ArticleJournal of separation science2026
Predicting the Aqueous Solubility of Neutral Organic Compounds by Reversed-Phase Liquid Chromatography.
Article in Journal of separation science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate estimation of water solubility is crucial for chemical screening, yet traditional predictive tools such as the General Solubility Equation (GSE) require melting point and octanol-water partition coefficient data and often struggle with weak electrolytes. This study presents two highly efficient reversed-phase liquid chromatography (RPLC) correlation strategies evaluated, comprising 49 binary solvent systems on three stationary phases. First, simple, melting point, octanol-water partition coefficient, and descriptor-free, isocratic models were explored to estimate the water solubility of neutral organic compounds using RPLC retention as the sole input. This approach demonstrated superior predictive accuracy of 0.307 log units and a more uniform error distribution across both non-electrolytes and weak electrolytes than the more conventional GSE. Second, to improve the predictive accuracy of estimating water solubility, RPLC retention and melting point data were explored. Predictive accuracy improved notably at higher organic volume fractions (50%-70% v/v) across all evaluated stationary phases. The correlation model comprising 70% (v/v) acetonitrile on an XTerra MS C18 stationary phase yielded a coefficient of determination of 0.962, a standard deviation of the model fit of 0.276, and an average absolute error value of 0.222. Together, these complementary chromatographic modelling strategies offer powerful, high-throughput alternatives for rapid solubility screening: providing either a direct, descriptor-free approach for compounds lacking structural information or a highly precise RPLC model approach combining retention and melting point data that minimizes prediction errors below 0.3 log units.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.