From in vitro hepatic metabolic studies towards human health risk assessment: Two case studies of diuron and carbosulfan

Pesticide Biochemistry and Physiology 107 (2013) 258–265

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From in vitro hepatic metabolic studies towards human health risk assessment: Two case studies of diuron and carbosulfan Khaled M. Abass ⇑,1 Centre For Arctic Medicine, Thule Institute, University of Oulu, Finland Pharmacology and Toxicology Unit, Institute of Biomedicine, University of Oulu, Finland

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Article history: Received 22 April 2013 Accepted 27 August 2013 Available online 4 September 2013 Dedicated to Professor Olavi Pelkonen, the former head of the Pharmacology and Toxicology department, on the occasion of his retirement Keywords: Risk assessment In vitro metabolism In vivo extrapolation Pesticides Toxicokinetics

a b s t r a c t Risk assessment of environmental pollutants is an absolutely essential tool in the overall process of protecting public health. Risk assessment needs reliable scientific information and one source of information is the characterization of metabolic fate and toxicokinetics of environmental pollutants. The aim of in vitro characterization is to produce relevant information on metabolism and interactions to anticipate and ultimately predict what happens in vivo in humans. Because human data is most appropriate to improve human risk assessment, the best option is to rely upon human-derived in vitro models and obtain quantitative toxicokinetics data from in vitro systems for the comparison between species or individuals. In short, based on our studies of pesticide metabolism and interactions, we have used in vitro metabolism data in human and animal hepatic in vitro models and clearance testing data to calculate chemical-specific adjustment factors, instead of fixed uncertainty factors, to be employed as an alternative and more realistic model for human health risk assessment of pesticides and other environmental pollutants. Ó 2013 Elsevier Inc. All rights reserved.

1. Health risk assessment of chemicals 1.1. General considerations In the health risk assessment of chemicals, the safety or uncertainty factor 100 is used to convert NOAEL (No Observed Adverse Effect Level) from an animal toxicity study to an ADI (Acceptable Daily Intake) value for human intake, ADI = NOAEL/100. However, the determination of a NOAEL is often based on data only from animal experiments. The assessment factor of 100 has often been used as a default to cover the inter- and intra-species variations [1,2]. Abbreviations: ADAF, adjustment factor for animal to human differences in toxicodynamic; ADI, acceptable daily intake; ADUF, uncertainty factor for animal to human differences in toxicodynamic; AKAF, adjustment factor for animal to human differences in toxicokinetic; AKUF, uncertainty factor for animal to human differences in toxicokinetic; ARfD, acute reference dose; CSAF, chemical-specific adjustment factors; CUF, composite uncertainty factor; CYP, cytochrome P450; HDAF, adjustment factor for human variability in toxicodynamic; HDUF, uncertainty factor for human variability in toxicodynamic; HKAF, adjustment factor for human variability in toxicokinetic; HKUF, uncertainty factor for human variability in toxicokinetic; MPPGL, milligrams of microsomal protein per gram of liver; NOAEL, no observed adverse effect level. ⇑ Address: Centre for Arctic Medicine, Thule Institute, P.O. Box 7300, FI-90014 University of Oulu, Oulu, Finland. Fax: +358 85533564. E-mail addresses: khaled.megahed@oulu.fi, [email protected] 1 Permanent address: Department of Pesticides, Menoufia University, P.O. Box 32511, Egypt. 0048-3575/$ - see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.pestbp.2013.08.003

Based on factor 100, Renwick [3,4] has attempted to provide a scientific basis for the default values of 10 for interspecies and 10 for interindividual variability. Renwick also proposed a division of each of these factors into subfactors to allow for separate evaluations of differences in toxicokinetic and toxicodynamic properties based on the relative magnitude of toxicokinetics and toxicodynamics variation between and within species. He proposed that the 10-fold factors for inter- and intra-species variation should be subdivided into factors of 4 for toxicokinetics and 2.5 for toxicodynamics. WHO/IPCS [5] has adapted the Renwick approach with one deviation. The UF (uncertainty factor) for interindividual variation should be divided into 3.16-fold for both toxicokinetics and toxicodynamics. The Swedish Chemical Agency, KEMI [6], has recommended the inclusion of assessment factors in risk assessment, when justifiable, since the scientific background for default assessment (uncertainty) factors in general remains unsatisfactory. WHO/IPCS [7] has proposed the use of chemical-specific toxicological data instead of default assessment factors, whenever possible. Consequently, Chemical-Specific adjustment Factors (CSAFs) have been introduced to provide a method for the incorporation of quantitative data on interspecies differences or interindividual variability in either toxicokinetics, of the active chemical moiety, or toxicodynamics into the risk assessment procedure, by modifying the relevant default UF of 10. The basic idea is to replace one or

