AIMC Topic: Solubility

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Calibrating the prediction model of soluble solids content and firmness in kiwifruit across years based on NIR spectroscopy using model transfer and transfer learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Near-infrared (NIR) spectroscopy has been widely used in nondestructive detection of fruit internal quality. However, the biological variability of fruit would change their texture, which may lead to the failure of fruit quality prediction models bui...

Real-time component-based particle size measurement and dissolution prediction during continuous powder feeding using machine vision and artificial intelligence-based object detection.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
This work presents a system, in which machine vision combined with artificial intelligence-based image analysis was used to determine the component-based particle size distribution of pharmaceutical powder blends. The blends consisted of acetylsalicy...

Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes.

Journal of inorganic biochemistry
Predicting the solubility and lipophilicity of platinum(II, IV) complexes is essential for prioritizing potential anticancer candidates in drug discovery. This study introduces the first publicly available online model for predicting the solubility o...

Enhancing Predictions of Drug Solubility Through Multidimensional Structural Characterization Exploitation.

IEEE journal of biomedical and health informatics
Solubility is not only a significant physical property of molecules but also a vital factor in small-molecule drug development. Determining drug solubility demands stringent equipment, controlled environments, and substantial human and material resou...

Exploring a universal model for predicting blueberry soluble solids content based on hyperspectral imaging and transfer learning to address spatial heterogeneity challenge.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Accurate assessment of soluble solid content (SSC) in blueberries is crucial for quality evaluation. However, in real production lines, blueberries are usually in random placement and the biological heterogeneity of blueberry parts can lead to spectr...

Application of machine learning approach to estimate the solubility of some solid drugs in supercritical CO.

Scientific reports
Accurate estimation of the solubility of solid drugs (SDs) in the supercritical carbon dioxide (SC-CO) plays an essential role in the related technologies. In this study, artificial intelligence models (AIMs) by gene expression programming (GEP) and ...

Correlation of rivaroxaban solubility in mixed solvents for optimization of solubility using machine learning analysis and validation.

Scientific reports
In this study, the solubility of rivaroxaban, a poorly water-soluble drug, was investigated in mixed solvent systems to address challenges in pharmaceutical formulation and bioavailability enhancement. Solubility optimization is essential for the eff...

Determination of 5-fluorouracil anticancer drug solubility in supercritical COusing semi-empirical and machine learning models.

Scientific reports
In order to provide the facilities to design the supercritical fluid (SCF) processes for micro or nanosizing of solid solute compounds such as drugs, it is essential to obtain their solubility in green solvents like pressurized CO. This important rol...

Machine learning integrated with in vitro experiments for study of drug release from PLGA nanoparticles.

Scientific reports
This paper investigates delivery of encapsulated drug from poly lactic-co-glycolic micro-/nano-particles. Experimental data collected from about 50 papers are analyzed by machine learning algorithms including linear regression, principal component an...

Machine Learning-Based Prediction of Drug Solubility in Lipidic Environments: The Sol_ME Tool for Optimizing Lipid-Based Formulations with a Preliminary Apalutamide Case Study.

AAPS PharmSciTech
Lipid-based formulations are essential for enhancing drug solubility and bioavailability, yet selecting optimal lipid excipients for specific drugs remains challenging. This study introduces Sol_ME, a machine learning-based model designed to predict ...