Evidence map›Paper›PMID 33718828›Full record

ArticleiScience2021

Automated solubility screening platform using computer vision.

Parisa Shiri, Veronica Lai, Tara Zepel, Daniel Griffin, Jonathan Reifman, Sean Clark, Shad Grunert, Lars P E Yunker, Sebastian Steiner, Henry Situ and 3 more

Abstract read
In one paragraph

Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Steering towards safe self-driving laboratories.Nature reviews. Chemistry · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Parisa ShiriDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Veronica LaiDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Tara ZepelDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Daniel GriffinAmgen Inc., Cambridge, MA 02141, USA.
Jonathan ReifmanAmgen Inc., Cambridge, MA 02141, USA.
Sean ClarkDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Shad GrunertDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Lars P E YunkerDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Sebastian SteinerDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Henry SituDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Fan YangDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Paloma L PrietoDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.
Jason E HeinDepartment of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Solubility screening is an essential, routine process that is often labor intensive. Robotic platforms have been developed to automate some aspects of the manual labor involved. However, many of the existing systems rely on traditional analytic techniques such as high-performance liquid chromatography, which require pre-calibration for each compound and can be resource consuming. In addition, automation is not typically end-to-end, requiring user intervention to move vials, establish analytical methods for each compound and interpret the raw data. We developed a closed-loop, flexible robotic system with integrated solid and liquid dosing capabilities that relies on computer vision and iterative feedback to successfully measure caffeine solubility in multiple solvents. After initial researcher input (<2 min), the system ran autonomously, screening five different solvent systems (20-80 min each). The resulting solubility values matched those obtained using traditional manual techniques.

Indexed as

automationengineeringgreen chemistryorganic chemistryorganic synthesis

Identifiers

PMID33718828
PMCPMC7921605

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.