Guidance for Evaluating In Vivo Fish Bioaccumulation Data

Guidance for Evaluating In Vivo FishBioaccumulation DataThomas F Parkerton,*� Jon A Arnot,` Anne V Weisbrod,§ Christine Russom,jj Robert A Hoke,#Kent Woodburn,�� Theo Traas,`` Mark Bonnell,§§ Lawrence P Burkhard,jj and Mark A Lampi�

�ExxonMobil Biomedical Sciences, Inc., Annandale, New Jersey, USA`Canadian Environmental Modelling Centre, Trent University, Peterborough, Ontario§Procter & Gamble, Winton Hill Business Center, Cincinnati, Ohio 45224, USAjjNational Health and Environmental Effects Laboratory, Office of Research and Development, US Environmental Protection Agency,Duluth, Minnesota#DuPont Haskell Laboratory for Health and Environmental Sciences, Newark, Delaware, USA��Health and Environmental Sciences, Dow Corning, Midland, Michigan 48686, USA``National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands§§Environment Canada—New Substances, Gatineau, Quebec

(Received 13 August 2007; Accepted 11 November 2007)

ABSTRACTCurrently, the laboratory-derived fish bioconcentration factor (BCF) serves as one of the primary data sources used to

assess the potential for a chemical to bioaccumulate. Consequently, fish BCF values serve a central role in decision making

and provide the basis for development of quantitative structure–property relationships (QSPRs) used to predict the

bioaccumulation potential of untested compounds. However, practical guidance for critically reviewing experimental BCF

studies is limited. This lack of transparent guidance hinders improvement in predictive models and can lead to uninformed

chemical management decisions. To address this concern, a multiple-stakeholder workshop of experts from government,

industry, and academia was convened by the International Life Sciences Institute Health and Environmental Sciences Institute

to examine the data availability and quality issues associated with in vivo fish bioconcentration and bioaccumulation data.

This paper provides guidance for evaluating key aspects of study design and conduct that must be considered when judging

the reliability and adequacy of reported laboratory bioaccumulation data. Key criteria identified for judging study reliability

include 1) clear specification of test substance and fish species investigated, 2) analysis of test substance in both fish tissue

and exposure medium, 3) no significant adverse effects on exposed test fish, and 4) a reported test BCF that reflects steady-

state conditions with unambiguous units. This guidance is then applied to 2 data-rich chemicals (anthracene and 2,3,7,8-

tetrachlorodibenzo-p-dioxin) to illustrate the critical need for applying a systematic data quality assessment process. Use of

these guidelines will foster development of more accurate QSPR models, improve the performance and reporting of future

laboratory studies, and strengthen the technical basis for bioaccumulation assessment in chemicals management.

Keywords: Bioconcentration Dietary biomagnification Data quality Anthracene 2,3,7,8-Tetrachlorodibenzo-p-

dioxin

INTRODUCTIONBioaccumulation potential is a key property that is con-

sidered in product classification and labeling, priority settingfor chemical management, pollution prevention initiatives,premanufacture notifications, environmental risk assessment,and derivation of environmental quality objectives (EC 1979,2003; USEPA 1999a, 1999b, 2000b; Environment Canada2003; OSPAR Commission 2004; United Nations EconomicCommission for Europe 2005; United Nations EnvironmentalProgram 2006). Currently, the laboratory-derived fish bio-concentration factor (BCF) serves as one of the principalsources of information used to assess the potential for asubstance to bioaccumulate in aquatic and marine environ-ments and potentially to pose indirect exposure concerns (viathe food chain pathway) to higher-tropic-level consumers,including humans. Consequently, fish BCF data are central indecisions of whether a chemical should be consideredbioaccumulative. These data have also been used for devel-

oping quantitative structure–property relationships (QSPRs)

to predict bioaccumulation potential for untested chemicals

(Veith et al. 1979; Bintein et al. 1993; Meylan et al. 1999).

