Overview

IndusChemFate Lite is a streamlined version of the original IndusChemFate Physiologically Based ToxicoKinetic (PBTK) model. This model estimates blood, urine and tissue concentrations of chemicals and their primary metabolites based on different exposure scenarios.

Key Differences from the Original Model:

• Simplified Metabolism: Unlike the full version which supports metabolism in all organs and up to 4 metabolites, this simplified version only considers metabolism in the liver and only from parent compound to first metabolite.
• Reduced Complexity: The model focuses on the core elements of toxicokinetics while reducing parameter requirements.
• Easier to Use: With fewer required parameters, this version is more accessible for initial assessments and screening.

Credit to Original Developers

This model is a direct translation from Visual Basic to R of the IndusChemFate model originally developed by Frans Jongeneelen & Wil ten Berge at IndusTox Consult (Netherlands) for CEFIC-LRI. The original model was published in 2011. Full credit goes to these researchers for their groundbreaking work in developing an open-source, multi-compartment PBTK model.

Original Model References:

• Jongeneelen, F.J. & Ten Berge, W.F. (2011). A Generic, Cross-Chemical Predictive PBTK Model with Multiple Entry Routes Running as Application in MS Excel; Design of the Model and Comparison of Predictions with Experimental Results. Annals of Occupational Hygiene, 55(8): 841-864.
• Jongeneelen, F.J. & Ten Berge, W.F. (2011). Simulation of urinary excretion of 1-hydroxypyrene in various scenarios of exposure to PAH with a generic, cross-chemical predictive PBTK-model. International Archives of Occupational and Environmental Health, 86(1): 99-107.

Example

A csv file is provided at the following Github Repo in the folder named Jaqpot_examples, as example on how to provide the input of the model.

Model Structure

The model includes 11 body compartments:

• Adipose tissue
• Bone
• Brain
• Heart
• Kidney
• Intestine (combined stomach & intestines)
• Liver
• Lung
• Muscle
• Skin
• Bone marrow

Each compartment is modeled with a mass-balance ordinary differential equation that describes the change in chemical concentration over time.

Exposure Scenarios

The model can simulate exposures for 14 different standardized subjects:

Human Subjects

1. Normal man (in rest) - 70 kg
2. Obese man (in rest) - 80 kg
3. Normal man (light work) - 70 kg
4. Obese man (light work) - 80 kg
5. Normal woman (in rest) - 60 kg
6. Obese woman (in rest) - 70 kg
7. Normal woman (light work) - 60 kg
8. Obese woman (light work) - 70 kg
9. Normal child (in rest) - 16 kg
10. Obese child (in rest) - 20 kg
11. Normal child (playing) - 16 kg
12. Obese child (playing) - 20 kg

Experimental Animals

1. Mouse (experimental study) - 0.03 kg
2. Rat (experimental study) - 0.3 kg

Each scenario uses standardized physiological parameters (organ volumes, blood flows) appropriate for that subject. Activity level ("in rest" vs. "light work"/"playing") affects cardiac output, alveolar ventilation, and the relative distribution of blood flow to different organs.

Exposure Routes

The model simulates three possible routes of exposure:

1. Inhalation: Exposure to substances via breathing, with parameters for concentration and exposure duration. The model accounts for respiratory protection if used.

2. Dermal Absorption: Two mechanisms are modeled:

   • Direct skin contact: Absorption through direct deposition of liquid or solid chemicals on the skin
   • Vapor absorption: Absorption through skin from chemicals in the air

3. Oral Intake: Modeled as a bolus dose applied to the intestinal lumen and released to the intestinal tissue at a first-order rate.

Multiple exposure routes can be combined in the same simulation.

Elimination and Removal Mechanisms

The model accounts for several elimination pathways:

1. Metabolism: In this simplified version, metabolism occurs only in the liver and only transforms the parent compound into a single metabolite. The metabolism follows Michaelis-Menten kinetics with parameters Vmax (maximum velocity) and Km (Michaelis-Menten constant).

2. Urinary Excretion: Calculated based on glomerular filtration rate, with consideration of tubular resorption that depends on the hydrophobicity (Log Kow) of the compound.

3. Exhalation: Based on the concentration in alveolar air, which depends on blood concentration and the blood:air partition coefficient.

4. Enterohepatic Circulation: Optional recirculation of the compound between liver and intestines, which can extend the compound's half-life in the body.

Parameters Estimated with QSARs

Several key parameters are estimated using Quantitative Structure-Activity Relationships (QSARs) to minimize required input data:

1. Blood:Air Partition Coefficients: Estimated using a QSAR based on Henry's Law constant and octanol:air partition coefficient.

