Evidence map›Paper›PMID 41495125›Full record

ArticleScientific reports2026

Solubility of Glibenclamide in supercritical solvent versus pressure and temperature via development of machine learning and rain optimization algorithm.

Hadil Faris Alotaibi, Chou-Yi Hsu, Fadhil Faez Sead, Anupam Yadav, S Renuka Jyothi, Swati Mishra, Bilakshan Purohit, Anorgul Ashirova, Temur Eshchanov, Ashish Singh Chauhan

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Hadil Faris AlotaibiDepartment of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah Bint AbdulRahman University, 11671, Riyadh, Saudi Arabia. Hfalotaibi@pnu.edu.sa.
Chou-Yi HsuThunderbird School of Global Management, Arizona State University Tempe Campus, Phoenix, AZ, 85004, USA. t545316@gmail.com.
Fadhil Faez SeadDepartment of Dentistry, College of Dentistry, The Islamic University, Najaf, Iraq.
Anupam YadavDepartment of Computer Engineering and Application, GLA University Mathura, Bharthia, 281406, India.
S Renuka JyothiDepartment of Biotechnology and Genetics, School of Sciences, JAIN (Deemed to Be University), Bangalore, Karnataka, India.
Swati MishraDepartment of Pharmacology, IMS and SUM Hospital, Siksha 'O' Anusandhan (Deemed to Be University), Bhubaneswar, Odisha, 751003, India.
Bilakshan PurohitCentre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, India.
Anorgul AshirovaDepartment of General Professional Sciences, Mamun University, Khiva, Uzbekistan.
Temur EshchanovUrgench State University Named After Abu Rayhon Beruni, Urgench, Uzbekistan.
Ashish Singh ChauhanDivision of Research and Innovation, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, Uttarakhand, India.

Funding

Princess Nourah Bint Abdulrahman University PNURSP2025R205
6 · The paper itself

Abstract

This study develops machine-learning models for predicting the solubility of Glibenclamide and the density of supercritical CO₂ under varying temperature and pressure conditions. Three regression techniques-Polynomial Kernel Ridge Regression (PKR), Weighted Least Squares (WLS), and Gradient Boosting Trees (GBT)-were employed, with hyperparameters optimized via the Rain Optimization Algorithm (ROA). PKR delivered the highest solubility-prediction accuracy, achieving an R

Indexed as

AlgorithmsGlyburideMachine LearningSolventsCarbon DioxidePressureSolubilityTemperatureCarbon DioxideGlyburideSolventsGradient boosting treesKernel ridge regressionModelingPharmaceuticsWeighted least squares

Identifiers

PMID41495125
PMCPMC12855953

What OpenQuestion holds

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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.