pharmacokinetics


Namepharmacokinetics JSON
Version 0.1 PyPI version JSON
download
home_pagehttps://github.com/xyzpw/pharmacokinetics-module/
SummaryPython tools for pharmacokinetic calculations.
upload_time2024-07-16 15:36:27
maintainerNone
docs_urlNone
authorxyzpw
requires_pythonNone
licenseMIT
keywords pharmacokinetics pharmacodynamics pharmacology pharmacy chemistry
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # pharmacokinetics
![downloads](https://img.shields.io/pepy/dt/pharmacokinetics) ![repo-size](https://img.shields.io/github/repo-size/xyzpw/pharmacokinetics-module)

The **pharmacokinetics** package is a Python package designed to make pharmacokinetic formulas easier to calculate in your Python code.

## Usage
Some functions will use kwargs, which will allow the ability to use alternatives to values, e.g. the parameter `t12` can be used instead of `ke`, which will convert the elimination half-life to the elimination rate constant with the following formula:

$\Large{\frac{\ln2}{t^{1/2}}}$

> [!NOTE]
> Remember to make sure your units match!

### Calculating Concentrations
Calculating the concentration remaining after an elapsed time after peak concentration using the formula $C \cdot e^{-k_et}$:
```python
import pharmacokinetics as pk
pk.single_dose.calculateRemaining(initial_concentration=10, time_elapsed=4, t12=9)
```
The above code will calculate the remaining concentration of a drug that has reached peak concentration 4 hours ago with an elimination half-life of 9 hours.

The formula to this function:<br>
$10 \ mg \cdot e^{-\frac{\ln2}{9 \ h}4 \ h}=7.35 \ mg$

To calculate the concentration at any time $T$ (oral administration), the usage is:
```python
import pharmacokinetics as pk
pk.concentrationAtTime(
    dose=200,
    vd=0.7,
    bioavailability=0.99,
    t12=4.5,
    t12abs=7/60,
    elapsed=6
)
```
This above code follows the formula:

$\frac{F \cdot D \cdot k_a}{Vd(k_a - k_e)}(e^{-k_e \cdot t} - e^{-k_a \cdot t})$

Alternatively, `interval` can be used if the drug is taken at intervals, this will use the formula:

$\Large{\frac{F \cdot D \cdot k_a}{Vd(k_a - k_e)}(\frac{e^{-k_e \cdot t}}{1 - e^{-k_e \cdot \tau}} - \frac{e^{-k_a \cdot t}}{1 - e^{-k_a \cdot \tau}})}$

### Solving Values
Half-lives can be solved if the initial concentration, remaining concentration, and time elapsed are known:
```python
import pharmacokinetics as pk
pk.single_dose.halflifeFromDoses(
    dose=15,
    dose=9,
    elapsed=9
)
```
Where the time elapsed is the time past since the drug has reached maximum concentration and begins the elimination phase, which will then follow the formula $C = e^{-x \cdot 9 \ h}$ where $x$ is the elimination rate constant. Solving for $x$ becomes $\frac{\ln(\frac{9}{15})}{9} = -k_e$ to get half-life we use $\frac{\ln2}{|-k_e|} = 12.2 \ h$.

### Calculating Peak Time
If a drug's absorption and elimination constants are known, the tmax can be calculated:
```python
import pharmacokinetics as pk
pk.calculateTmax(t12=9, t12abs=0.75)
```
The formula to this calculation: $\frac{1}{k_a - k_e} \ln(\frac{ka}{ke}) = \frac{\ln(\frac{k_a}{k_e})}{k_a - k_e} = T_{max}$, which results in a tmax of 2.93 hours.

## Disclaimers
This package uses real formulas, but that does not mean it is free from errors, for example, bugs and typos can result in inaccurate info.<br>
If any bugs or inaccuracies are seen, open an issue so it can be fixed.

## Developers
If you intend to install the edited package, create a wheel file:
```bash
$ pip3 install setuptools # required to build package (skip if already installed)
$ python3 -m build # builds the package to a wheel file
```
To install this, I recommend creating a virtual environment:
```bash
$ python3 -m venv .venv # creates virtual environment
$ source .venv/bin/activate # activates the virtual environment
```
Now use pip install with the file that was just created.<br>
To deactivate the virtual environment:
```bash
$ deactivate
```
### Contributing
Contributions must not break the code or change formulas.<br>
Contributions that can possibly be accepted:
- fixed typos
- fixed bugs
- new formulas (source required)


