AIMC Topic: Solubility
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Comparison of novel granulated pellet-containing tablets and traditional pellet-containing tablets by artificial neural networks.
Pharmaceutical development and technology
Apr 24, 2014
Novel granulated pellets technique was adopted to prepare granulated pellet-containing tablets (GPCT). GPCT and traditional pellet-containing tablets (PCT) were prepared according to 29 formulations devised by the Design Expert 7.0, with doxycycline ...
Development of machine learning models for estimation of disintegration time on fast-disintegrating tablets.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Aug 1, 2025
The disintegration time for solid dosage oral formulations is directly influenced by diverse factors such as molecular properties, physical characteristics, excipient compositions, and formulation-specific attributes. This research addresses the chal...
Advancing Amorphous Solid Dispersions Design: Insights into Dissolution Kinetics via Thermodynamic Descriptor and Machine Learning.
Molecular pharmaceutics
Jul 7, 2025
Amorphous solid dispersions (ASD) are an effective strategy for enhancing the solubility and bioavailability of poorly soluble drugs. However, designing and optimizing ASD formulations often rely on extensive dissolution experiments without sufficie...
Predicting the solubility of drugs in supercritical carbon dioxide using machine learning and atomic contribution.
European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Jun 1, 2025
The pharmaceutical sector is aware of supercritical CO (SC-CO) as a possible replacement for problematic organic solvents. Using a novel artificial intelligence (AI) strategy to predict drug solubility using the SC-CO system mathematically has been d...
Prediction of the Appropriate Temperature and Pressure for Polymer Dissolution Using Machine Learning Models.
Molecular informatics
Feb 1, 2025
The widespread use of polymer solutions in the chemical industry poses a significant challenge in determining optimal dissolution conditions. Traditionally, researchers have relied on experimental methods to estimate the processing parameters needed ...
Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions.
Polimery w medycynie
Jan 1, 2024
BACKGROUND: Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use.
Combining machine learning and molecular simulations to predict the stability of amorphous drugs.
The Journal of chemical physics
Jul 7, 2023
Amorphous drugs represent an intriguing option to bypass the low solubility of many crystalline formulations of pharmaceuticals. The physical stability of the amorphous phase with respect to the crystal is crucial to bring amorphous formulations into...
A general optimization protocol for molecular property prediction using a deep learning network.
Briefings in bioinformatics
Jan 17, 2022
The key to generating the best deep learning model for predicting molecular property is to test and apply various optimization methods. While individual optimization methods from different past works outside the pharmaceutical domain each succeeded i...
Different molecular enumeration influences in deep learning: an example using aqueous solubility.
Briefings in bioinformatics
May 20, 2021
Aqueous solubility is the key property driving many chemical and biological phenomena and impacts experimental and computational attempts to assess those phenomena. Accurate prediction of solubility is essential and challenging, even with modern comp...
Improvement of solubility and dissolution of ebastine by fabricating phosphatidylcholine/ bile salt bilosomes.
Pakistan journal of pharmaceutical sciences
Sep 1, 2020
Although ebastine (EBT) can impede histamine-induced skin allergic reaction and persuade long acting selective H1 receptor antagonistic effects but its poor water solubility circumscribed its clinical application. The main objective of this research ...
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