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Chemistry, Pharmaceutical

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Combined application of mixture experimental design and artificial neural networks in the solid dispersion development.

Drug development and industrial pharmacy
This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs were prepared by solven...

Optimization of controlled release nanoparticle formulation of verapamil hydrochloride using artificial neural networks with genetic algorithm and response surface methodology.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
This study was performed to optimize the formulation of polymer-lipid hybrid nanoparticles (PLN) for the delivery of an ionic water-soluble drug, verapamil hydrochloride (VRP) and to investigate the roles of formulation factors. Modeling and optimiza...

Advancing Pharmaceutical Science with Artificial Neural Networks: A Review on Optimizing Drug Delivery Systems Formulation.

Current pharmaceutical design
Drug Delivery Systems (DDS) have been developed to address the challenges associated with traditional drug delivery methods. These DDS aim to improve drug administration, enhance patient compliance, reduce side effects, and optimize target therapy. T...

In-line monitoring and endpoint determination of percolation process of herbal medicine using ultraviolet spectroscopy combined with convolutional neural network.

The Journal of pharmacy and pharmacology
OBJECTIVES: As a common step in the herbal medicine production process, percolation usually lacks effective process monitoring methods and is often conducted with fixed process parameters. In this study, an in-line ultraviolet (UV) spectroscopy was u...

Machine Learning and Perturbation Theory Machine Learning (PTML) in Medicinal Chemistry, Biotechnology, and Nanotechnology.

Current topics in medicinal chemistry
Recently, different authors have reported Perturbation Theory (PT) methods combined with machine learning (ML) to obtain PTML (PT + ML) models. They have applied PTML models to the study of different biological systems. Here we present one state-of-a...

PTML Multi-Label Algorithms: Models, Software, and Applications.

Current topics in medicinal chemistry
By combining Machine Learning (ML) methods with Perturbation Theory (PT), it is possible to develop predictive models for a variety of response targets. Such combination often known as Perturbation Theory Machine Learning (PTML) modeling comprises a ...

Artificial Neural Networks in Computer-Aided Drug Design: An Overview of Recent Advances.

Advances in experimental medicine and biology
Computer-aided drug design (CADD) is the framework in which the huge amount of data accumulated by high-throughput experimental methods used in drug design is quantitatively studied. Its objectives include pattern recognition, biomarker identificatio...

Development and application of a comprehensive machine learning program for predicting molecular biochemical and pharmacological properties.

Physical chemistry chemical physics : PCCP
We establish a comprehensive quantitative structure-activity relationship (QSAR) model termed AlphaQ through the machine learning algorithm to associate the fully quantum mechanical molecular descriptors with various biochemical and pharmacological p...