Human monitoring analysis settings

Calculation settings

Table 155 Calculation settings for module Human monitoring analysis.
Name Type Description
Exposure type
ExposureType The type of exposure considered in the assessment; acute (short term) or chronic (long-term).
Multiple substances analysis

Boolean

Specifies whether the assessment involves multiple substances.
Compute cumulative exposures

Boolean

Specifies whether the assessment involves multiple substances and results should be cumulated over all substances.
Censored values handling method (also used as fallback for censored lognormal approach)
NonDetectsHandlingMethod Method for dealing with censored value samples in human monitoring data. Note that this method is also used as a fallback when fitting a censored lognormal model to the concentration data fails.
Fraction for censored value replacement

Numeric

Factor used for replacing the censored value.
Imputation method for non detect values
NonDetectImputationMethod Imputation method for non detect values: replace nondetects based on by f*LOD/LOQ) or from left tail censored lognormal distribution.
Missing value imputation method
MissingValueImputationMethod Imputation method for missing values: 1) By zero, 2) Impute from data, 3) No missing value imputation
Biological matrix
BiologicalMatrix The target biological matrix (internal compartment) for which exposures are computed.
Convert to single target

Boolean

Convert all substance concentrations from other biological matrices to the same target biological matrix. This conversion is applied when the number of substances measured on the target biological matrix is limited. Substances measured on other matrices can be converted using kinetic conversion models.
Between matrix concentration conversion factor

Numeric

Conversion factor to use when extrapolating concentrations of other biological matrices to concentrations of the selected target biological matrix.
Specify the minimum percentage of non-missing values (%)

Numeric

Specify the minimum percentage of non-missing values required for imputation. No imputation is done when the percentage of non-missing values in the data is smaller than the specified percentage.
Standardise blood concentrations for lipid-soluble substances

bool

Standardise blood concentrations for lipid-soluble substances: 1) Standardise by total lipid measured via gravimetric analysis, 2) Standardise by total lipid measured via enzymatic summation, 3) Standardise by derived total lipid content of Triglycerides/Cholesterol (Bernert et al. 2007).
Specify the standardisation method of blood concentrations for lipid-soluble substances
StandardiseBloodMethod Specify the standardisation method of blood concentrations for lipid-soluble substances.
Subset selection: exclude substances from lipid standardisation

bool

Select this option to exclude one or more lipid-soluble substances from standardisation.
Select substances to exclude from lipid standardisation

AlphaNumeric

The selected (lipid-soluble) substances will be excluded from lipid standardisation.
Normalise or standardise urine concentrations for specific gravity or creatinine

bool

Normalise or standardise urine concentrations for specific gravity or creatinine: 1) Normalise by specific gravity, 2) Standardise by creatinine concentration.
Specify the normalisation/standardisation method of urine concentrations for specific gravity or creatinine
StandardiseUrineMethod Specify the normalisation/standardisation method of urine concentrations for specific gravity or creatinine.
Subset selection: exclude substances from urine normalisation/standardisation

bool

Select this option to exclude one or more substances from normalization for specific gravity or creatinine standardisation.
Select the substances to exclude from urine normalisation/standardisation

AlphaNumeric

The selected substances will be excluded from urine normalization/standardisation.
Substance weighting for MCR
ExposureApproachType Risk based: exposures in equivalents of the reference substance; standardised: standardised exposures per substance have variance 1; or unweighted exposures: RPFs are equal to 1.
Perform MCR analysis

Boolean

Perform a Maximum Cumulative Ratio (MCR) analysis to determine co-exposure between substances.
Display ratio total exposure/ maximum (in MCR plot)

Numeric

For MCR plot: specify ratio total exposure/ maximum for individual(day) exposures .
Show tail percentiles (MCR plot) for:

AlphaNumeric

Give specific percentiles of exposure distribution (%), e.g. 97.5 99 (space separated).
Set minimum percentage contribution per substance to the tail exposure (MCR plot)

Numeric

Set minimum percentage contribution per substance to the tail exposure.
Kinetic conversion method
KineticConversionType Kinetic conversion method, default (factor = 1), simple conversion factors (dependent on substance, exposure route and expression type) or PBK models (not implemented yet).

Output settings

Table 156 Output settings for module Human monitoring analysis.
Name Type Description
Store simulated individual day exposures

Boolean

Store the simulated individual day exposures. If unchecked, no additional output will be generated. If checked, the output will contain an additional section with the simulated individual day exposures.