Dataset Information

Investigation of COSMO-SAC model for solubility and cocrystal formation of pharmaceutical compounds.

ABSTRACT: In this study, a predictive model named COSMO-SAC was investigated in solid/liquid equilibria for pharmaceutical compounds. The examined properties were the solubility of drug in the pure and mixed solvents, octanol/water partition coefficient, and cocrystal formation. The results of the original COSMO-SAC model (COSMO-SAC (2002)) was compared with a semi-predictive model named Flory-Huggins model and a revised version of the COSMO-SAC (COSMO-SAC (2010)). The results indicated the acceptable accuracy of the COSMO-SAC (2002) in the considered scope. The results emphasized on the suitability of the COSMO-SAC model for simple molecules containing C, H, and O by covalent and hydrogen bonding interactions. Applicability of the COSMO-SAC for more complicated molecules made of various functional groups such as COO and COOH doubly requires more modification in the COSMO-SAC.

SUBMITTER: Mahmoudabadi SZ

PROVIDER: S-EPMC7670437 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Investigation of COSMO-SAC model for solubility and cocrystal formation of pharmaceutical compounds.

Mahmoudabadi Samane Zarei SZ Pazuki Gholamreza G

Scientific reports 20201116 1

In this study, a predictive model named COSMO-SAC was investigated in solid/liquid equilibria for pharmaceutical compounds. The examined properties were the solubility of drug in the pure and mixed solvents, octanol/water partition coefficient, and cocrystal formation. The results of the original COSMO-SAC model (COSMO-SAC (2002)) was compared with a semi-predictive model named Flory-Huggins model and a revised version of the COSMO-SAC (COSMO-SAC (2010)). The results indicated the acceptable acc ...[more]

PMID: 33199834

Similar Datasets

Project description:The quantum mechanics-aided COSMO-SAC activity coefficient model is applied and systematically examined for predicting the thermodynamic compatibility of drugs and polymers. The drug-polymer compatibility is a key aspect in the rational selection of optimal polymeric carriers for pharmaceutical amorphous solid dispersions (ASD) that enhance drug bioavailability. The drug-polymer compatibility is evaluated in terms of both solubility and miscibility, calculated using standard thermodynamic equilibrium relations based on the activity coefficients predicted by COSMO-SAC. As inherent to COSMO-SAC, our approach relies only on quantum-mechanically derived σ-profiles of the considered molecular species and involves no parameter fitting to experimental data. All σ-profiles used were determined in this work, with those of the polymers being derived from their shorter oligomers by replicating the properties of their central monomer unit(s). Quantitatively, COSMO-SAC achieved an overall average absolute deviation of 13% in weight fraction drug solubility predictions compared to experimental data. Qualitatively, COSMO-SAC correctly categorized different polymer types in terms of their compatibility with drugs and provided meaningful estimations of the amorphous-amorphous phase separation. Furthermore, we analyzed the sensitivity of the COSMO-SAC results for ASD to different model configurations and σ-profiles of polymers. In general, while the free volume and dispersion terms exerted a limited effect on predictions, the structures of oligomers used to produce σ-profiles of polymers appeared to be more important, especially in the case of strongly interacting polymers. Explanations for these observations are provided. COSMO-SAC proved to be an efficient method for compatibility prediction and polymer screening in ASD, particularly in terms of its performance-cost ratio, as it relies only on first-principles calculations for the considered molecular species. The open-source nature of both COSMO-SAC and the Python-based tool COSMOPharm, developed in this work for predicting the API-polymer thermodynamic compatibility, invites interested readers to explore and utilize this method for further research or assistance in the design of pharmaceutical formulations.

Dataset Information

Investigation of COSMO-SAC model for solubility and cocrystal formation of pharmaceutical compounds.

Publications

Investigation of COSMO-SAC model for solubility and cocrystal formation of pharmaceutical compounds.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets