State-of-the-art review of artificial neural networks to predict, characterize and optimize pharmaceutical formulation

S Wang, J Di, D Wang, X Dai, Y Hua, X Gao, A Zheng… - Pharmaceutics, 2022 - mdpi.com
During the development of a pharmaceutical formulation, a powerful tool is needed to extract
the key points from the complicated process parameters and material attributes. Artificial …

Toward the integration of machine learning and molecular modeling for designing drug delivery nanocarriers

XJ Gao, K Ciura, Y Ma, A Mikolajczyk… - Advanced …, 2024 - Wiley Online Library
The pioneering work on liposomes in the 1960s and subsequent research in controlled drug
release systems significantly advances the development of nanocarriers (NCs) for drug …

Application of ensemble machine learning approach to assess the factors affecting size and polydispersity index of liposomal nanoparticles

B Hoseini, MR Jaafari, A Golabpour… - Scientific Reports, 2023 - nature.com
Liposome nanoparticles have emerged as promising drug delivery systems due to their
unique properties. Assessing particle size and polydispersity index (PDI) is critical for …

Optimizing nanoliposomal formulations: Assessing factors affecting entrapment efficiency of curcumin-loaded liposomes using machine learning

B Hoseini, MR Jaafari, A Golabpour… - International Journal of …, 2023 - Elsevier
Background Curcumin faces challenges in clinical applications due to its low bioavailability
and poor water solubility. Liposomes have emerged as a promising delivery system for …

Intriguing of pharmaceutical product development processes with the help of artificial intelligence and deep/machine learning or artificial neural network

N Jariwala, CL Putta, K Gatade, M Umarji… - Journal of Drug Delivery …, 2023 - Elsevier
The objectives of current review are (1) to provide a historical overview of artificial
intelligence and deep/machine learning (AI & D/ML) or Artificial Neural Network (ANN)(2) to …

[HTML][HTML] Predicting liposome formulations by the integrated machine learning and molecular modeling approaches

R Han, Z Ye, Y Zhang, Y Cheng, Y Zheng… - Asian Journal of …, 2023 - Elsevier
Liposome is one of the most widely used carriers for drug delivery because of the great
biocompatibility and biodegradability. Due to the complex formulation components and …

Impact of critical process parameters and critical material attributes on the critical quality attributes of liposomal formulations prepared using continuous processing

G Yenduri, AP Costa, X Xu, DJ Burgess - International Journal of …, 2022 - Elsevier
Liposomes were one of the earliest drug delivery vehicles used for anti-cancer therapeutics
and similarly, lipid-based nanoparticles have been used for abundance of applications as …

Exploiting Pharma 4.0 Technologies in the Non-Biological Complex Drugs Manufacturing: Innovations and Implications

V Malheiro, J Duarte, F Veiga, F Mascarenhas-Melo - Pharmaceutics, 2023 - mdpi.com
The pharmaceutical industry has entered an era of transformation with the emergence of
Pharma 4.0, which leverages cutting-edge technologies in manufacturing processes. These …

Environmentally friendly PAEs alternatives with desired synthesizability by in silico methods

H Yang, Q Li, Y Wu, Y Zhao, N Hao, W He… - Journal of Cleaner …, 2023 - Elsevier
Phthalate esters (PAEs) as plasticizers posed significant environmental and human health
risks during the production and application processes. This study aims to investigate the …

Neural network prediction model of cocrystal melting temperature based on molecular descriptors and graphs

H Yue, J Wang, M Lu - Crystal Growth & Design, 2023 - ACS Publications
Among the physical properties characterizing cocrystals, melting temperature is one of the
primary properties. Its prediction has been done by researchers, but in the known prediction …