Predictive modeling for drug-polymer compatibility in pharmaceutical formulations using COSMO-SAC.
Project description
COSMOPharm
COSMOPharm is a Python package designed for predictive modeling of drug-polymer compatibility and drug-solubility in common solvents. It leverages the COSMO-SAC (Conductor-like Screening Model Segment Activity Coefficient) model, offering a robust platform for solubility, miscibility, and phase behavior prediction in drug formulation processes.
Features
- Compatibility Prediction: Predict drug-polymer compatibility using the open-source COSMO-SAC model.
- Solubility Calculation: Guide polymer selection for drug formulations by calculating drug-polymer solubilities.
- Miscibility and Phase Behavior Analysis: Understand drug-polymer miscibility and phase behavior under various conditions.
- User-friendly Interface: Facilitate research with easy-to-use functions and comprehensive documentation.
Associated Research
The development of COSMOPharm is closely tied to ongoing research aimed at enhancing the understanding and application of COSMO-SAC models in drug formulation. A forthcoming manuscript detailing the theoretical foundations and empirical validations of the models used in this package will provide comprehensive insights into the work COSMOPharm supports.
Note: A related publication, provided as an example of the research context, can be found here. This link will be updated to directly point to our specific manuscript upon its publication, enabling users to delve deeper into the scientific basis and applications of COSMOPharm.
Installation
Install COSMOPharm with pip:
pip install cosmopharm
Ensure you have installed the cCOSMO library as per instructions on the COSMOSAC GitHub page.
Quick Start
This minimal example demonstrates how to use COSMOPharm to calculate solubility and miscibility of a drug with a polymer:
import cCOSMO
from cosmopharm import SLE, COSMOSAC
from cosmopharm.utils import create_components, read_params
# Define components - replace 'DrugName' and 'PolymerName' with your actual component names
names = ['DrugName', 'PolymerName']
params_file = "path/to/your/params.xlsx"
# Load parameters and create components
parameters = read_params(params_file)
components = create_components(names, parameters)
# Initialize COSMO-SAC model - replace paths with your local paths to COSMO profiles
db = cCOSMO.DelawareProfileDatabase(
"path/to/your/complist/complist.txt",
"path/to/your/profiles/")
for name in names:
iden = db.normalize_identifier(name)
db.add_profile(iden)
COSMO = cCOSMO.COSMO3(names, db)
# Setup the COSMO-SAC model with components
model = COSMOSAC(COSMO, components=components)
# Calculate solubility (SLE)
sle = SLE(solute=components[0], solvent=components[1], actmodel=model)
solubility = sle.solubility(mix='real')
# Output the solubility
print(solubility[['T', 'w', 'x']].to_string(index=False))
Replace 'DrugName', 'PolymerName', and file paths with your actual data and files. This example provides a straightforward demonstration of calculating the real solubility of a drug in a polymer using COSMOPharm.
Contributing
Contributions are welcome! Please refer to our GitHub repository for more information.
Citation
If you use COSMOPharm in your research, kindly cite our work. Citation details are available in CITATION.md.
License
COSMOPharm is released under the MIT License. For more details, see the LICENSE file.
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