# **************************************************************************
# *
# * Authors: Carlos Oscar Sorzano (info@kinestat.com)
# *
# * Kinestat Pharma
# *
# * This program is free software; you can redistribute it and/or modify
# * it under the terms of the GNU General Public License as published by
# * the Free Software Foundation; either version 2 of the License, or
# * (at your option) any later version.
# *
# * This program is distributed in the hope that it will be useful,
# * but WITHOUT ANY WARRANTY; without even the implied warranty of
# * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# * GNU General Public License for more details.
# *
# * You should have received a copy of the GNU General Public License
# * along with this program; if not, write to the Free Software
# * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA
# * 02111-1307 USA
# *
# * All comments concerning this program package may be sent to the
# * e-mail address 'info@kinestat.com'
# *
# **************************************************************************
import pyworkflow.protocol.params as params
from .protocol_pkpd_fit_base import ProtPKPDFitBase
from pkpd.models.pk_models import PKPDSimpleEVModel
from pkpd.pkpd_units import strUnit
from pyworkflow.protocol.constants import LEVEL_ADVANCED
from pyworkflow.object import Integer
import math
import numpy as np
# TESTED in test_workflow_gabrielsson_pk02.py
# TESTED in test_workflow_gabrielsson_pk06.py
[docs]class ProtPKPDAbsorptionRate(ProtPKPDFitBase):
""" Estimation of the absorption rate for a non-intravenous route. The estimation is performed after estimating
the elimination rate. The experiment is determined by the\n
Protocol created by http://www.kinestatpharma.com\n.
See the theory at http://www.pharmpress.com/files/docs/Basic%20Pharmacokinetics%20sample.pdf"""
_label = 'absorption rate'
#--------------------------- DEFINE param functions --------------------------------------------
def _defineParams(self, form):
form.addSection('Input')
form.addParam('inputExperiment', params.PointerParam, label="Input experiment",
pointerClass='PKPDExperiment',
help='Select an experiment with samples')
form.addParam('protElimination', params.PointerParam, label="Elimination rate",
pointerClass='ProtPKPDEliminationRate',
help='Select an execution of a protocol estimating the elimination rate')
form.addParam("absorptionF", params.FloatParam, label="Absorption fraction", default=1,
help="Between 0 (=no absorption) and 1 (=full absorption)")
form.addParam('bounds', params.StringParam, label="Ka, V, [tlag] bounds", default="", expertLevel=LEVEL_ADVANCED,
help='Bounds for Ka (absorption constant), V (distribution volume) and optionally tlag.\nExample 1: (0,1e-3);(30,50);(0.1,0.5) -> Ka in (0,1e-3), V in (30,50) and tlag in (0.1,0.5)\n')
form.addParam('confidenceInterval', params.FloatParam, label="Confidence interval", default=95, expertLevel=LEVEL_ADVANCED,
help='Confidence interval for the fitted parameters')
form.addParam('includeTlag', params.BooleanParam, label="Include tlag", default=True, expertLevel=LEVEL_ADVANCED,
help='Calculate the delay between administration and absorption')
self.fitType=Integer() # Logarithmic fit
self.fitType.set(1)
#--------------------------- STEPS functions --------------------------------------------
[docs] def getXYvars(self):
self.varNameX = self.protElimination.get().predictor.get()
self.varNameY = self.protElimination.get().predicted.get()
[docs] def createModel(self):
return PKPDSimpleEVModel(self.includeTlag.get())
[docs] def prepareForSampleAnalysis(self, sampleName):
sample = self.experiment.samples[sampleName]
sampleFit = self.eliminationFitting.getSampleFit(sampleName)
sample.interpretDose()
self.model.D = sample.getDoseAt(0.0)
self.model.Dunits = sample.getDoseUnits()
if sampleFit == None:
print(" Cannot process %s because its elimination rate cannot be found\n\n"%sampleName)
return False
self.model.C0 = sampleFit.parameters[0]
self.model.C0units = self.eliminationFitting.modelParameterUnits[0]
self.model.Ke = sampleFit.parameters[1]
self.model.KeUnits = self.eliminationFitting.modelParameterUnits[1]
print("Concentration at t=0 = %f [%s]"%(self.model.C0,strUnit(self.model.C0units)))
print("Elimination rate = %f [%s]"%(self.model.Ke,strUnit(self.model.KeUnits)))
self.experiment.addParameterToSample(sampleName, "Ke", self.model.KeUnits, "Automatically estimated elimination rate", self.model.Ke)
return True
[docs] def postSampleAnalysis(self, sampleName):
xunits = self.experiment.getVarUnits(self.varNameX)
Cunits = self.experiment.getVarUnits(self.varNameY)
Ka = self.model.parameters[0]
Ke = self.model.Ke
tmax = math.log(Ka/Ke)/(Ka-Ke)
self.experiment.addParameterToSample(sampleName, "tmax", xunits, "Estimated time of the Maximum of the non-iv peak", tmax)
Cmax = self.model.forwardModel(self.model.parameters,x=[np.atleast_1d(np.array(tmax))])[0][0]
self.experiment.addParameterToSample(sampleName, "Cmax", Cunits, "Estimated concentration of the Maximum of the non-iv peak", Cmax)
print("tmax = %f [%s]"%(tmax,strUnit(xunits)))
print("Cmax = %f [%s]"%(Cmax,strUnit(Cunits)))
#--------------------------- INFO functions --------------------------------------------
def _summary(self):
msg=[]
msg.append("Non-compartmental analysis for the observations of the variable %s"%self.protElimination.get().predicted.get())
return msg
def _warnings(self):
msg = []
experiment = self.readExperiment(self.getInputExperiment().fnPKPD,show=False)
incorrectList = experiment.getNonBolusDoses()
if len(incorrectList)!=0:
msg.append("This protocol is meant only for bolus regimens. Check the doses for %s"%(','.join(incorrectList)))
return msg