AIMC Topic: Drug Liberation

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Preparation of agar nanospheres: comparison of response surface and artificial neural network modeling by a genetic algorithm approach.

Carbohydrate polymers
Multivariate nature of drug loaded nanospheres manufacturing in term of multiplicity of involved factors makes it a time consuming and expensive process. In this study genetic algorithm (GA) and artificial neural network (ANN), two tools inspired by ...

Implementing partial least squares and machine learning regressive models for prediction of drug release in targeted drug delivery application.

Scientific reports
A combined methodology was performed based on chemometrics and machine learning regressive models in estimation of polysaccharide-coated colonic drug delivery. The release of medication was measured using Raman spectroscopy and the data was used for ...

Machine learning predictions of drug release from isocyanate-derived aerogels.

Journal of materials chemistry. B
This work utilized machine learning (ML) algorithms to predict and validate the drug release kinetics of a short worm-like nanostructured isocyanate-derived aerogel: the first time ML has been employed to study the drug delivery properties of this i...

Supervised machine learning for predicting drug release from acetalated dextran nanofibers.

Biomaterials science
Electrospun drug-loaded polymeric nanofibers can improve the efficacy of therapeutics for a variety of implications. By design, these biomaterial platforms can enhance drug bioavailability and site-specific delivery while reducing off-target toxiciti...

A novel scheme for non-invasive drug delivery with a magnetically controlled drug delivering capsule endoscope.

Journal of controlled release : official journal of the Controlled Release Society
There is a lack of effective means for precise drug delivery of gastrointestinal diseases. Herein we report a novel magnetically controlled drug delivering capsule endoscope (MDCE) to achieve precision drug delivery for gastrointestinal diseases. MDC...

Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine.

Technology in cancer research & treatment
OBJECTIVE: This study presents a comparative analysis of RF and SVM for predicting calcein release from ultrasound-triggered, targeted liposomes under varied low-frequency ultrasound (LFUS) power densities (6.2, 9, and 10 mW/cm).

Diversified Applications of Self-assembled Nanocluster Delivery Systems- A State-ofthe- art Review.

Current pharmaceutical design
BACKGROUND: For the nanoparticulate system and the transportation of cellular elements for the fabrication of microelectronic devices, self-assembled nanoclusters arrange the components into an organized structure. Nanoclusters reduce transcytosis an...

Optimization of metronidazole SR buccal tablet for gingivitis using genetic algorithm.

Pakistan journal of pharmaceutical sciences
Gingivitis is a condition that needs sustained concentration of antibiotic locally over extended period of time. The current study aimed to formulate and evaluate the sustained and localized release of metronidazole (MTZ) as mucoadhesive buccal table...

Improvement of solubility and dissolution of ebastine by fabricating phosphatidylcholine/ bile salt bilosomes.

Pakistan journal of pharmaceutical sciences
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 ...