In this stage, an advanced evaluation is carried out. It applies to cases where there are comprehensive data available. The fundamental approach is that the model parameter values are adjusted systematically, in a specific order, until the goodness of fit is acceptable (i.e. the fits obtained to all the data are not rejected by the specified criteria). If the fit is acceptable then the estimated intake is taken as the best estimate and the effective dose is calculated with the same model parameter values that were assumed in the assessment of intake. These results (intake and committed effective dose) are then recorded together with the corresponding parameter values (Step 5.15.1). Thus after each Step in which a parameter value is varied (5.17 to 5.22) there is a corresponding Step (5.17.1 to 5.22.1 respectively) to test the goodness of fit. Since these are all very similar to Step 5.15, explanatory text is not given. It is recommended, in cases where multiple types of bioassay data sets are available, that the intake and dose are assessed by fitting predicted values to the different types of data simultaneously.


Step 5.15: Is the goodness of fit acceptable? If the goodness of fit is acceptable (i.e. the fit obtained is not rejected by the specified criteria, Section 4.2.6) then the estimated intake is taken as the best estimate. The effective dose is then calculated with the same model parameter values that were assumed in the assessment of intake. However if the fit is rejected then proceed to next (step 5.16).


Step 5.16: Determine specific HRTM absorption parameter values: For materials that are moderately to very insoluble (typically absorption Types M or S), determine specific values for fr and ss by fitting fr, ss and intake to the data with sr fixed at 100 d-1. For most materials there is no evidence for binding to the respiratory tract so the bound fraction fb is taken to be zero. However, if relevant values of sr and/or of fb and sb have been determined from in vivo experimental data then use these values.


Step 5.17: Determine specific f1 value: Generally, it is not justifiable to change the f1 value as well as the HRTM absorption parameter values. Occasionally, for inhaled materials that are relatively insoluble, it is necessary to reduce the value of f1 so that the predicted systemic activities or urinary excretion rates are consistent with the data.


Step 5.18 : Determine specific HRTM particle transport values: The parameter values that describe particle transport from the respiratory tract in the HRTM were based so far as possible on human experimental data, which enable typical lung clearance rates to be determined for a year or so after particle deposition in the lungs. However, the values were chosen to be average values for healthy non-smokers. The experimental data from which they were derived show considerable inter-subject variation even among healthy subjects, and indicate that clearance would generally be slower in smokers and patients with lung disease (ICRP Publication 66, 1994). If there are comprehensive lung and/or faecal excretion data available, it may be necessary to vary particle transport rates to improve the fits to the data.


It should be noted that adjusting particle transport rates also effects the amount absorbed into blood, because clearance from the lung is competitive between absorption into blood and particle transport to the GI tract. Thus in some cases it is necessary to readjust HRTM absorption parameter values (i.e. repeat step 5.16) after varying the particle transport rates.


Step 5.19: Determine specific GI model transit parameter values: The parameter values in the ICRP GI tract model again represent typical values, and there will be considerable inter (and intra-) subject variations. The transit time through the GI tract affects the amount in the whole body and the amount excreted in the faeces within the first few days following inhalation or ingestion. If there are comprehensive early data it may be necessary to alter the GI tract model parameter values to obtain a reasonable fit to the data.


Step 5.20: Adjust systemic biokinetic model parameter values: Again, model parameters values were derived by ICRP to represent population averages, and there are likely to be individual variations, which will result in differences between predicted values and data, independently of the biokinetics of the respiratory or GI tract. This might well arise for very soluble materials, where particle transport rates have little effect. Individual whole body retention half-times have been reported for intakes of tritiated water and caesium-137. However, for actinides, with sufficiently comprehensive data, individual differences from model predictions might be observed for retention in liver and skeleton, or in the ratio between deposition in such organs, and urinary excretion.


It is emphasised that this is the last step, so adjusting the systemic biokinetic model parameter values should only be considered after varying the HRTM and GI tract model parameter values, and f1 value (Steps 5.18, 5.19 and 5.20). If the goodness of fit test results in the fit being rejected according to the specified criteria then send the case to the IDEAS website. Otherwise the results (intake and committed effective dose) are then recorded together with the corresponding parameter values (Step 5.15.1).







































Prof. Dr.-Ing. Hans Richard Doerfel

IDEA System GmbH, Am Burgweg 4, D-76227 Karlsruhe, Germany.