In silico co-crystal design: assessment of the latest advances

C von Essen, D Luedeker - Drug Discovery Today, 2023 - Elsevier
Pharmaceutical co-crystals represent a growing class of crystal forms in the context of
pharmaceutical science. They are attractive to pharmaceutical scientists because they …

Co-crystal nanoarchitectonics as an emerging strategy in attenuating cancer: Fundamentals and applications

P Kumbhar, K Kolekar, C Khot, S Dabhole… - Journal of Controlled …, 2023 - Elsevier
Cancer ranks as the second foremost cause of death in various corners of the globe. The
clinical uses of assorted anticancer therapeutics have been limited owing to the poor …

Cocrystal virtual screening based on the XGBoost machine learning model

D Yang, L Wang, P Yuan, Q An, B Su, M Yu… - Chinese Chemical …, 2023 - Elsevier
Co-crystal formation can improve the physicochemical properties of a compound, thus
enhancing its druggability. Therefore, artificial intelligence-based co-crystal virtual screening …

Efficient Screening of Coformers for Active Pharmaceutical Ingredient Cocrystallization

IJ Sugden, DE Braun, DH Bowskill… - Crystal Growth & …, 2022 - ACS Publications
Controlling the physical properties of solid forms for active pharmaceutical ingredients (APIs)
through cocrystallization is an important part of drug product development. However, it is …

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 …

Cocrystals and drug–drug cocrystals of anticancer drugs: A perception towards screening techniques, preparation, and enhancement of drug properties

DD Kara, M Rathnanand - Crystals, 2022 - mdpi.com
The most favored approach for drug administration is the oral route. Several anticancer
drugs come under this category and mostly lack solubility and oral bioavailability, which are …

General graph neural network-based model to accurately predict cocrystal density and insight from data quality and feature representation

J Guo, M Sun, X Zhao, C Shi, H Su… - Journal of Chemical …, 2023 - ACS Publications
Cocrystal engineering as an effective way to modify solid-state properties has inspired great
interest from diverse material fields while cocrystal density is an important property closely …

Machine Learning-Guided Prediction of Cocrystals Using Point Cloud-Based Molecular Representation

S Ahmadi, MA Ghanavati, S Rohani - Chemistry of Materials, 2024 - ACS Publications
The design and synthesis of cocrystals have emerged as promising crystal engineering
strategies for enhancing the physicochemical properties of a diverse range of target …

Cocrystal prediction of bexarotene by graph convolution network and bioavailability improvement

F Xiao, Y Cheng, JR Wang, D Wang, Y Zhang, K Chen… - Pharmaceutics, 2022 - mdpi.com
Bexarotene (BEX) was approved by the FDA in 1999 for the treatment of cutaneous T-cell
lymphoma (CTCL). The poor aqueous solubility causes the low bioavailability of the drug …

Molecular descriptors property prediction using transformer-based approach

T Tran, C Ekenna - International Journal of Molecular Sciences, 2023 - mdpi.com
In this study, we introduce semi-supervised machine learning models designed to predict
molecular properties. Our model employs a two-stage approach, involving pre-training and …