https://github.com/openscilab/drux
Drug Release Analysis Framework
https://github.com/openscilab/drux
drug-delivery drug-discovery drug-release kinetics simulation simulator
Last synced: 4 months ago
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Drug Release Analysis Framework
- Host: GitHub
- URL: https://github.com/openscilab/drux
- Owner: openscilab
- License: mit
- Created: 2025-03-22T13:21:03.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-09-19T22:02:32.000Z (4 months ago)
- Last Synced: 2025-09-20T00:48:03.234Z (4 months ago)
- Topics: drug-delivery, drug-discovery, drug-release, kinetics, simulation, simulator
- Language: Python
- Homepage:
- Size: 134 KB
- Stars: 13
- Watchers: 4
- Forks: 1
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
- Security: SECURITY.md
- Authors: AUTHORS.md
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README
Drux: Drug Release Analysis Framework
----------
## Overview
Drux is a Python-based framework for simulating drug release profiles using mathematical models. It offers a reproducible and extensible platform to model, analyze, and visualize time-dependent drug release behavior, making it ideal for pharmaceutical research and development. By combining simplicity with scientific rigor, Drux provides a robust foundation for quantitative analysis of drug delivery kinetics.
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## Installation
### PyPI
- Check [Python Packaging User Guide](https://packaging.python.org/installing/)
- Run `pip install drux==0.1`
### Source code
- Download [Version 0.1](https://github.com/openscilab/drux/archive/v0.1.zip) or [Latest Source](https://github.com/openscilab/drux/archive/dev.zip)
- Run `pip install .`
## Supported Models
### Higuchi
The Higuchi model describes the release of a drug from a matrix system, where the drug diffuses through a porous medium.
The Higuchi equation addressed important aspects of drug transport and release from planar
devices. According to this model, the cumulative amount of drug released at time $t$ is given by:
$$
M_t = \sqrt{D(2c_0 - c_s)c_st}
$$
where:
- $M_t (\frac{mg}{cm^2})$ is the cumulative absolute amount of drug released at time $t$
- $D ({\frac{cm^2}{s}})$ is the drug diffusivity in the polymer carrier
- $c_0 (\frac{mg}{cm^3})$ is the initial drug concentration (total concentration of drug in the matrix)
- $c_s (\frac{mg}{cm^3})$ is the solubility of the drug in the polymer (carrier)
⚠️ The Higuchi model assumes that $c_0 \ge c_s$
#### Applications
1. Matrix Tablets
2. Hydrophilic polymer matrices
3. Controlled - Release Microspheres
4. Semisolid Systems
5. Implantable Drug delivery systems
## Usage
### Higuchi Model
```python
from drux import HiguchiModel
model = HiguchiModel(D=1e-6, c0=1, cs=0.5)
model.simulate(duration=1000, time_step=10)
model.plot(show=True)
```
## Issues & bug reports
Just fill an issue and describe it. We'll check it ASAP! or send an email to [drux@openscilab.com](mailto:drux@openscilab.com "drux@openscilab.com").
- Please complete the issue template
## References
1- T. Higuchi, "Rate of release of medicaments from ointment bases containing drugs in suspension," Journal of Pharmaceutical Sciences, vol. 50, no. 10, pp. 874–875, 1961.
2- D. R. Paul, "Elaborations on the Higuchi model for drug delivery," International Journal of Pharmaceutics, vol. 418, no. 1, pp. 13–17, 2011.
3- R. T. Medarametla, K. V. Gopaiah, J. N. Suresh Kumar, G. Anand Babu, M. Shaggir, G. Raghavendra, D. Naveen Reddy, and B. Venkamma, "Drug Release Kinetics and Mathematical Models," International Journal of Science and Research Methodology, vol. 27, no. 9, pp. 12–19, Sep. 2024.
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