            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/xyzpw/pharmacokinetics-module/",
    "name": "pharmacokinetics",
    "maintainer": null,
    "docs_url": null,
    "requires_python": null,
    "maintainer_email": null,
    "keywords": "pharmacokinetics, pharmacodynamics, pharmacology, pharmacy, chemistry",
    "author": "xyzpw",
    "author_email": null,
    "download_url": "https://files.pythonhosted.org/packages/c2/3f/346a474d78c55f3003990fb17351686db303c513cbeb59877c2e66ed4bca/pharmacokinetics-0.1.tar.gz",
    "platform": null,
    "description": "# pharmacokinetics\n![downloads](https://img.shields.io/pepy/dt/pharmacokinetics) ![repo-size](https://img.shields.io/github/repo-size/xyzpw/pharmacokinetics-module)\n\nThe **pharmacokinetics** package is a Python package designed to make pharmacokinetic formulas easier to calculate in your Python code.\n\n## Usage\nSome functions will use kwargs, which will allow the ability to use alternatives to values, e.g. the parameter `t12` can be used instead of `ke`, which will convert the elimination half-life to the elimination rate constant with the following formula:\n\n$\\Large{\\frac{\\ln2}{t^{1/2}}}$\n\n> [!NOTE]\n> Remember to make sure your units match!\n\n### Calculating Concentrations\nCalculating the concentration remaining after an elapsed time after peak concentration using the formula $C \\cdot e^{-k_et}$:\n```python\nimport pharmacokinetics as pk\npk.single_dose.calculateRemaining(initial_concentration=10, time_elapsed=4, t12=9)\n```\nThe above code will calculate the remaining concentration of a drug that has reached peak concentration 4 hours ago with an elimination half-life of 9 hours.\n\nThe formula to this function:<br>\n$10 \\ mg \\cdot e^{-\\frac{\\ln2}{9 \\ h}4 \\ h}=7.35 \\ mg$\n\nTo calculate the concentration at any time $T$ (oral administration), the usage is:\n```python\nimport pharmacokinetics as pk\npk.concentrationAtTime(\n    dose=200,\n    vd=0.7,\n    bioavailability=0.99,\n    t12=4.5,\n    t12abs=7/60,\n    elapsed=6\n)\n```\nThis above code follows the formula:\n\n$\\frac{F \\cdot D \\cdot k_a}{Vd(k_a - k_e)}(e^{-k_e \\cdot t} - e^{-k_a \\cdot t})$\n\nAlternatively, `interval` can be used if the drug is taken at intervals, this will use the formula:\n\n$\\Large{\\frac{F \\cdot D \\cdot k_a}{Vd(k_a - k_e)}(\\frac{e^{-k_e \\cdot t}}{1 - e^{-k_e \\cdot \\tau}} - \\frac{e^{-k_a \\cdot t}}{1 - e^{-k_a \\cdot \\tau}})}$\n\n### Solving Values\nHalf-lives can be solved if the initial concentration, remaining concentration, and time elapsed are known:\n```python\nimport pharmacokinetics as pk\npk.single_dose.halflifeFromDoses(\n    dose=15,\n    dose=9,\n    elapsed=9\n)\n```\nWhere the time elapsed is the time past since the drug has reached maximum concentration and begins the elimination phase, which will then follow the formula $C = e^{-x \\cdot 9 \\ h}$ where $x$ is the elimination rate constant. Solving for $x$ becomes $\\frac{\\ln(\\frac{9}{15})}{9} = -k_e$ to get half-life we use $\\frac{\\ln2}{|-k_e|} = 12.2 \\ h$.\n\n### Calculating Peak Time\nIf a drug's absorption and elimination constants are known, the tmax can be calculated:\n```python\nimport pharmacokinetics as pk\npk.calculateTmax(t12=9, t12abs=0.75)\n```\nThe formula to this calculation: $\\frac{1}{k_a - k_e} \\ln(\\frac{ka}{ke}) = \\frac{\\ln(\\frac{k_a}{k_e})}{k_a - k_e} = T_{max}$, which results in a tmax of 2.93 hours.\n\n## Disclaimers\nThis package uses real formulas, but that does not mean it is free from errors, for example, bugs and typos can result in inaccurate info.<br>\nIf any bugs or inaccuracies are seen, open an issue so it can be fixed.\n\n## Developers\nIf you intend to install the edited package, create a wheel file:\n```bash\n$ pip3 install setuptools # required to build package (skip if already installed)\n$ python3 -m build # builds the package to a wheel file\n```\nTo install this, I recommend creating a virtual environment:\n```bash\n$ python3 -m venv .venv # creates virtual environment\n$ source .venv/bin/activate # activates the virtual environment\n```\nNow use pip install with the file that was just created.<br>\nTo deactivate the virtual environment:\n```bash\n$ deactivate\n```\n### Contributing\nContributions must not break the code or change formulas.<br>\nContributions that can possibly be accepted:\n- fixed typos\n- fixed bugs\n- new formulas (source required)\n\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "Python tools for pharmacokinetic calculations.",
    "version": "0.1",
    "project_urls": {
        "Homepage": "https://github.com/xyzpw/pharmacokinetics-module/"
    },
    "split_keywords": [
        "pharmacokinetics",
        " pharmacodynamics",
        " pharmacology",
        " pharmacy",
        " chemistry"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "e041ccb0fa5982472b2512e1ef0fdbb26ddd08c376bf293e491b38283a4d9733",
                "md5": "ee732d51bdf2b909c6c55f2f09cbf371",
                "sha256": "da33a19379f9d11e6ce9ae43561f1fe6452dc57475f60bfee8ac77faddc03dee"
            },
            "downloads": -1,
            "filename": "pharmacokinetics-0.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "ee732d51bdf2b909c6c55f2f09cbf371",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 9309,
            "upload_time": "2024-07-16T15:36:21",
            "upload_time_iso_8601": "2024-07-16T15:36:21.187423Z",
            "url": "https://files.pythonhosted.org/packages/e0/41/ccb0fa5982472b2512e1ef0fdbb26ddd08c376bf293e491b38283a4d9733/pharmacokinetics-0.1-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "c23f346a474d78c55f3003990fb17351686db303c513cbeb59877c2e66ed4bca",
                "md5": "31a808c0350d80169107f6b09016715d",
                "sha256": "356c2e8391351afb719eeb56a8e034d3a6823e0d5c9b44b2f3eddc56512d42ef"
            },
            "downloads": -1,
            "filename": "pharmacokinetics-0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "31a808c0350d80169107f6b09016715d",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 7627,
            "upload_time": "2024-07-16T15:36:27",
            "upload_time_iso_8601": "2024-07-16T15:36:27.372034Z",
            "url": "https://files.pythonhosted.org/packages/c2/3f/346a474d78c55f3003990fb17351686db303c513cbeb59877c2e66ed4bca/pharmacokinetics-0.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-07-16 15:36:27",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "xyzpw",
    "github_project": "pharmacokinetics-module",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "pharmacokinetics"
}
        
Elapsed time: 0.42837s