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more of these subfactors with chemical-specific factors that can be derived from quantitative chemical-specific data. The assessment factor may increase or decrease and the differences may be considerable (Fig. 1) [7,8]. 1.2. Interspecies differences and interindividual variability in toxicokinetics Due to data limitation for most substances, an assessment factor is usually applied for extrapolation. Species-specific differences, based on chemical-specific data, between animals and humans should be taken into consideration in the extrapolation of data from animal studies to humans [7]. The interspecies assessment factor is generally recognized as providing an extrapolation from an average animal to an average human being, assuming that humans are 10-fold more sensitive than experimental animals. The assessment of species differences in glucuronidation and the metabolism of human CYP1A2 substrates supported the need to replace the default factor by compound-specific quantitative data [9,10]. KEMI and Falk-Filipsson et al. [6,11] suggested a speciesspecific default factor, if no chemical-specific data are available. This factor should be based on differences in caloric demand and is thus 4 for extrapolation from rats, 7 from mice, 3 from guinea pigs, 2.4 from rabbits and 1.4 from dogs. Human susceptibility to chemicals may depend on a number of determinants, including for example the genotype and gender of the individual, age, growth and development, health status and lifestyle factors [11]. Laboratory animals are initially healthy, of similar age and are fed with the same feed, and genetic variability is limited. Thus, interindividual variation in sensitivity towards toxic agents can be expected to be much higher within the human population than in inbred strains of laboratory animals. It has been suggested by KEMI [6] that an interindividual factor of 3–5, with differences in sensitivity due to enzymatic polymorphisms not included in this estimate, might be sufficient to reflect the toxicokinetic variability between healthy adults. Falk-Filipsson et al. [11] concluded based on several analyses [4,12–22] that an inter-individual factor of 3.2 might not be appropriate to reflect the toxicokinetic variability between individuals, and they suggested a factor of 4.5 as a minimum. 1.3. Considerations regarding in vitro-in vivo extrapolation Risk assessment needs reliable scientific information and one source of information is the characterization of metabolic fate

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and toxicokinetics. Human data is needed in order to obtain quantitative toxicokinetic data for comparisons between individuals or between animals and humans [11]. Because humans cannot be used as study subjects with pesticides except in occasional circumstances, we have to rely upon in vitro and animal experiments. In vitro metabolic data for the active chemical moiety can be used as a sufficient data basis to derive a chemical-specific adjustment factor [6,23] taking into account that metabolism is usually the most important factor contributing to interindividual and interspecies differences in toxicokinetics. Using in vitro-derived techniques such as microsomes, the kinetic parameters Vmax (the maximal velocity of the reaction) and Km (the substrate concentration that gives one-half Vmax) values and thus, the intrinsic clearance (CLint, LM = Vmax/Km), can be determined experimentally. A comprehensive discussion of assumptions behind these measures can be found in an excellent report by Houston [24]. However, in vitro chemical specific quantitative data can be scaled to determine the in vivo hepatic clearance for the metabolism of certain compounds. Comparison between the in vivo hepatic clearance CLH [L/min] between species, e.g., the clearance in each tested mammalian microsome is divided by the clearance in humans. The MPPGL, milligrams of microsomal protein per gram of liver, liver blood flow QH (L/min), as well as the size of the liver are needed for the extrapolation [25–27]. In vivo hepatic clearance for the metabolism of a compound can be extrapolated from experimentally determined in vitro intrinsic clearance (CLLM) and actual measurements of MPPGL. The pharmacokinetic parameters can be calculated as following: In vitro intrinsic clearance. CLint, LM [ml/min/mg protein] = Vmax/Km. Hepatic intrinsic clearance. CLint, whole liver [ml/min] = CLint, LM [ml/min/mg protein]  MPPGL  liver weight.  Hepatic clearance.  CLH [L/min] = CLint, whole liver [L/min]  QH/(CLint, whole liver [L/min] + QH).    

