cosmopharm 0.0.2

Predictive modeling for drug-polymer compatibility in pharmaceutical formulations using COSMO-SAC.

COSMOPharm

COSMOPharm is a Python package designed to streamline the predictive modeling of drug-polymer compatibility, crucial for the development of pharmaceutical amorphous solid dispersions. Leveraging the COSMO-SAC (Conductor-like Screening Model Segment Activity Coefficient) model, COSMOPharm offers a robust platform for scientists and researchers to predict solubility, miscibility, and phase behavior in drug formulation processes.

Features

• Compatibility Prediction: Utilize open-source COSMO-SAC model for prediction of drug-polymer compatibility.
• Solubility Calculation: Calculate drug-polymer solubilities to guide the selection of suitable polymers for drug formulations.
• Miscibility and Phase Behavior Analysis: Analyze the miscibility of drug-polymer pairs and understand their phase behavior under various conditions.
• User-friendly Interface: Easy-to-use functions and comprehensive documentation to facilitate research and development in pharmaceutical sciences.

Installation

Please note that COSMOPharm requires the manual installation of the cCOSMO library. Refer to the COSMOSAC GitHub page for detailed instructions.

Once cCOSMO is installed, you can install COSMOPharm using pip:

pip install cosmopharm

Quick Start

Here's a quick example to get you started with COSMOPharm: Example

# Example usage script: example_usage.py

import cCOSMO
from cosmopharm import SLE, LLE, COSMOSAC
from cosmopharm.utils import read_params, create_components

# Rest of the script...

Contributing / Getting Help

Contributions to COSMOPharm are welcome! We accept contributions via pull requests to the GitHub repository.

For bugs, feature requests, or other queries, please open an issue on GitHub.

Citation

If you use COSMOPharm in your research, please consider citing it. You can find the citation format in CITATION.md.

License

COSMOPharm is released under the MIT License. See the LICENSE file for more details.