Recent trends and perspectives of artificial intelligence-based machine learning from discovery to manufacturing in biopharmaceutical industry
Background Machine learning (ML) tools have become invaluable in potential drug
candidate screening, formulation development, manufacturing, and characterization of …
candidate screening, formulation development, manufacturing, and characterization of …
State-of-the-art review of neural network applications in pharmaceutical manufacturing: current state and future directions
Neural network applications, as an emerging machine learning technology, are increasingly
being integrated into pharmaceutical manufacturing technologies, offering significant …
being integrated into pharmaceutical manufacturing technologies, offering significant …
[HTML][HTML] Appropriate budget contingency determination for construction projects: State-of-the-art
T Ammar, M Abdel-Monem, K El-Dash - Alexandria Engineering Journal, 2023 - Elsevier
Contingency is a critical component in the cost estimation process for any construction
project. The contingency reserve considers potential costs related to risks and uncertainties …
project. The contingency reserve considers potential costs related to risks and uncertainties …
[HTML][HTML] An artificial neural network-particle swarm optimization (ANN-PSO) approach to predict the aeration efficiency of venturi aeration system
In the present study, the artificial neural network-particle swarm optimization (ANN-PSO)
approach was adopted for optimizing the standard aeration efficiency (SAE) of the venturi …
approach was adopted for optimizing the standard aeration efficiency (SAE) of the venturi …
[HTML][HTML] Interpretable artificial neural networks for retrospective QbD of pharmaceutical tablet manufacturing based on a pilot-scale developmental dataset
B Nagy, Á Szabados-Nacsa, G Fülöp… - International Journal of …, 2023 - Elsevier
As the pharmaceutical industry increasingly adopts the Pharma 4.0. concept, there is a
growing need to effectively predict the product quality based on manufacturing or in-process …
growing need to effectively predict the product quality based on manufacturing or in-process …
Serial artificial neural networks characterized by Gaussian mixture for the modelling of the Consigma25 continuous manufacturing line
In this research, the Consigma25 Continuous Manufacturing (CM) Line is statistically
analysed and modelled. First, the main effects plot is employed to examine the effects of …
analysed and modelled. First, the main effects plot is employed to examine the effects of …
[HTML][HTML] Explainable deep recurrent neural networks for the batch analysis of a pharmaceutical tableting process in the spirit of Pharma 4.0
Due to the continuously increasing Cost of Goods Sold, the pharmaceutical industry has
faced several challenges, and the Right First-Time principle with data-driven decision …
faced several challenges, and the Right First-Time principle with data-driven decision …
Comparing the performance of Raman and near-infrared imaging in the prediction of the in vitro dissolution profile of extended-release tablets based on artificial …
In this work, the performance of two fast chemical imaging techniques, Raman and near-
infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug …
infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug …
Enantioselective nanofiltration using predictive process modeling: Bridging the gap between materials development and process requirements
Organic solvent nanofiltration (OSN) is a low-energy alternative for continuous separations
in the chemical industry. As the pharmaceutical sector increasingly turns toward continuous …
in the chemical industry. As the pharmaceutical sector increasingly turns toward continuous …
Magnetic impacts on double diffusion of a non‐Newtonian NEPCM in a grooved cavity: ANN model with ISPH simulations
Employing phase change materials (PCMs) offers the advantage of storing and releasing
thermal energy while ensuring temperature stability. This characteristic makes PCMs …
thermal energy while ensuring temperature stability. This characteristic makes PCMs …