Toxicodynamic modeling

Blaauboer BJ (2003) Biokinetic and toxicodynamic modelling and its role in toxicological research and risk assessment. Altern Lab Anim 31(3) 277-281... 

Toxicodynamic Modeling of Noncancer Effects of Chemical Mixtures... 

Toxicodynamic Modeling of Cancer-Related Effects of Chemicals and a Binary Chemical Mixture... 

Hack CE. 2006. Bayesian analysis of physiologically based toxicokinetic and toxicodynamic models. Toxicology 221 241-248. 

Jonsson F, Johanson G. 2003. The Bayesian population approach to physiological toxicoki-netic-toxicodynamic models—an example using the MCSim software. Toxicol Lett 138 143-150. 

Integration of Physiologically Based Biokinetic and Toxicodynamic Modelling... 

One can differentiate between three types of transformation products of environmental pollutants. First, environmental pollutants can be metabolized during the toxicokinetic phase of uptake/metabolism/distribution/elimination in organisms (Table 1). Here, the observed effect is actually due to the combined effect of different metabolites. Taking these transformation reactions into account will help to understand mechanisms of toxicity, species sensitivity differences, and time dependency of effects. Lee and Landrum [8,9] developed a model to describe the mixture effects of PAH and their metabolites in Hyalella azteca. This combined toxicokinetic/toxicodynamic models convincingly demonstrated the importance of accounting for metabolite formation and how different mixture toxicity concepts can be incorporated into such models. 

Pery ARR, Brochot C, Zeman FA, Mombelli E, Desmots S, Pavan M, Fioravanzo E, Zaldfvar JM. 2013. Prediction of dose-hepatotoxic response in humans based on toxicokinetic/ toxicodynamic modeling with or without in vivo data A case study with acetaminophen. Toxicol Lett 220 26-34. 

A very important issue - disregard of which is a big source of bad modeling studies - is the dear distinction of transport processes (toxicokinetics) and interactions with targets such as membranes, enzymes, or DNA (toxicodynamics). Figure 10.1-6 gives a rather simplified model of a fish to illustrate this distinction. 

In their analyses, statistics on the relevant extrapolation factor from animals to humans, as reported in the literature, were considered synoptically, and distinctions were made between (1) publications which focused on allometrically justifiable differences (2) publications which examined the toxicodynamic or toxicokinetic variability and (3) pubhcations which considered the total (gross) interspecies factor. In addition, consideration of PBPK models was discussed as a possible alternative. 

If sufficient data are available, substance-specific PBPK models should always be given preference over the use of general scaling factors. However, PBPK models were considered not to replace all of the sub-factors in the interspecies comparison and should, by definition, only include toxicokinetic differences. A further extrapolation factor for toxicodynamic differences between the species needs to be discussed. 

PBTK models can potentially be extended to include the toxicodynamic phase (PBTK/TD model) if a direct relationship exists between the concentration of the active metabolite (or parent compound) and the toxic effect (Yang et al. 1995). 

As an example, Hsieh et al. identified toxicodynamic biomarkers in monkey semm that demonstrated a quantitative relationship with drug exposure (Cr iax, AUC) and related pathological events [148], The biomarkers were used for a more precise calculation of the no observed adverse effect level (NOAEL). The safety of three different dosing schedules was predicted using pharmacokinetic pharmacodynamic (PKPD) modeling and biomarker analysis. 

Absorption, Distribution, Metabolism, and Excretion. There is an obvious data need to determine the pharmacokinetic and toxicokinetic behavior of HDl in both humans and laboratory animals. Determination of blood levels of inhaled, ingested and dermally absorbed HDl would be difficult, given the very short half-life in biological matrices (Berode et al. 1991) and the rate at which HDl binds to proteins in the blood. Although some information is known about the metabolism of HDl in humans inhaling a known quantity of HDl (Brorson et al. 1990), the rate at which absorption occurs, where the majority of the metabolism of HDl occurs (in the water in the mucous layer of the bronchi as opposed to the blood or the kidney), and the distribution patterns and toxic effects of the metabolite (if any) are not well described. Information in these areas of toxicokinetics and toxicodynamics could also be useful in developing a PBPK/PD model for HDl. Research should focus on the respiratory and dermal routes of exposure. 

In the mechanistic models used to predict toxic effects of time-variable exposure to organisms, a distinction can be made between 1-step models and 2-step models (Ashauer et al. 2006). One-step models only consider toxicokinetics, whereas 2-step models consider both toxicokinetics and toxicodynamics. One-step models try to describe the uptake and elimination of a given compound in an organism and relate the calculated internal concentration to the effect occurring. Usually, an average total body residue is calculated, assuming that the concentration at the actual site(s) of action will be linearly related to the total body concentration. In specific cases, it may be necessary to calculate the concentration at the site of action through the use of more refined multicompartment (PBPK) models. 

In the mechanistic models used to predict effects of time-variable exposure to organisms, a distinction can be made between 1) l-step models that consider the toxicokinetic terms uptake, elimination, and critical body residues and 2) 2-step models that besides toxicokinetics also address the toxicodynamic terms injury and repair. A disadvantage of these models is that their parameterization is compound-and species-specific and hence requires many experimental data (Section 6.2.3). 

Physiologically based pharmacokinetic (PBPK) modelling sometimes constitutes a basis for replacement of default components of uncertainty for toxicokinetics and a portion of toxicodynamics. Where data are sufficient, a full biologically based dose-response model addresses additional uncertainties with respect to both interspecies differences and interindividual variability in both kinetics and dynamics. 

When measured internal concentrations are lacking, but a time series of effect data is available, then a 1-compartment model may still be useful to describe and analyze the toxicokinetic behavior of a substance. The effects pattern in time provides information on the toxicokinetics as well as toxicodynamics. Jager and Kooijman (2009) demonstrate that the relevant TK parameter can generally be derived from survival data with reasonable accuracy, and discuss how these scaled toxicokinetics relate to the whole body kinetics. 

Basic Pharmacodynamic, Toxicodynamic, and Dynamic Energy Budget Models... 

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