opendose_poppk.PKModel

class opendose_poppk.PKModel(F: float = 0.8, ka: float = 1.8, ke: float = 0.28, Vd: float = 65.0, Q: float = 10.0, V2: float = 20.0, CL: float | None = None, V: float | None = None, phys_half_life_h: float | None = None)

1-compartment pharmacokinetic model with first-order absorption.

Supports 2-compartment system with inter-compartmental flows and radioactive decay.

Parameters:

  • F (bioavailability (0–1))

  • ka (absorption rate constant (h⁻¹))

  • ke (elimination rate constant (h⁻¹))

  • Vd (volume of distribution (L))

  • Q (inter-compartmental flow (L/h))

  • V2 (peripheral compartment volume (L))

  • CL (systemic clearance (L/h) - alternative to ke)

  • V (central volume (L) - alternative to Vd)

  • phys_half_life_h (physical decay half-life (h) for radioactive isotopes)

__init__(F: float = 0.8, ka: float = 1.8, ke: float = 0.28, Vd: float = 65.0, Q: float = 10.0, V2: float = 20.0, CL: float | None = None, V: float | None = None, phys_half_life_h: float | None = None)

Initialize PKModel with classic parameters (F, ka, ke, Vd) or alternative parameters (CL, V). Supports radioactive decay.

Methods

__init__([F, ka, ke, Vd, Q, V2, CL, V, ...])

Initialize PKModel with classic parameters (F, ka, ke, Vd) or alternative parameters (CL, V).

auc([D])

AUC₀→∞ analítica para modelo linear: AUC = F·D / CL.

cmax([D])

Retorna (Cmax, Tmax) numéricos usando concentration.

concentration(t[, D])

Plasma concentration profile C(t) after extravascular-like dose input.

concentration_iv_bolus(t[, dose])

Concentration profile after an IV bolus in the central compartment.

concentration_iv_infusion(t, rate, duration_h)

Concentration profile for IV infusion with constant rate.

concentration_multiple_dose(t[, D, ...])

Concentração para regime de múltiplas doses em intervalos fixos.

concentration_nonlinear(t[, D, vmax, km])

Concentration profile with one-compartment Michaelis-Menten elimination.

simulate_population(t[, D, n_subjects, ...])

Simulação Monte Carlo de IIV sem covariáveis.

state_space()

Retorna as matrizes do sistema em espaço de estados.

steady_state_metrics([D, interval_h, ...])

Estimate steady-state metrics from repeated fixed-interval dosing.