Chemistry, Pharmaceutical
Showing 51 to 60 of 161 articles
Virtual screening of drug materials for pharmaceutical tablet manufacturability with reference to sticking.
International journal of pharmaceutics
Sep 16, 2024
The manufacturing of pharmaceutical solid dosage forms, such as tablets involves a large number of successive processing operations including crystallisation of the drug substance, granulation, drying, milling, mixing of the formulation, and compacti...
Evaluation of floatability characteristics of gastroretentive tablets using VIS imaging with artificial neural networks.
European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Sep 11, 2024
Gastroretentive dosage forms are recommended for several active substances because it is often necessary for the drug to be released from the carrier system into the stomach over an extended period. Among gastroretentive dosage forms, floating tablet...
A comprehensive study of pharmaceutics solubility in supercritical solvent through diverse thermodynamic and hybrid Machine learning approaches.
International journal of pharmaceutics
Aug 11, 2024
The pharmaceutical industry is increasingly drawn to the research of innovative drug delivery systems through the use of supercritical CO (scCO)-based techniques. Measuring the solubility of drugs in scCO at varying conditions is a crucial parameter ...
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Optimization and evaluation of modified release solid dosage forms using artificial neural network.
Scientific reports
Jul 16, 2024
This study aims to optimize and evaluate drug release kinetics of Modified-Release (MR) solid dosage form of Quetiapine Fumarate MR tablets by using the Artificial Neural Networks (ANNs). In training the neural network, the drug contents of Quetiapin...
Hybrid modeling of T-shaped partial least squares regression and transfer learning for formulation and manufacturing process development of new drug products.
International journal of pharmaceutics
Jul 14, 2024
T-shaped partial least squares regression (T-PLSR) is a valuable machine learning technique for the formulation and manufacturing process development of new drug products. An accurate T-PLSR model requires experimental data with multiple formulations...
Smart laser Sintering: Deep Learning-Powered powder bed fusion 3D printing in precision medicine.
International journal of pharmaceutics
Jul 6, 2024
Medicines remain ineffective for over 50% of patients due to conventional mass production methods with fixed drug dosages. Three-dimensional (3D) printing, specifically selective laser sintering (SLS), offers a potential solution to this challenge, a...
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Automated Tomographic Assessment of Structural Defects of Freeze-Dried Pharmaceuticals.
AAPS PharmSciTech
Jun 25, 2024
The topology and surface characteristics of lyophilisates significantly impact the stability and reconstitutability of freeze-dried pharmaceuticals. Consequently, visual quality control of the product is imperative. However, this procedure is not onl...
POxload: Machine Learning Estimates Drug Loadings of Polymeric Micelles.
Molecular pharmaceutics
May 28, 2024
Block copolymers, composed of poly(2-oxazoline)s and poly(2-oxazine)s, can serve as drug delivery systems; they form micelles that carry poorly water-soluble drugs. Many recent studies have investigated the effects of structural changes of the polyme...
Exploring the Potential of Artificial Intelligence as a Facilitating Tool for Formulation Development in Fluidized Bed Processor: a Comprehensive Review.
AAPS PharmSciTech
May 13, 2024
This in-depth study looks into how artificial intelligence (AI) could be used to make formulation development easier in fluidized bed processes (FBP). FBP is complex and involves numerous variables, making optimization challenging. Various AI techniq...
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A comprehensive assessment of machine learning algorithms for enhanced characterization and prediction in orodispersible film development.
International journal of pharmaceutics
May 3, 2024
Orodispersible films (ODFs) have emerged as innovative pharmaceutical dosage forms, offering patient-specific treatment through adjustable dosing and the combination of diverse active ingredients. This expanding field generates vast datasets, requiri...
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