Dose-effect analysis parameters

The majority of experimental mixture studies have analyzed the effects that arise from simultaneous exposure to chemicals. Very few studies exist where sequential exposure to several chemicals was analyzed. Only a concept founded on an understanding of the relationship between dose or concentration and exposure duration, time to effect, and recovery can hope to deal with the effect of sequential exposures. Conceptual frameworks for descriptions of time-dependent toxicity from a mechanistic perspective are available (e.g., Rozman and Doull 2000 Ashauer et al. 2006). However, the link between existing dose-time response models and a framework for mixture effect analysis from sequential exposure has yet to be made. A recent example of an interesting study that looked at sequential exposures is from Ashauer et al. (2007b), who base their analysis on a 1-compartment model for substance uptake, plus additional parameters for effect propagation and recovery. Generalizations are not yet in sight. 

Due to the superposition of various other biological, physiological and physical parameters used in modelling, the published exposure-dose conversion factors range from 2 to 120 mGy per WLM. However, a sensitivity analysis indicated that for most indoor exposure situations compensatory effects can reduce this range to about 5 to 10 mGy/WLM for the indoor situations occurring most frequently (OECD/NEA, 1983). 

While changes in cell phenotypes have proved useful in some settings to characterize the immunotoxicity of xenobiotics,1 phenotypic analysis alone is often not a sensitive indicator of low dose immunotoxicity for many agents that alter immune function. Xenobiotics that exert selective toxicity on lymphoid and myeloid cells may be discovered through immunophenotypic analysis. However, most agents produce immunotoxicity at doses much lower than those required to produce cytotoxicity or interfere with primary lymphoid organ differentiation. Some of the most potent immunosuppressive chemicals that have been tested, such as cyclosporine A, do not alter immunophenotype at doses that are immunosuppressive. On the other hand, when phenotyping is linked to assessment of functional parameters of the cells, immunotoxic effects are more likely to be identified. 

PK models (Section 13.2.4), PD models (Section 13.2.5), and PK/PD models (Section 13.2.6) can be used in two different ways, that is, in simulations (Section 13.2.7) and in data analysis (Section 13.2.8). Simulations can be performed if the model structure and its underlying parameter values are known. In fact, for any arbitrary dose or dosing schedule the drug concentration profile in each part of the model can be calculated. The quantitative measures of the effectiveness of drug targeting (Section 13.4) can also be evaluated. If actual measurements have been performed in in-vivo experiments in laboratory animals or man, the relevant model structure and its parameter values can be assessed by analysis of plasma disappearance curves, excretion rate profiles, tissue concentration data, and so forth (Section 13.2.8). 

They suggested the effect parameter the Critical Effect Dose (CED, a benchmark dose. Section 4.2.5) derived from the dose-response data by regression analysis. This CED was defined as the dose at which the average animal shows the Critical Effect Size (CES) for a particular toxicological endpoint, below which there is no reason for concern. The distribution of the CED can probabilistically be combined with probabilistic distributions of assessment factors for deriving standards... 

Response or effect surface analysis (RSA) uses multiple linear regressions to produce a statistically based mathematical relationship between the doses of each of the chemicals in a mixmre and the effect parameter. The equation for a mixmre containing three compounds would be... 

Fig. 1.5 Illustration of the simulation and analysis of a virtual trial outcome. The solid line represent the true dose-response relationship based on a sampled set of parameters from the joint posterior distribution of the model parameters. The circles represent the simulated drug effects in the patients included in the trial on the basis of the true" model parameters and the errors bars...

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