AIMC Topic: Particle Size

Clear Filters Showing 61 to 70 of 221 articles

Particle formation in response to different protein formulations and containers: Insights from machine learning analysis of particle images.

Journal of pharmaceutical sciences
Subvisible particle count is a biotherapeutics stability indicator widely used by pharmaceutical industries. A variety of stresses that biotherapeutics are exposed to during development can impact particle morphology. By classifying particle morpholo...

Constructing a visual detection model for floc settling velocity using machine learning.

Journal of environmental management
Optimizing the dosage of coagulant is a time-consuming process, and real-time evaluation of floc settling velocity can quickly predict the coagulation effect and optimize the dosage. This study used a convolutional neural network (CNN) model to analy...

Transitioning the production of lipidic mesophase-based delivery systems from lab-scale to robust industrial manufacturing following a risk-based quality by design approach augmented by artificial intelligence.

Journal of colloid and interface science
Lipidic mesophase drug carriers have demonstrated the capacity to host and effectively deliver a wide range of active pharmaceutical ingredients, yet they have not been as extensively commercialized as other lipid-based products, such as liposomal de...

Development of fucoidan/polyethyleneimine based sorafenib-loaded self-assembled nanoparticles with machine learning and DoE-ANN implementation: Optimization, characterization, and in-vitro assessment for the anticancer drug delivery.

International journal of biological macromolecules
This study aims to develop sorafenib-loaded self-assembled nanoparticles (SFB-SANPs) using the combined approach of artificial neural network and design of experiments (ANN-DoE) and to compare it with other machine learning (ML) models. The central c...

Machine learning-driven QSAR models for predicting the cytotoxicity of five common microplastics.

Toxicology
In the field of microplastics (MPs) toxicity prediction, machine learning (ML) computer simulation techniques are showing great potential. In this study, six ML algorithms were utilized to predict the toxicity of MPs on BEAS-2B cells based on quantit...

Magnetic-actuated hydrogel microrobots with multimodal motion and collective behavior.

Journal of materials chemistry. B
Magnetic-actuated miniature robots have sparked growing interest owing to their promising potential in biomedical applications, such as noninvasive diagnosis, cargo delivery, and microsurgery. Innovations are required to combine biodegradable materia...

Characterizing sector-oriented roadside exposure to ultrafine particles (PM) via machine learning models: Implications of covariates influences on sectors variability.

Environmental pollution (Barking, Essex : 1987)
Ultrafine particles (UFPs; PM) possess intensified health risk due to their smaller size and unique spatial variability. One of major emission sources for UFPs is vehicle exhaust, which varies based on the traffic composition in each type of roadside...

Exposure Pathways of Ambient Magnetite Nanoparticles Revealed by Machine Learning-Aided Single-Particle Mass Spectrometry.

Nano letters
Nanosized ultrafine particles (UFPs) from natural and anthropogenic sources are widespread and pose serious health risks when inhaled by humans. However, tracing the inhaled UFPs is extremely difficult, and the distribution, translocation, and metab...

A flexible, stretchable and wearable strain sensor based on physical eutectogels for deep learning-assisted motion identification.

Journal of materials chemistry. B
Physical eutectogels as a newly emerging type of conductive gel have gained extensive interest for the next generation multifunctional electronic devices. Nevertheless, some obstacles, including weak mechanical performance, low self-adhesive strength...

Molybdenum Disulfide-Assisted Spontaneous Formation of Multistacked Gold Nanoparticles for Deep Learning-Integrated Surface-Enhanced Raman Scattering.

ACS nano
Several fabrication methods have been developed for label-free detection in various fields. However, fabricating high-density and highly ordered nanoscale architectures by using soluble processes remains a challenge. Herein, we report a biosensing pl...