2. In vitro and human-derived techniques for testing xenobiotic metabolism In vitro systems have become an integral part of drug metabolism studies as well as throughout the drug discovery process and in academic research [28–30]. In vitro approaches to predict human clearance have become more frequent with the increase

Fig. 1. The subdivision of the 100-fold default uncertainty factor and the integration of in vitro data, modified from [6,8,27].

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in the availability of human-derived materials [31]. All models have certain advantages and disadvantages, but the common advantage to these approaches is the reduction of the complexity of the study system. However, the use of in vitro models is always a compromise between convenience and relevance [27,29,30,32].

2.1. Subcellular fractions (liver microsomes and homogenates) Subcellular fractions including microsomes are the most widely used in vitro systems in drug metabolism studies of new drug candidates [33,34]. Microsomes consist of vesicles of the hepatocyte endoplasmic reticulum and are prepared by standard differential ultracentrifugation [34]. Hepatic microsomes are useful for evaluation of metabolic stability, metabolite identification and quantification, and enzyme inhibition.

2.2. cDNA-expressed CYPs (single-enzyme systems) Recombinant xenobiotic metabolizing enzymes are well established and commercially available e.g. Supersomes™. These enzymes are expressed in bacterial [35], yeast [36], and mammalian cell lines [37] and human lymphoblast or baculovirus-infected insect cells [38].

2.3. Hepatocytes Hepatocytes are used to evaluate the metabolic stability of the compounds and identify the metabolizing enzymes and enzyme inhibition. Hepatocytes in suspension are technically the easiest of all hepatocyte systems. However, interspecies comparison seems to be more reliable with hepatocytes in suspensions than in culture due to potential damage of cytotoxic substances and variations in the expression levels of xenobiotic metabolizing enzymes in cultures [39].

2.4. Liver slices Liver slices have begun to slowly fall out of use in the prediction of pharmacokinetic properties and drug metabolism due predominantly to issues associated with drug movement into and out of the slices, lower enzyme activities and the increased use of hepatocytes to study similar reactions [40–43]. However, liver slices are still a powerful tool to study biotransformation in vitro [32,44].

2.5. Immortalized cell lines Different human and animal cell lines are available (http:// www.lgcpromochem-atcc.com). Human liver cell lines can be isolated from primary tumors of the liver parenchyma, developed after chronic hepatitis or cirrhosis [45]. Recently a new human hepatoma cell line, HepaRG, was derived from a hepatocellular carcinoma. The HepaRG cells express a large panel of liver-specific genes including several cytochrome P450 enzymes such as CYP1A2, CYP2B6, CYP2C9, CYP2E1 and CYP3A4, which is in contrast to the other hepatoma cell lines such as HepG2. In addition to P450 enzymes, HepaRG cells have a stable expression of phase II enzymes, transporters and nuclear transcription factors over a time period of six weeks in culture [46–50]. An important limitation with the HepaRG cell line is that it has been derived from a single donor and therefore it does not represent the high level of inter-individual variability that is known to exist with the biotransformation enzymes.

