Work

Comparative Assessment of Statistical and Thermodynamic Prediction Methods for Solvate Formation: A Case Study with Curcumin and Its Derivatives

Year: 2025

Type: article

Abstract: This study compares statistical and thermodynamic methodologies for predicting solvate formation using curcumin (CUR) and its derivatives demethoxycurcumin (DMC) and bisdemethoxycurcumin (BDMC) as models. We evaluated the performance of Statistical Frequency of Interaction for Multicomponent Prediction (SFIMP) and Conductor-like Screening Model for Realistic Solvents (COSMO-RS) methods to identify solvents likely to form solvates. A comprehensive crystallization screen yielded several new solvated and hydrated forms. Our results show that hydrogen bond propensity (HBP) performed best among individual predictors, while COSMO-RS combined with HBP yielded superior predictive accuracy overall. These insights aid rational design and screening of multicomponent solid forms in pharmaceutical development.

Source: Crystal Growth & Design

DOI: 10.1021/acs.cgd.5c01343

Authors: Julian Ticona-Chambi, Duane Choquesillo-Lazarte, Silvia Lucia Cuffini, Lourdes Infantes

Institutions: Universidade Federal de São Paulo, Consejo Superior de Investigaciones Científicas, Instituto Andaluz de Ciencias de la Tierra, Instituto de Química Física Blas Cabrera

Language: English

Topic: Crystallization and Solubility Studies

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,500