Evidence mapPaperPMID 42326669Full record

ArticleACS omega2026

Comparing the Utility of Cannabidiol Quantitation Methods for Use in High-Throughput In Vitro Assays.

Gokce Alp, Behnoush Kermanshahi, Andrea Olaizola, Frantz Le Devedec, Jessica Kalra

Abstract read
In one paragraph

Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Gokce AlpApplied Research Centre, Langara College, Vancouver V5Y 2Z6, British Columbia, Canada.ORCID https://orcid.org/0000-0001-8155-7377
Behnoush KermanshahiApplied Research Centre, Langara College, Vancouver V5Y 2Z6, British Columbia, Canada.
Andrea OlaizolaFaculty of Pharmaceutical Sciences, University of British Columbia, Vancouver V6T 1Z3, British Columbia, Canada.
Frantz Le DevedecAcceleration Consortium, University of Toronto, Toronto M5S3M2, Ontario, Canada.
Jessica KalraApplied Research Centre, Langara College, Vancouver V5Y 2Z6, British Columbia, Canada.ORCID https://orcid.org/0009-0004-3383-6901

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, isolated phytocannabinoids have received significant attention for their therapeutic potential, showing diverse pharmacological effects in vitro and in preclinical studies. However, in vitro drug efficacy and drug development studies are challenging to perform as accurate quantification of phytocannabinoids is required to generate dose response curves and pharmacokinetic profiles. While assessment of free cannabinoids is straightforward, assessing small quantities in cell culture media or as part of a formulation is difficult due to the low solubility of cannabinoids in aqueous medium and high propensity for adsorbing to plastics. Therefore, to pursue a phytocannabinoid drug development program, one of the major obstacles to overcome is selecting an appropriate analytical method that provides both accuracy and efficiency for cannabinoid quantitation. To address this challenge, three methods for quantifying cannabinoids are compared: high performance liquid chromatography (HPLC), UV/vis Spectrophotometry, and colorimetric analysis using Fast Blue B Salt (FBBS). Each method demonstrates advantages and limitations, and a comprehensive understanding of their utility in different experimental workflows is necessary for advancing the study of cannabinoids as therapeutic agents.

Identifiers

PMID42326669
PMCPMC13280897

What Socratic 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 Socratic graph.