pkpd.protocols.protocol_pkpd_two_compartments_metabolite module

class pkpd.protocols.protocol_pkpd_two_compartments_metabolite.ProtPKPDTwoCompartmentsClintMetabolite(**kwargs)[source]

Bases: pkpd.protocols.protocol_pkpd_ode_base.ProtPKPDODEBase

Fit a two-compartmentx model to a set of measurements (any arbitrary dosing regimen is allowed)

The central compartment is referred to as C, while the peripheral compartment as Cp. The differential equation is V dC/dt = -(Clint+Clp) * C + Clp * Cp + dD/dt, Vp dCp/dt = Clp * C - Clp * Cp, dCm/dt=Clint*C/Vm-Clm*Cm/Vm

and Clint=Vmax/(Km+C)

where C is the concentration of the central compartment, V, Vp, Vm the distribution volume of the central, peripheral and metabolite compartment, Clp is the distribution rate between the central and the peripheral compartments,

Clm is the clearance of metabolite at the metabolite compartments,

Vmax is the maximum processing capability of the metabolic pathway degrading the drug into the metabolite,

Km is the Michaelis-Menten constant,and D the input dosing regime.

Note that the intrinsic clearance occurs at the central volume.

Confidence intervals calculated by this fitting may be pessimistic because it assumes that all model parameters are independent, which are not. Use Bootstrap estimates instead.

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