3. In vitro characterization of the metabolism and metabolic interactions of xenobiotics The aim of in vitro characterization is to produce relevant and useful information on metabolism and interactions to anticipate, and even to predict, what happens in vivo in man. Each in vitro model has its own set of advantages and disadvantages as they range from simple to more complex systems: individual enzymes, subcellular fractions, cellular systems, liver slices and whole organ, respectively [29,30,32]. To understand some of the factors related to xenobiotic metabolism that can influence the achievement of these aims, there are several important points to consider such as: determination of the metabolic stability of the compound, identification of reactive metabolites, evaluation of the variation between species, identification of human CYPs and their isoforms involved in the activation or detoxification, evaluation of the variation between individuals, identification of individuals and subpopulations at increased risk, and overall improvement of the process of human risk assessment [27,29,30,51]. An overview of different in vitro studies for the characterization of metabolism and metabolic interactions of xenobiotics are discussed below. 3.1. Metabolic stability of the compound Several in vitro test systems (microsomes, homogenates, hepatocytes or recombinant proteins) are available to determine metabolic stability. In vitro methods for the study of stability are probably the most well-established of drug metabolism systems. As a result, if a new chemical entity is rapidly metabolized in vitro, its bioavailability and persistence in vivo are most probably too low for it to be a drug candidate. There are two main components to any in vitro screen for metabolic stability; namely, a system for metabolizing the compounds and a means of analyzing the metabolic reaction [52,53]. Similar studies performed in human and test species give valuable information for the selection of test species for pharmacokinetic and toxicological in vivo studies. Moreover, the determination of metabolic stability of human in vitro incubation systems results in the possibility of extrapolation to the in vivo situation [27,53,54]. 3.2. Identification of metabolites and metabolic routes During the last few years, human subcellular preparations and recombinant enzymes have become readily available and can be used to generate metabolites of compounds that can then be rapidly identified and quantified using modern, highly sensitive analytical techniques. LC/MS has proven its status as the most powerful analytical tool for screening and identifying drug metabolites in modern drug discovery [29,30,53,55–57]. These analytical techniques have become irreplaceable for drug metabolism laboratories, providing large amounts of information from a wide variety of samples. It has to be stressed that mass spectrometers are not all the same and choosing the wrong LC–MS system may lead to compromised data quality or biased results as well as wasted time and effort [53]. 3.3. Identification of the metabolizing enzymes If the results of the metabolic stability and metabolic routes in human in vitro systems indicate that CYP enzymes contribute significantly to the metabolism of a xenobiotic, then identification of the individual CYP enzyme(s) involved in the metabolism of a xenobiotic is necessary for in vitro – in vivo extrapolation and prediction. Due to the broad substrate specificity of CYP enzymes, it is possible for more than one enzyme to be involved in the metabolism of a single compound. In vitro methods have been established

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to determine which CYP isoform(s) is (are) involved in the metabolism of a xenobiotic [29,30]. The approaches employed for this purpose will be presented below. 3.3.1. cDNA-expressed enzymes The availability of a full panel of recombinant enzymes covering the major human liver CYPs allows a direct approach for assaying the metabolism of a compound by incubation with the isolated isoforms. This can be done by following substrate consumption or product formation by each isoform using the same analytical methods as for HLM-based assays [55]. The biotransformation of a xenobiotic by a single CYP does not necessarily mean its participation in the reaction in vivo. The relative roles of individual CYPs cannot be quantitatively estimated using this approach due to the interindividual variation in the levels of individual active CYPs in the liver [58,59]. However, cDNA-expressed CYPs are well suited for isozyme identification in a high-throughput screening format [60]. The relative importance of individual isoform to in vivo clearance is dependent upon the relative abundance of each isoforms. When taking into account the average composition of human hepatic CYPs, an approximate prediction of the participation of any CYP enzyme in the whole liver activity can be achieved [61,62]. 3.3.2. Correlation studies Using a bank of ‘‘phenotyped’’ liver microsomes, correlation analysis can be performed. Correlation analysis involves measuring the rate of xenobiotic metabolism by several liver samples from individual humans and correlating reaction rates with the level of activity of the individual CYP enzymes in the same microsomal samples. If there are a sufficient number of individual samples (at least ten), the correlation plot would give the information needed for the evaluation of the participating CYPs. The higher the correlation between the activities, the larger the probability that the respective CYP enzyme is responsible for the metabolism of the xenobiotic. Another approach is to correlate the levels of an individual CYP determined by Western blot analysis against the metabolic activity [32,37,63–66]. 3.3.3. Inhibition studies with CYP-selective chemical inhibitors and specific antibodies Pooled human liver microsomes or individual liver microsomal samples could be used to examine the effect of CYP-selective chemical inhibitors or selective inhibitory antibodies. Antibody inhibition involves an evaluation of the effects of inhibitory antibodies against selective CYP enzymes on the metabolism of a xenobiotic in human liver microsomes. Chemical inhibition involves an evaluation of the effects of known CYP enzyme inhibitors on the metabolism of a xenobiotic. Several compounds have been characterized for their inhibitory potency against different CYPs; for example, furafylline is perhaps the most potent and selective inhibitor of CYP1A2, tranylcypromine of CYP2A6, thio-tepa and ticlopidine of CYP2B6, trimethoprim and sulfamethoxazole are selective inhibitors of CYP2C8 and CYP2C9, respectively, fluconazole of CYP2C19, quinidine is a commonly used in vitro diagnostic inhibitor of CYP2D6 activity, pyridine and disulfiram of CYP2E1, and ketoconazole and itraconazole are among many potent and relatively selective inhibitors of CYP3A4 often used in vitro and in vivo as diagnostic inhibitors [29,30,67–72]. 3.3.4. Inhibition of CYP enzymes Testing the inhibitory interactions of a xenobiotic on CYP-specific model activity in human liver microsomes in vitro provides information about the affinity of the compound for CYP enzymes [30]. The type of CYP inhibition can be either irreversible (mechanism-based inhibition) or reversible. Irreversible inhibition