However, while it is recognized that study design, methods,

and documentation quality affect bioaccumulation assessment

reliability (Barron and Woodburn 1995; Franke 1996),

guidance for critically reviewing BCF studies is limited (Arnot

and Gobas 2006). To address this concern, a workshop of

experts from governments, industry, and academia was

convened to examine the data availability and quality issues

associated with in vivo fish bioaccumulation data. The 1st

publication from this workshop reported on the sources of in

vivo fish bioaccumulation data (Weisbrod et al. 2007). This

2nd paper provides guidance for evaluating key aspects of

study design and conduct that need to be considered when

judging the quality of laboratory bioconcentration and dietary

bioaccumulation studies.

While information on the bioaccumulation of a chemical

can be provided by both laboratory and field studies, most in

vivo data for compounds in commerce have been derived from

laboratory tests. As a result, the principal focus of the

workshop and this summary is on the appropriate documen-

* To whom correspondence may be addressed:[email protected]

Published on the Web 11/11/2007.

Integrated Environmental Assessment and Management — Volume 4, Number 2—pp. 139–155� 2008 SETAC 139

Review—GlobalIssu

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tation and quality assessment of laboratory bioaccumulationtest data for organic chemicals. Although the general principlesoutlined in this report apply to evaluation of bioaccumulationdata for inorganic chemicals, this topic is beyond the scope ofthis paper and is the subject of past reviews (McGeer et al.2003; Luoma and Rainbow 2005). The guidance suggested inthis paper is then applied to 2 illustrative organic chemicals forwhich considerable in vivo fish data have been reported. Keyinsights gleaned from this analysis are then discussed withrespect to bioaccumulation assessment.

CHARACTERIZING DATA RELIABILITYThe systematic approach proposed by Klimisch has been

widely used to evaluate the quality of available substance-specific test data and considers 3 general study aspects:Reliability, relevance, and adequacy (Klimisch et al. 1997).Reliability determines whether the study was conducted infull or partial compliance with standardized test guidelinesand is sufficiently documented to yield data that arescientifically defensible. While reliability addresses thevalidity of the experimental design, study documentation,and reported test results, relevance addresses the appropriate-ness of the test endpoint for the substance under inves-tigation. For example, laboratory bioaccumulation test dataare not considered relevant for higher-molecular-weightpolymers because such materials are insoluble in water ordiet and impermeable to biological membranes (Connell1990; Environment Canada 2004). In contrast, adequacydetermines the usefulness of study data for the intendedpurpose (e.g., categorization or risk assessment). The Kli-misch data quality evaluation scheme has been adopted foruse in the International Uniform Chemical InformationDatabase and the Organization for Economic Cooperationand Development (OECD) Screening Information Data Setprogram. A similar approach is used by the US EnvironmentalProtection Agency (USEPA) in the High Production VolumeChallenge Program, in which key reliability criteria fordifferent types of studies are provided to guide data qualityreview (OECD 2004).

The Klimisch approach assigns studies into 4 reliabilitycategories. ‘‘Reliable’’ data are generated from studies thatcomply with or are comparable to published guidelines or areconducted with accepted methods that are described insufficient detail. If studies include adequate documentationbut lack specific details or deviate from guideline require-ments, such data may be deemed ‘‘reliable with restrictions,’’provided that deviations are judged acceptable, that is,unlikely to influence study results significantly. Data aredetermined to be ‘‘not reliable’’ when key considerations areclearly omitted or when documentation reveals unacceptabletest performance or methodological flaws. Data are defined as‘‘not assignable’’ when sufficient detail is not provided oncritical study aspects to reach an objective decision.

When data from multiple studies are available, a weight-of-evidence-analysis can maximize use of existing in vivo testresults, with greater weight placed on data from the reliablestudies. If multiple data sets of questionable or unknownreliability indicate consistent results, these data collectivelymay be judged adequate to characterize the bioaccumulationpotential for the substance in question. Data from structurallyrelated compounds may be used as surrogate values tocharacterize untested chemicals and prioritize the need toconduct additional compound-specific BCF testing.

TEST GUIDELINESNational and international standardized test guidelines are

available for conducting laboratory bioconcentration testswith fish (ASTM 1996; OECD 1996). While studies havebeen published on the bioaccumulation of chemicals follow-ing dietary exposure (Fisk et al. 1996, 1998, 2000; Brown etal. 2002; Stapleton et al. 2004), only a generic, notstandardized, laboratory protocol for fish is available (Anon-ymous 2004).

