AIMC Topic: Solubility

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ML-Driven Pharmaceutical Cocrystal Technology: Advances in Screening, Property Prediction and Applications.

AAPS PharmSciTech
Recently, pharmaceutical cocrystal technology has garnered considerable global attention because of its innovativeness and environmental sustainability. This technology effectively enhances the bioavailability of poorly soluble drugs and optimizes th...

Combining crystal engineering and surface engineering to estimate the structure -functions relationship of Tafamidis solid state forms with the aid of machine learning.

International journal of pharmaceutics
The mutual benefits of surface engineering and crystal engineering led to the discovery of a pharmaceutical cocrystal with balanced biopharmaceutical properties. The surface engineering of a pharmaceutical API (Active Pharmaceutical Ingredient), name...

Descriptor-First Approach for ADMET Prediction in the PolarisHub Antiviral Challenge.

Journal of chemical information and modeling
The prediction of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties remains a central bottleneck in small-molecule discovery. We present the third-place solution from the PolarisHub Antiviral Competition, covering five ...

Mechanistic, data-driven, and hybrid models: A critical comparison in surrogate drug dissolution modeling.

International journal of pharmaceutics
Mathematical modeling is becoming increasingly important in the pharmaceutical industry. It supports the Quality by Design framework by aiding process understanding and examining the impact of critical material and process parameters on the critical ...

pKa prediction for small molecules: an overview of experimental, quantum, and machine learning-based approaches.

Journal of computer-aided molecular design
The pKa, also known as the logarithmic dissociation constant, is a crucial parameter that defines the ionization level of a molecule when it is in solution. It is essential for several physicochemical properties, including lipophilicity, solubility, ...

Computational analysis on the influence of pressure and temperature on drug solubility in supercritical CO with machine learning and optimizer.

Scientific reports
Machine learning models can be applied for estimation of continuous manufacturing parameters in pharmaceutical processing of oral-solid formulations. Development of Quality by Design (QbD) has motivated the pharmaceutical sector to move towards conti...

Predicting drug solubility in supercritical carbon dioxide green solvent using machine learning models based on thermodynamic properties.

Scientific reports
Reliable prediction of drug solubility in supercritical carbon dioxide (scCO₂) is crucial for the efficient design of pharmaceutical processes, including particle engineering and supercritical fluid-based extraction. Given that experimental determina...

Ag+ modified paper-based SERS combined with SiPLS for quantitative detection of soluble As3+ in aqueous realgar solutions.

Analytica chimica acta
The detection of soluble arsenic in realgar and its preparations is crucial for toxicity evaluation. Therefore, surface-enhanced Raman spectroscopy (SERS) combined with machine learning was applied for the rapid detection of soluble As3+ in realgar a...

From Liquid SNEDDS to Solid SNEDDS: A Comprehensive Review of Their Development and Pharmaceutical Applications.

The AAPS journal
The liquid and solid formulations of self-nano-emulsifying drug delivery systems (SNEDDS) have garnered significant attention in the pharmaceutical field for their ability to enhance the solubility and absorption of hydrophobic drugs. While both liqu...

Integrated experimental, computational and machine learning approaches for the development of Apremilast-Aceclofenac coamorphous systems.

International journal of pharmaceutics
Understanding the molecular mechanisms of drug coamorphization remains a key challenge in solid-state pharmaceutics. This study presents a molecular level strategy for designing drug-drug coamorphous systems (CAMs) of apremilast (APR) and aceclofenac...