# Source code for pkpd.protocols.protocol_pkpd_two_compartments_conv

```
# **************************************************************************
# *
# * Authors: Carlos Oscar Sorzano (info@kinestat.com)
# *
# * Kinestat Pharma
# *
# * This program is free software; you can redistribute it and/or modify
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# **************************************************************************
import pyworkflow.protocol.params as params
from .protocol_pkpd_ode_base import ProtPKPDODEBase
from pkpd.models.pk_models import PK_Twocompartments
[docs]class ProtPKPDTwoCompartmentsConv(ProtPKPDODEBase):
""" Fit a two-compartmentx model to a set of measurements (any arbitrary dosing regimen is allowed)\n
The central compartment is referred to as C, while the peripheral compartment as Cp.
The differential equation is V dC/dt = -(Cl+Clp) * C + Clp * Cp + dD/dt, Vp dCp/dt = Clp * C - Clp * Cp\n
where C is the concentration of the central compartment, Cl the clearance, V and Vp the distribution volume of the central and peripheral compartment,
Clp is the distribution rate between the central and the peripheral compartments, and D the input dosing regime.
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.\n
The forward model is implemented by convolution instead of by numerical solution of the differential equation.\n
Protocol created by http://www.kinestatpharma.com\n"""
_label = 'pk two-compartments conv'
def __init__(self,**kwargs):
ProtPKPDODEBase.__init__(self,**kwargs)
[docs] def forwardModel(self, parameters, x=None):
return self.forwardModelByConvolution(parameters, x)
#--------------------------- DEFINE param functions --------------------------------------------
def _defineParams(self, form):
self._defineParams1(form, True, "t", "Cp")
form.addParam('bounds', params.StringParam, label="Parameter bounds ([tlag], sourceParameters, Cl, V, Clp, Vp)", default="",
help="Bounds for time delay, central clearance and volume and peripheral clearance and volume. "\
'Make sure that the bounds are expressed in the expected units (estimated from the sample itself).'\
'Be careful that Cl bounds must be given here. If you have an estimate of the elimination rate, this is Ke=Cl/V. Consequently, Cl=Ke*V ')
form.addParam('tFImpulse', params.StringParam, label="Maximum length of the impulse response [min]", default="",
help="This is the time length for which the impulse response will be simulated. Leave empty if it must be taken from the input signal.")
```