The requirements of current bioconcentration test guide-lines are considerable in terms of both cost and animal use (deWolf et al. 2007). Less onerous test requirements haverecently been proposed as potential modifications to theOECD 305 guideline that would significantly reduce costsand animal use (Woodburn and Springer 2005; Springer et al.2007). These proposed changes include using 1 instead of 2exposure concentrations and reducing the number of fishsamples collected during the uptake phase of the test.

Guidance for the conduct of field bioaccumulation studiesis lacking. However, recent work has identified importantfactors that contribute to uncertainty in field bioaccumulationendpoints and provided recommendations for improved fieldsampling designs (Burkhard 2003). While beyond the scopeof this paper, further efforts are needed to define bestpractices for field investigations of substance-specific bio-accumulation.

Key considerations for interpreting laboratory bioconcen-tration studies are described here based on past literaturereviews (Barron 1990) and recently proposed evaluationcriteria for bioconcentration data (Arnot and Gobas 2006).

Test substance information

The identity of the test substance, including chemicalname, Chemical Abstract Services Registration Number (CASRN), and information on purity, particularly for radiolabeledtest substances, should be provided. Biotransformation maylead to overestimates of the BCF for radiolabeled compounds,unless the parent compound is specifically quantified relativeto metabolites or impurities (see Test Substance Determinationin Water and Fish Tissue section).

Key physical-chemical properties should be considered instudy evaluation. Knowledge of water solubility (SW) helpsdetermine if the exposure concentration is likely to haveincluded undissolved chemical that may lead to an under-estimate of the BCF (see Exposure Conditions section). If theBCF is calculated from the observed ratio of the chemicalconcentration in test organisms to that in water (i.e., Cfish/Cwater), the octanol–water partition coefficient (KOW) canprovide insight into whether sufficient exposure time wasprovided for achieving steady-state conditions, assuming aworst-case (e.g., no metabolism) scenario (see Test Endpointsection; OECD 1996). In the case of ionizable chemicals, theacid dissociation constant (pKa) should be considered becausethe degree of ionization may affect bioconcentration kineticsand partitioning (Geyer et al. 2000; Escher and Hermens2004; Erickson et al. 2006a, 2006b).

Test species information

The test species identity and characteristics should bereported. Since life stage and gender may account fordifferences in metabolic biotransformation, and organism sizeinfluences accumulation kinetics, these details should beprovided. Whole-organism lipid content is another key

140 Integr Environ Assess Manag 4, 2008—TF Parkerton et al.

parameter because this variable is often used to characterizepartitioning of the test substance between the aqueousexposure medium and the test organism (Barron 1990).Large variations in BCF values for the same chemical may bedue to differences in the lipid content (Geyer et al. 1997).Current food web models assume that the substance half-lifein biota is proportional to the lipid content, therebyimpacting time to achieve steady state (Arnot and Gobas2003). Furthermore, because lipid normalization is increas-ingly being used in regulatory decision making, it is importantto report lipid content of the test species, ideally at selectedtimes during the test. Given that different methods for lipidextraction and analysis yield different results (Randall et al.1998), it is recommended that lipid data be judged forconsistency relative to a standard method (Bligh and Dyer1959). However, it must be recognized that for somechemical classes (i.e., perfluorochemicals), lipid may not bethe principal tissue compartment to which the substancepartitions. Therefore, caution must be applied in lipidnormalization across chemical classes (Martin et al. 2003).

Another common criterion for judging the acceptability ofbioconcentration studies is test organism health. While criteriavary, if fish mortality is less than 10% to 20% in treated andcontrol groups, it is recommended results be considered‘‘reliable.’’ In cases where .20% mortality is reported, it isrecommended that the study be considered ‘‘not reliable.’’ Ifno mortality data are provided, one option is to designate thestudy as ‘‘reliable with restrictions’’ if the exposure concen-tration used is at least a factor of 10 below the known orpredicted LC50. In contrast, if no mortality data are providedand the tested exposure concentration is within a factor of 10of concentrations expected to pose acute toxicity concerns, itis advisable to designate the study as ‘‘not assignable.’’

