Michaelis-Menten Elimination Model
One-compartment model with saturable (nonlinear) elimination kinetics.
Model Schematic
IV Bolus
│
▼
┌─────────────┐
│ Central │
│ V │──── Vmax/(Km + C) ────▶ Saturable Elimination
└─────────────┘
Differential Equation
dA_central/dt = -Vmax × A_central / (Km × V + A_central)
Or in terms of concentration:
dC/dt = -Vmax × C / (Km + C) / V
Parameters
| Parameter |
Description |
Typical Range |
Units |
| Vmax |
Maximum elimination rate |
10-1000 |
mg/h |
| Km |
Michaelis constant |
1-100 |
mg/L |
| V |
Volume of distribution |
10-500 |
L |
Example Values
| Parameter |
Value |
Rationale |
| Vmax |
50.0 mg/h |
Maximum enzyme capacity |
| Km |
10.0 mg/L |
Half-saturation concentration |
| V |
50.0 L |
Total body water |
| Dose |
500 mg |
High dose to show saturation |
Key Features
- At low C (C << Km): First-order kinetics, CL ≈ Vmax/Km
- At high C (C >> Km): Zero-order kinetics, rate ≈ Vmax
- Nonlinear PK: AUC not proportional to dose
- Examples: phenytoin, ethanol, aspirin (high dose)
Derived Parameters
| Parameter |
Formula |
Description |
| CLint |
Vmax/Km |
Intrinsic clearance (at low C) |
| t½ (low C) |
0.693 × V × Km / Vmax |
Half-life at low concentrations |
Use Cases
- Drugs with capacity-limited metabolism
- High-dose regimens
- Therapeutic drug monitoring
- Phenytoin dosing optimization
Clinical Implications
- Dose escalation: Small dose increases can cause large concentration changes
- Steady-state: Takes longer to reach at higher doses
- Drug interactions: Enzyme inhibitors have greater effect when near saturation
Files
| File |
Description |
julia.jl |
Julia implementation |
python.py |
Python implementation |
cli.json |
CLI specification |