Source code for pkpd.protocols.protocol_pkpd_estimate_bioavailability

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# * Authors:     Carlos Oscar Sorzano (
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# * Kinestat Pharma
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import numpy as np

import pyworkflow.protocol.params as params
from .protocol_pkpd import ProtPKPD
from pkpd.pkpd_units import PKPDUnit


[docs]class ProtPKPDNCAEstimateBioavailability(ProtPKPD): """ Estimate bioavailability as F=(AUCpo/Dpo) / (AUCiv/Div) [Gabrielsson 2010, p. 546], i.e., the ratio \n between the oral and intravenous AUC normalized by their respective doses. Protocol created by\n""" _label = 'bioavailability nca' #--------------------------- DEFINE param functions -------------------------------------------- def _defineParams(self, form): form.addSection('Input') form.addParam('protNCAEV', params.PointerParam, label="Extra-vascular NCA", pointerClass='ProtPKPDNCAEV', help='Non-compartmental analysis of the Extra-Vascular route, the dose must be a bolus\n' 'The sample names in both (EV and IV) analysis must be exactly the same.') form.addParam('protNCAIV', params.PointerParam, label="IV NCA", pointerClass='ProtPKPDNCAIVExp,ProtPKPDNCAIVObs', help='Non-compartmental analysis of the Extra-Vascular route, the dose must be a bolus\n' 'The sample names in both (EV and IV) analysis must be exactly the same.') #--------------------------- STEPS functions -------------------------------------------- def _insertAllSteps(self): self._insertFunctionStep('runEstimateF') self._insertFunctionStep('createOutput')
[docs] def runEstimateF(self): self.experimentEV=self.readExperiment(self.protNCAEV.get().outputExperiment.fnPKPD) self.experimentIV=self.readExperiment(self.protNCAIV.get().outputExperiment.fnPKPD) Flist = [] for sampleEVname, sampleEV in self.experimentEV.samples.items(): if sampleEVname in self.experimentIV.samples: sampleEV.interpretDose() DEV=sampleEV.getDoseAt(0) sampleIV=self.experimentIV.samples[sampleEVname] sampleIV.interpretDose() DIV=sampleIV.getDoseAt(0) AUCev=sampleEV.descriptors['AUC_0inf'] AUCiv=sampleIV.descriptors['AUC_0inf'] if AUCev!="NA" and AUCiv!="NA": F=(float(AUCev)/DEV)/(float(AUCiv)/DIV) Flist.append(F) self.experimentEV.addParameterToSample(sampleEV.sampleName,"bioavailability",PKPDUnit.UNIT_NONE, "bioavailability",F) else: self.experimentEV.addParameterToSample(sampleEV.sampleName,"bioavailability",PKPDUnit.UNIT_NONE, "bioavailability","NA") else: self.experimentEV.addParameterToSample(sampleEV.sampleName,"bioavailability",PKPDUnit.UNIT_NONE, "bioavailability","NA") self.experimentEV.write(self._getPath("experiment.pkpd")) fhSummary=open(self._getPath("summary.txt"),"w") if len(Flist)>0: Fmean = np.mean(Flist) fhSummary.write("Average bioavailability (normalized between 0 and 1)=%f\n"%Fmean) if Fmean>1: fhSummary.write("Bioavailability larger than 1 is caused by PK non-linearities and dependences of AUC on the dose\n") fhSummary.close()
[docs] def createOutput(self): self._defineOutputs(outputExperiment=self.experimentEV) self._defineSourceRelation(self.protNCAEV, self.experimentEV) self._defineSourceRelation(self.protNCAIV, self.experimentEV)
#--------------------------- INFO functions -------------------------------------------- def _summary(self): msg=[] self.addFileContentToMessage(msg,self._getPath("summary.txt")) return msg def _citations(self): return ['Gabrielsson2010']