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 …

[HTML][HTML] 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 …

Artificial intelligence assisted pharmaceutical crystallization

Z Zhu, Y Zhang, Z Wang, W Tang, J Wang… - Crystal Growth & …, 2024 - ACS Publications
The ever-increasing demand for novel drug development has spurred the adaptation of
conventional research methods in the era of artificial intelligence. Pharmaceutical …

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 …

Speeding up the cocrystallization process: Machine learning-combined methods for the prediction of multicomponent systems

R Birolo, F Bravetti, E Alladio, E Priola… - Crystal Growth & …, 2023 - ACS Publications
Pharmaceutical cocrystals are crystalline materials composed of at least two molecules, ie,
an active pharmaceutical ingredient (API) and a coformer, assembled by noncovalent forces …

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 …

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 …

[HTML][HTML] 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 …

Transformer-based models for chemical SMILES representation: A comprehensive literature review

ME Mswahili, YS Jeong - Heliyon, 2024 - cell.com
Pre-trained chemical language models (CLMs) have attracted increasing attention within the
domains of cheminformatics and bioinformatics, inspired by their remarkable success in the …