  • Volumetric accuracy1µl
    Having confirmed pipetting accuracy and reprodu- approximately 1µl.

How hard this is to adopt

3.8 of 5, higher is easier

Each score is shown against the range the other 59 builds actually occupy, because no criterion uses the full 1–5 scale. These describe how reproducible the build is, not how good the science is.

  • Resolution

    3/1–5

    Peristaltic pumps with a 0.4 uL/step theoretical limit but +/-2 uL error at any target (10 uL gave 7-11 uL), reliable from ~25 uL, with flow controlled 2-100 uL/s.

  • Throughput

    5/2–5

    One to ten independently pumped pipet channels each with its own reservoir, contamination characterised up to 10 pipets, parallel distinct programs per well and 48 h unattended operation.

  • Parts sourcing

    4/2–4

    Mostly off-the-shelf or kit-based components.

  • Skill needed

    4/2–4

    Build/operation described as low-skill or basic assembly.

  • Facilities needed

    3/2–4

    Requires accessible but nontrivial lab/maker equipment.

  • Documentation

    4/2–5

    Open resources include several build or operation artifacts.

  • Validation effort

    4/2–4

    Volumes 10-1000 uL, flow 10-100 uL/s, carryover with 0/1/4/8 washes, 48 h drift within +/-1%, benchmarked against manual pipetting (12.6% versus 3.6% cell loss); no clogging or pulsation data.

  • Cycle time

    3/1–4

    Only a speed-matched comparison (manual 100 uL wash in 10 s equals automated 10 uL/s); 2-40 s per well and 4-13 min per plate given with no manual throughput benchmark.

2 further criteria are recorded but not shown
  • Application Level — scored 4 (75% of records share one value), so it cannot separate one build from another.
  • Build Time — scored 3 (scored for only 6 of 60 records), so it cannot separate one build from another.

Both remain in the published dataset.

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Record metadata
Publication data

Matched by doi · retrieved 2026-07-21

Abstract

Liquid handling robots have the potential to automate many procedures in life sciences. However, they are not in widespread use in academic settings, where funding, space and maintenance specialists are usually limiting. In addition, current robots require lengthy programming by specialists and are incompatible with most academic laboratories with constantly changing small-scale projects. Here, we present the Pipetting Helper Imaging Lid (PHIL), an inexpensive, small, open-source personal liquid handling robot. It is designed for inexperienced users, with self-production from cheap commercial and 3D-printable components and custom control software. PHIL successfully automates pipetting (incl. aspiration) for e.g. tissue immunostainings and stimulations of live stem and progenitor cells during time-lapse microscopy using 3D printed peristaltic pumps. PHIL is cheap enough to put a personal pipetting robot within the reach of most labs and enables users without programming skills to easily automate a large range of experiments.

Bibliographic details

Published
2022-05-30
Journal/source
Nature Communications
Publisher
Springer Science and Business Media LLC
DOI
10.1038/s41467-022-30643-7
Type
journal-article
Language
en
Volume / issue
13 / 1
Pages
Not supplied
ISSN
2041-1723

Access and metrics

Open access
Yes
OA status
gold
License
cc-by
Version
publishedVersion
Cited by
39
References
54
Retracted
No

Authors and affiliations

  1. Philip DettingerCorresponding authorUniversity of Basel · ETH Zurich
  2. Tobías KullETH Zurich
  3. Geethika ArekatlaETH Zurich
  4. Nouraiz AhmedETH Zurich
  5. Yang ZhangETH Zurich
  6. Florin SchneiterETH Zurich
  7. Arne WehlingETH Zurich
  8. Daniel SchirmacherETH Zurich
  9. Shunsuke KawamuraETH Zurich
  10. Dirk LoefflerETH Zurich
  11. Timm SchroederCorresponding authorETH Zurich

Topics and keywords

Microfluidic and Bio-sensing TechnologiesMicrofluidic and Capillary Electrophoresis Applications3D Printing in Biomedical ResearchPipetteRobotComputer scienceOpen sourceSoftwareHuman–computer interactionBiomedical engineeringNanotechnologyArtificial intelligenceEngineeringMaterials scienceOperating system

Funding

  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung · 179490
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung · 186271
Perspective and practical signals

Why it matters

Shows open hardware that integrates pipetting + incubation + imaging, closer to ‘robot-compatible’ liquid handling.

Limitations

Designed for small-volume/well-plate work -- not built for large-batch or high-volume liquid handling

Skills needed

3D printingelectronics assemblybasic scripting (no programming experience required for operation)

Democratizing features

open-source hardwarea and software, 3D printable and assembled with off-the-shelf components, compact and modular design meant for sitting directly on microscope stages thus enabling automated interventions during live-cell imaging, designed for standard two-finger robot grippers and common robotic arms, supports multi-pipetting,