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requires biotransformation of the inhibitor, while reversible inhibition can take place directly, without metabolism. Reversible inhibition is the most common type of enzyme inhibition and can be further divided into competitive, noncompetitive, uncompetitive, and mixed-type inhibition [67]. The inhibitory interactions of a xenobiotic on CYP enzymes can be tested by co-incubating a series of dilutions of a xenobiotic with a reaction mixture containing single or multiple substrates. In the single substrate assay, traditionally CYP interaction studies are performed using specific assays for each CYP isoform. A decrease in probe metabolite formation produced by inhibition is usually analyzed by LC–UV, LC–MS or fluorometry. In the cocktail assay, several CYP-selective probes are incubated with human liver microsomes and analyzed by LC– MS–MS [73,74]. 3.4. Interactions due to enzyme induction/inhibition Environmental pollutants can potentially cause drug interactions via interactions with the major metabolizing enzymes, Investigating the potential for these interactions is a multi-step process, firstly the individual toxicant must be investigated, the metabolism pathway needs to be identified and the metabolites produced identified and quantified. These metabolites also require investigation for their potential to inhibit or induce metabolizing enzymes. The next stage of the investigation is to extrapolate this to the potential for exposure and therefore adverse interactions. 3.5. Integrated use of in vitro data The above presentation of in vitro metabolism, kinetic and interaction experimental techniques constitutes the background for the integrated use of the data for risk assessment purposes. Each pesticide is ‘‘an individual’’ with its own characteristics regarding toxicokinetics and this individuality is revealed by the judicious use of all the experimental approaches described above. However, the main challenge is how to translate the in vitro measured characteristics into the information useful for the risk assessment process. Below we present our own case studies on the approach that employ the use of extrapolated in vitro measures as chemical-specific adjustment factors for the calculation of composite uncertainty factors. Another, and probably more precise and ultimately more realistic, approach is to use modelling and simulation for risk assessment process, for example the physiologically based toxicokinetic modelling, which however needs more extensive experimental data and comprehensive background knowledge on various physiological and demographic factors. This approach is surveyed in a recent comprehensive report [75]. 4. Case studies of diuron and carbosulfan Practical examples of extrapolating in vivo hepatic clearance using in vitro techniques for diuron, as one of the phenylurea herbicides, and carbosulfan, a carbamate insecticide are illustrated below. 4.1. Quantitative prediction of in vivo pharmacokinetic parameters from in vitro metabolic data In vitro biotransformations and dispositions of diuron and carbosulfan were studied in seven mammalian hepatic microsomes including human to investigate interspecies differences as well as in 10 individual hepatic microsomes to investigate interindividual variability [76–78]. Human liver samples were from 10 individuals of Caucasian race including four females and six males between the ages of 21–62 years. Intracerebral hemorrhage was the primary