Test substance determination in water and fish tissue

Since the BCF measurement is critically dependent onaccurate knowledge of test substance concentrations in theexposure medium and fish tissue, analytical measurements ofthe test substance should be conducted in both the exposuremedium and the organism (Table 1, options AA, BB, AB orBA) for study reliability to be further considered. In addition,documentation (or further reference) is needed regarding thevalidity of the analytical method used. Laboratory tests thatinvolve radiolabeled test materials often involve nonspecificsubstance analysis in exposure medium and fish tissue (i.e.,total radioactivity is used to indicate the test chemicalconcentration). This analytical approach has often been usedbecause of its advantages in investigating mass balancemetabolic processes. However, depending on the nature ofthe analytical method(s) used, it can pose several concernswith respect to study interpretation (Barron et al. 1990). First,small amounts of radiolabeled impurities that may be presentin the test substance can confound interpretation of test

results. Second, in the absence of additional analyticalcharacterization data, biodegradation and biotransformationprocesses in the exposure medium and fish tissue can furthercomplicate test interpretation (ASTM 1996). As a result, itmay not be possible to assess the reliability of such studiesunless evidence is provided that impurities or degradationprocesses did not impact test results. Similarly, studies that arebased on questionable analytical methods for parent substancedetermination should also be designated ‘‘not assignable.’’

An important generalization is that BCF values based onsubstance-specific versus total radioactivity analyses will notbe directly comparable for substances that can undergobiotransformation because these 2 approaches quantify differ-ent analytes. For metabolizable substances, use of concen-trations derived from total radioactivity in organism tissuesmay overestimate bioaccumulation potential because bothparent compound and metabolites are quantified. Totalradioactivity can grossly overestimate bioaccumulation ifmetabolites are broken down and incorporated into organismtissues as a result of normal catabolic processes (e.g.,radiolabeled molecules may be incorporated into nativecellular components such as lipids or carbohydrates). Alter-natively, if metabolites are excreted from fish to water andthese metabolites are not differentiated from parent com-pound in the water analysis, the levels of parent compound inthe exposure medium may be overestimated, leading to anunderestimation of the BCF. Thus, while such studies mayconform to test guideline requirements, implying that suchstudies are ‘‘reliable’’ may in fact be misleading and notsupport consistent decision making or QSPR model develop-ment. Rather, only studies based on a parent substance–specific analysis in both exposure medium and fish tissueprovide reliable and adequate test data for these purposes(option AA; Arnot and Gobas 2006). Studies that attempt toestimate parent BCFs by multiplying BCFs based on totalradioactivity by the fraction of radioactivity that is measuredto be parent at the end of exposure period should be regardedas ‘‘not assignable’’ because this percentage may not beconstant but may change with time (Spacie et al. 1983).

Another method that has been reported in the literature fordetermining fish bioconcentration factors is referred to as the‘‘Banerjee method.’’ This test assumes that the measureddecline in measured aqueous concentrations of a testsubstance in a static exposure test system is due solely toaccumulation by exposed fish (Banerjee et al. 1984; de Voogtet al. 1991). This experimental design corresponds to optionAC or BC in Table 1, depending on whether substance-specific or nonspecific analyses are used to quantify aqueousexposure concentrations. Since this approach ignores thepotential for metabolism of the parent compound by the testorganisms and the potential confounding effects of abioticlosses in the test system on estimated fish concentrations, it isrecommended that this test design be judged as ‘‘not reliable.’’Similarly, tests that involve only nominal exposure concen-trations (options CA, CB, and CC) are judged ‘‘not reliable,’’consistent with other guidance that assigns low confidence tosuch studies (Arnot and Gobas 2006).