2. Tissue:Blood Partition Coefficients: Predicted using a QSAR based on octanol:water partition coefficient and the lipid content of tissues.

3. Skin Permeation Coefficients: Estimated from the molecular weight and octanol:water partition coefficient.

4. Renal Tubular Resorption: Estimated from the octanol:water partition coefficient using a sigmoid model.

This approach allows the model to run with minimal chemical-specific input data.

Differential Equations Concept

The model uses a system of ordinary differential equations (ODEs) to describe the change in chemical mass in each compartment over time. The general form for a compartment is:

dM_i/dt = Q_i * (C_art - C_i/R_i) - Metabolism + Production

Where:

• dM_i/dt: Rate of change of mass in compartment i
• Q_i: Blood flow to compartment i
• C_art: Arterial blood concentration
• C_i: Concentration in compartment i
• R_i: Partition coefficient between compartment i and blood
• Metabolism: Rate of metabolism in the compartment
• Production: Rate of production from metabolism of precursors

Special equations apply to the lung (accounting for inhalation/exhalation), kidney (accounting for urinary excretion), liver (accounting for metabolism and enterohepatic circulation), and skin (accounting for dermal absorption).

Parent Substance and Metabolites

The model tracks:

• Parent Substance (index 0): The original chemical to which exposure occurs
• First Metabolite (index 1): The product of parent substance metabolism

In the code and parameters, the numbering convention is consistent:

• Parameters ending with "_0" refer to the parent substance
• Parameters ending with "_1" refer to the first metabolite

For example:

• M_Liver_0 is the mass of parent substance in the liver
• M_Liver_1 is the mass of first metabolite in the liver
• Vmax_Liver_0 is the maximum rate of metabolism of parent substance in the liver
• Km_Liver_0 is the Michaelis-Menten constant for parent substance in the liver

Metabolism in the ODEs

In this simplified version, metabolism only occurs in the liver, converting the parent compound (index 0) to the first metabolite (index 1). The corresponding terms in the ODEs are:

For the parent compound in the liver:

- (Vmax_Liver_0 * VolCmpLiver * C_Liver_0)/(Km_Liver_0 + C_Liver_0)

For the first metabolite in the liver:

+ (Vmax_p_Liver_0 * VolCmpLiver * C_Liver_0)/(Km_Liver_0 + C_Liver_0)

Where:

• Vmax_Liver_0: Maximum rate of removal of parent compound
• Vmax_p_Liver_0: Maximum rate of production of first metabolite from parent compound
• Km_Liver_0: Michaelis-Menten constant
• C_Liver_0: Concentration of parent compound in liver
• VolCmpLiver: Volume of liver

This approach allows for different rates of removal and production, so not all metabolized parent compound necessarily becomes the tracked metabolite.

Required User Input

To run the model, users need to provide:

Chemical Properties for Parent Compound:

• Molecular weight (g/mol)
• Vapor pressure (Pascal)
• Water solubility (mg/L)
• Log Kow at pH 7.4 (blood pH)
• Log Kow at pH 5.5 (skin pH)
• Density (mg/cm³)

Chemical Properties for First Metabolite:

• Molecular weight (g/mol)
• Vapor pressure (Pascal)
• Water solubility (mg/L)
• Log Kow at pH 7.4 (blood pH)
• Density (mg/cm³)

Metabolism Parameters:

• Vmax_Liver_0: Maximum rate of removal of parent compound (μmol/kg/h)
• Vmax_p_Liver_0: Maximum rate of production of metabolite (μmol/kg/h)
• Km_Liver_0: Michaelis-Menten constant (μmol/L)

Exposure Conditions:

• Exposure scenario (select from 14 options)
• Optional custom body weight (kg)
• Exposure route(s) and parameters:
  • Inhalation: concentration (mg/m³), start time (h), duration (h)
  • Dermal: deposition rate (mg/cm²/h), skin area (cm²), start time (h), duration (h)
  • Oral: dose (mg/kg), time of administration (h)

Optional Parameters:

• Respiratory protection factor
• Dermal protection factor
• Skin temperature (°C)
• Enterohepatic recirculation ratio

Simulation Outputs

The model provides time-course data for:

• Concentrations in each tissue compartment
• Concentrations in venous and arterial blood
• Concentrations in exhaled air
• Concentrations in urine
• Cumulative excreted amounts
• Mass balance information

These outputs allow for comparison with biomonitoring data and assessment of target tissue exposures.

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IndusChemFate Lite provides a streamlined yet powerful tool for understanding the distribution and fate of chemicals in the body. It is particularly valuable for initial screening and risk assessment when detailed metabolism data may not be available.