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cause of death. More detailed characteristics of the liver samples are presented in our previous publication [79]. Metabolites were identified by LC–TOF and quantified by triple quadrupole mass spectrometry. In the case of diuron, the only metabolic pathway detected was demethylation at the terminal nitrogen atom resulting N-demethylmetabolite. The active N-demethylmetabolite exhibited higher non-target toxicity, based on toxicity assays towards bacteria, than the parent compound, diuron. The kinetic parameters Vmax and Km were calculated by nonlinear regression. In the case of carbosulfan, of eight detected carbosulfan metabolites, seven were identified with the help of the reference standard. These metabolites were carbofuran, 3-hydroxycarbofuran, 3-hydroxy-7- phenolcarbofuran, 3-ketocarbofuran, 3-keto-7-phenolcarbofuran, 7-phenolcarbofuran and dibutylamine. We have assumed that the unidentified metabolite is carbosulfan sulfinamide based on published reports [80,81]. 3-Hydroxycarbofuran was the main carbosulfan metabolite in all species and individuals, but otherwise there were some qualitative interspecies differences in carbofuran pathway metabolites. Only rabbit liver microsomes were able to metabolize carbofuran via hydroxylation to 7-phenolcarbofuran. Carbofuran was not detected in dog liver microsomes due to the rapid further metabolism. In general, liver microsomes from all seven species and individuals produced more toxic products (carbofuran, 3-hydroxy-carbofuran, 3-ketocarbofuran) more rapidly than the detoxification product (carbosulfan sulfinamide). 4.2. In vitro – in vivo extrapolation for the active chemical moiety The data we have presented show both differences and similarities in the in vitro metabolism of pesticides in liver microsomes of human and experimental animals, and this may be important in extrapolating data from in vitro to in vivo. Pharmacokinetic variables for the metabolism of selected pesticides in the human and animal body were extrapolated from in vitro data. The in vitro intrinsic clearance (CLint, LM) was determined experimentally and the value obtained used to estimate hepatic clearances (CLH) per kg body weight (Tables 1 and 2) [27]. The calculated in vivo hepatic clearances based on in vitro intrinsic clearances (CLint, LM) were considerably different in different species.

the reason why hepatic clearances for the active metabolite, CLH, per kg body weight were used for interspecies comparison in toxicokinetics. In these calculations CLH, per kg body weight in experimental animals, for the active chemical moiety, were divided by the clearance in humans (Table 1). The highest AKAF are 3.9 for Ndemethyldiuron and 3.5 for the carbofuran metabolic pathway. It must be stressed here that we measured only the hepatic metabolism, assuming that there is a negligible contribution of extrahepatic metabolism; however, metabolism is often the most important factor contributing to interspecies differences in toxicokinetics. 4.3.2. Interindividual variability and the calculation of the HKAF factor for carbosulfan Hepatic clearances were calculated for carbosulfan in ten donors and used for HKAF extrapolation. Since interindividual variability addresses the potential differences in the response of a sensitive individual compared to an average individual, the HKAF is 1.1 as the variation between the mean and the highest value as defined by Renwick and Lazarus [84]. Our studies with carbosulfan suggested that in vitro extrapolated interindividual variability in toxicokinetics is within the standard applied factors for interindividual extrapolation in toxicokinetics restricted to in vitro hepatic metabolism in the Caucasian race. 4.3.3. Calculation of the composite uncertainty factor (CUF), carbosulfan as an example The use of chemical-specific data has the effect of replacing a default factor for an area of uncertainty with chemical specific data, thereby reducing the overall uncertainty. CUF is the composite value obtained on multiplying the CSAF, used to replace a default subfactor, by the remaining default subfactors for which suitable data were not available. The composite uncertainty factor (CUF) could be either greater than or less than the usual default, 100, depending on the quantitative scientific data that have been introduced to reduce the default uncertainty factor [7] (Fig. 1). The CUF is generally shown as: CUF = [AKAF or AKUF]  [ADAF or ADUF]  [HKAF or HKUF]  [HDAF or HDUF]. Where:  AKAF Adjustment factor for animal to human differences in toxicokinetic.  AKUF Uncertainty factor for animal to human differences in toxicokinetic.  ADAF Adjustment factor for animal to human differences in toxicodynamic.  ADUF Uncertainty factor for animal to human differences in toxicodynamic.  HKAF Adjustment factor for human variability in toxicokinetic.  HKUF Uncertainty factor for human variability in toxicokinetic.  HDAF Adjustment factor for human variability in toxicodynamic.  HDUF Uncertainty factor for human variability in toxicodynamic.

4.3. Establishing the composite uncertainty factor for chemical risk assessment 4.3.1. Interspecies differences and the calculation of AKAF In the chemical risk assessment, traditional default values are used to account for interspecies differences and for human variability. Modern approaches aim to replace the default factors by dataderived values. The basic physiological parameters, such as body weight, liver weight and liver blood flow, vary between laboratory animal species and humans. There are large differences in physiological parameters in mice compared to humans [82,83]. This is

Table 1 In vivo hepatic clearance extrapolated from in vitro incubation in human and mammalian liver microsomes (LM) and the calculated AKAF for the active chemical moieties of diuron and carbosulfan. N-demethyldiuron

