Pykinetics is a modern, responsive web application designed for comprehensive pharmacokinetic (PK) analysis. Built with Python (Flask) and a dynamic JavaScript frontend, it allows users to input concentration-time data and instantly receive detailed kinetic modeling, robust parameter calculations, and interactive visualizations.
Enter the administration route, number of compartments, drug dose, and concentration-time data points into the input form.
Input concentration-time data for your drug
Click Analyze Kinetics and instantly receive comprehensive pharmacokinetic parameters, kinetic order classification, compartmental model selection, and interactive plots.
Complete PK analysis with parameters, graphs, and model fitting
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Zero, First, Second, and Third Order Reactions: Automatically identifies the best-fit kinetic order using
$R^2$ linear regressions against concentration,$ln(C)$ ,$1/C$ , and$1/C^2$ . - Compartmental Analysis: Evaluates Akaike Information Criterion (AIC) to intelligently distinguish between 1-Compartment and 2-Compartment intravenous (IV) models.
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Bi-Exponential Fits: Calculates complex
$A$ ,$\alpha$ ,$B$ , and$\beta$ parameters alongside compartment rate constants ($K_{12}$ ,$K_{21}$ ,$K_{10}$ ) for 2-Compartment biphasic data.
- Distinct analytical routing for IV Bolus vs Oral administration.
- Explicit mapping for Absorption Rate Constant (
$K_a$ ) modeling utilizing the Method of Residuals. - Automated extraction of observed peak timing (
$T_{max}$ ) and peak concentration ($C_{max}$ ). - Extrapolates Apparent Volume of Distribution (
$V_d/F$ ) and Apparent Clearance ($Cl/F$ ).
- Provides dynamic GUI support to independently track up to 4 separate compartments simultaneously.
- Responsive, auto-scaling CSS grid data tables that effortlessly add or remove input columns based on the selected compartment count.
- Renders dual-panel, interactive scatter plots in both Linear (
$C$ vs$t$ ) and Logarithmic ($ln(C)$ vs$t$ ) scales. - Dynamically overlays sophisticated regression curves (Zero order, First order, bi-exponential sweeps, and Oral absorption phase shapes) matching the analyzed data.
- Plots multi-trace series automatically for explicit multi-compartment inputs, color-coded for clarity.
- Beautifully stylized interface leveraging "Glassmorphism", glowing neon badges, and fluid layout scaling.
- Fully responsive across Desktop and Mobile form factors.
- Displays analysis output in pristine, easily readable property cards.
- Clone the repository:
git clone https://github.com/heyiamnotacoder/pykinetics.git
cd pykinetics- Set up a Virtual Environment (Recommended):
python3 -m venv venv
source venv/bin/activate- Install Dependencies:
pip install -r requirements.txt- Launch the Application:
python app.pyThe app will be available locally at http://127.0.0.1:5001.
- Backend: Python 3, Flask, NumPy, SciPy (for optimized curve fitting & regression engines).
- Frontend: HTML5, CSS3 Grid/Flexbox alignments, Vanilla JavaScript, Chart.js.
Created as an advanced pharmacological modeling tool.