# **************************************************************************
# *
# * Authors: Carlos Oscar Sorzano (info@kinestat.com)
# *
# * Kinestat Pharma
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# * 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_TwocompartmentsBoth
[docs]class ProtPKPDTwoCompartmentsBoth(ProtPKPDODEBase):
""" Fit a two-compartments model to a set of plasma and peripheral compartment measurements ((any arbitrary dosing regimen is allowed)\n
The differential equation is dC/dt = -Cl * C/V -Clp *(C-Cp)/V + 1/V * dD/dt, dCp/dt=Cl*C/Vp+Clp*(C-Cp)/Vp\n
where C is the concentration, Cl the total clearance (metabolic and excretion), V the distribution volume, Clp is the Clearance \n
to the peripheric compartment, Vp is the volume of the peripheric compartment, and D the input dosing regime.
This protocol assumes that you have measures of both the central and peripheral compartments.
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
Protocol created by http://www.kinestatpharma.com\n"""
_label = 'two-compartments both'
#--------------------------- DEFINE param functions --------------------------------------------
def _defineParams(self, form):
self._defineParams1(form)
form.addParam('predictor', params.StringParam, label="Time variable", default="t")
form.addParam('predicted', params.StringParam, label="Plasma concentration", default="Cp")
form.addParam('Cperipheral', params.StringParam, label="Peripheral concentration", default="Cper")
form.addParam('bounds', params.StringParam, label="Parameter bounds ([tlag], Cl, V, Clp, Vp)", default="",
help="Bounds for the tlag (if it must be estimated), clearance, and volume."\
'Make sure that the bounds are expressed in the expected units (estimated from the sample itself).'\
'If tlag must be estimated, its bounds must always be specified')
[docs] def getXYvars(self):
self.varNameX=self.predictor.get()
self.varNameY=[self.predicted.get(),self.Cperipheral.get()]
[docs] def createModel(self):
return PK_TwocompartmentsBoth()