Human LM Dog LM Rabbit LM Rat LM Mouse LM Minipig LM Monkey LM

Carbofuran metabolic pathway

CLint, LM [ml/min/mg protein]

CLH/kg B.W [ml/min/kg]

AKAF

CLint, LM [ml/min/mg protein]

CLH/kg B.W [ml/min/kg]

AKAF

0.17 0.40 0.31 0.08 0.21 0.16 0.33

15.9 34.8 37.2 36.0 62.1 26.8 1.7

2.2 2.3 2.3 3.9 1.7 2.7

0.45 0.22 0.34 0.33 0.25 0.47 0.45

18.5 31.6 37.5 58.0 64.9 36.0 47.0

1.7 2.0 3.1 3.5 1.9 2.5

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Table 2 Calculated in vivo hepatic clearance of the carbosulfan active moiety, the carbofuran metabolic pathway, extrapolated from incubation in ten donor liver microsomes (HLM).

CLint, LM [ml/min/mg protein] CLH/kg B.W [ml/min/kg]

HLM20

HLM21

HLM22

HLM23

HLM24

HLM28

HLM29

HLM30

HLM31

HLM32

0.391 18.40

0.264 16.92

0.365 17.93

0.381 17.89

0.671 19.67

0.420 19.03

0.394 18.18

0.473 17.65

0.101 14.18

0.354 15.99

In the case of carbosulfan, the CUF is a composite of adjustment factors for interspecies differences and human variability in toxicokinetics and uncertainty factors for interspecies differences and human variability in toxicodynamics. CUF = AKAF  ADUF  HKAF  HDUF, Therefore, CUF = 3.5  2.5  1.1  3.16 = 30. On the basis of Cmax, the uncertainty factor for some pesticides has been changed. FAO/WHO [85] established an acute reference dose (ARfD) for the carbamate insecticide, carbaryl, of 0.2 mg/kg bodyweight based on a NOAEL of 3.8 mg/kg bodyweight per day identified on the basis of inhibition of cholinesterase activity observed at 10 mg/kg bodyweight per day in a 5-week dietary study in dogs with the application of a 25-fold CUF. On the other hand, in the Australian evaluation of carbaryl, the current Australian ARfD of 0.01 mg/kg bodyweight is based on a NOEL of 1 mg/kg bodyweight per day identified on the basis of behavioural indications of autonomic neurotoxicity, and inhibition of brain and plasma erythrocyte cholinesterase activity in a study of developmental toxicity and a 13-week study of neurotoxicity in rats, and using a 100-fold safety factor [86,87]. FAO/WHO [85,88], established an ARfD of 0.009 mg/kg bw for carbofuran, the active chemical moiety in carbosulfan metabolic pathway, on the basis of the NOAEL of 0.22 mg/kg bw per day with the application of a CUF of 25. This, together with our CUF value of 30 provides strong support for the use of in vitro chemical-specific quantitative toxicokinetics data and quantitative prediction of in vivo metabolic clearance for the calculation of CUF for xenobiotics for the overall improvement of the process of human risk assessment. 5. Conclusion Risk assessment is commonly based on laboratory studies where experimental animals are intentionally treated with high doses of the pesticide being studied. We have shown an approach to extrapolate in vitro metabolic data to in vivo situation and to translate interspecies and interindividual in vitro metabolic data into risk assessment of chemicals. However, when estimating the composite uncertainty factor from in vitro-in vivo extrapolation data, one should keep in mind some limitations. Results obtained from in vitro test systems are highly dependent on several technical factors including the microsomal protein amount, incubation time, and initial velocity conditions used in the test system etc. [67] The best predictive value is usually obtained when the substrate concentration used is within the linear part of the time and protein concentration curves for substrate depletion or metabolite formation [89–91] (cited from pelkonen et al. [67]. The prediction of in vivo metabolic clearance is based on many scaling factors and physiological measures, which should either be assumed or measured [27]. These include for example microsomal yield (if microsomes are used), liver weight, liver blood flow, extra-hepatic metabolism and clearances via other routes than hepatic metabolism. However, in the context of extrapolating in vitro data into risk assessment, it is of importance to note that although the measurements are restricted to in vitro hepatic metabolism of selected compounds, metabolism is probably in these cases the most important factor contributing to interindividual and interspecies differences in toxicokinetics.

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