AIMC Topic: Particle Size
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Artificial Intelligence Tools for Scaling Up of High Shear Wet Granulation Process.
Journal of pharmaceutical sciences
Nov 2, 2016
The results presented in this article demonstrate the potential of artificial intelligence tools for predicting the endpoint of the granulation process in high-speed mixer granulators of different scales from 25L to 600L. The combination of neurofuzz...
A Practical Framework Toward Prediction of Breaking Force and Disintegration of Tablet Formulations Using Machine Learning Tools.
Journal of pharmaceutical sciences
Oct 27, 2016
Enabling the paradigm of quality by design requires the ability to quantitatively correlate material properties and process variables to measureable product performance attributes. Conventional, quality-by-test methods for determining tablet breaking...
Evaluating the predictability of PM grades in Seoul, Korea using a neural network model based on synoptic patterns.
Environmental pollution (Barking, Essex : 1987)
Sep 6, 2016
As of November 2014, the Korean Ministry of Environment (KME) has been forecasting the concentration of particulate matter with diameters ≤ 10 μm (PM) classified into four grades: low (PM ≤ 30 μg m), moderate (30 < PM ≤ 80 μg m), high (80 < PM ≤ 150 ...
Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.
Biotechnology progress
Aug 22, 2016
This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating pa...
An Artificial Neural Network Based Analysis of Factors Controlling Particle Size in a Virgin Coconut Oil-Based Nanoemulsion System Containing Copper Peptide.
PloS one
Jul 6, 2016
A predictive model of a virgin coconut oil (VCO) nanoemulsion system for the topical delivery of copper peptide (an anti-aging compound) was developed using an artificial neural network (ANN) to investigate the factors that influence particle size. F...
Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches.
SAR and QSAR in environmental research
Jun 22, 2016
The understanding of the mechanisms and interactions that occur when nanomaterials enter biological systems is important to improve their future use. The adsorption of proteins from biological fluids in a physiological environment to form a corona on...
Artificial neural network models for prediction of daily fine particulate matter concentrations in Algiers.
Environmental science and pollution research international
Apr 4, 2016
Neural network (NN) models were evaluated for the prediction of suspended particulates with aerodynamic diameter less than 10-μm (PM10) concentrations. The model evaluation work considered the sequential hourly concentration time series of PM10, whic...
Implementation of an artificial neural network as a PAT tool for the prediction of temperature distribution within a pharmaceutical fluidized bed granulator.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Mar 15, 2016
In this study, a novel in-line measurement technique of the air temperature distribution during a granulation process using a conical fluidized bed was designed and built for the purpose of measuring the temperature under the Process Analytical Techn...
Bending of Responsive Hydrogel Sheets Guided by Field-Assembled Microparticle Endoskeleton Structures.
Small (Weinheim an der Bergstrasse, Germany)
Mar 10, 2016
Hydrogel composites that respond to stimuli can form the basis of new classes of biomimetic actuators and soft robotic components. Common latex microspheres can be assembled and patterned by AC electric fields within a soft thermoresponsive hydrogel....
Nanocomposites of gold nanoparticles and graphene oxide towards an stable label-free electrochemical immunosensor for detection of cardiac marker troponin-I.
Analytica chimica acta
Dec 30, 2015
A stable label-free amperometric immunosensor is presented based on gold nanoparticles and graphene oxide nanocomposites for detection of cardiac troponin-I in the early diagnosis of myocardial infarction. For designing of the sensing platform, first...
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