Exposure conditions

Three important criteria for judging the reliability ofbioconcentration tests, specified in both OECD and ASTMguidelines, relate to exposure conditions. The 1st criterion isthat exposure concentrations should not exceed the aqueous

Table 1. Options for test substance analysis

Determination of testsubstance concentration

Exposuremedium

Fishtissue

Parent substance analysis A A

Nonspecific substance analysis B B

Nominal/calculated C C

Guidance for Evaluating In Vivo Fish Bioaccumulation Data—Integr Environ Assess Manag 4, 2008 141

solubility of the test substance. While this appears straightfor-ward, practically it may be difficult to evaluate in publishedstudies because the aqueous solubility value for the testsubstance being investigated may be uncertain or unknown.Professional judgment is therefore required (including, in theabsence of measured data, the use of QSPR models toestimate water solubility such as EPISuite [USEPA 2000a] orSPARC [Karickhoff et al. 2007]) to determine if testexposures are likely above the solubility limit. In cases wheretest exposures are judged to likely exceed aqueous solubility,study data should be designated as ‘‘not reliable.’’ While thiscriterion is difficult to assess, the effect on calculation of BCFvalues is not trivial (Arnot and Gobas 2006).

For very hydrophobic chemicals (e.g., log KOW . 6),accurate measurement of the water phase becomes difficultbecause of sorption to organic matter (see Test Conditionssection). This latter process can significantly alter thebioavailability of the test substance and complicate BCF testinterpretation (Opperhuizen and Stokkel 1988). For suchchemicals, test results will depend on the quantity and qualityof trace concentrations of organic carbon present in thedilution water, which can significantly enhance the ‘‘appa-rent’’ solubility of the test substance. In principle, thisreduction in bioavailability for hydrophobic substances in‘‘clean’’ laboratory water will be even more pronounced innatural water because of higher concentrations of dissolvedand particulate organic carbon. Therefore, in cases wheredosing procedures avoid neat product (e.g., droplets) andmaintain low organic carbon concentrations in the aqueousexposure media, experimentally derived BCFs under labconditions are likely to be higher than would be expectedfrom aqueous exposure in natural waters. However, forchemicals with a log KOW . 6, dietary exposure may serveas an additional significant exposure pathway. Therefore,extrapolation of lab bioconcentration data to environmentalsituations is uncertain. In the absence of adequate field data,that is, a bioaccumulation factor (BAF), a dietary bioaccu-mulation and elimination study may provide an alternative,more relevant laboratory test for bioaccumulation assessmentof substances with log KOW . 6 rather than the traditionalbioconcentration test.

Chemical dispersants have sometimes been used tofacilitate dissolution of poorly water-soluble test substancesto aid in the generation of aqueous test concentrations. Whilethe use of solubilizing agents is not recommended in thecurrent OECD and ASTM guidelines, a recent comparativestudy using the OECD 305 test guideline suggests that forcertain chemicals and dispersant conditions, BCF results maynot be adversely affected if test substance concentrations arenot above the aqueous solubility limit (Yakata et al. 2006).However, other studies have shown that dispersants caninfluence bioconcentration (Landrum 1983). Therefore, it isrecommended that studies performed with dispersants beconsidered ‘‘not assignable’’ unless the influence of thedispersant is shown to be negligible.

The 2nd exposure-related test guideline requirement forbioconcentration tests is that aqueous exposure concentra-tions be below concentrations that cause toxicity as previouslydiscussed.

The 3rd criterion is that aqueous exposure concentrationsare ideally maintained at relatively constant levels during theuptake phase. In the case of the OECD 305 test guideline, theconcentration of test substance in the exposure chambers

should be maintained within 620% of the overall meanmeasured value. In the case of the ASTM guideline, thehighest measured concentration should be no more than afactor of 2 greater than the lowest measured concentration inthe exposure chamber. Both of these BCF test guidelinesrecommend that flow-through exposure conditions with lowfish-to-dilution-water ratios (below 1.0 g fish�L water�1�d�1)be used to minimize decreases in test substance concen-trations caused by fish uptake and to ensure that dissolvedoxygen concentrations are adequately maintained during thetest (see Test Conditions section).

While maintaining uniform exposure concentrations isdesirable, our collective experience suggests that the variancein observed tissue concentration often dictates the uncertaintyin BCF determination. As a result, higher random variation inmeasured exposure concentrations (e.g., concentration rangewithin factor of 3) could be acceptable for a study to bejudged ‘‘reliable.’’

In cases where the variation in measured exposureconcentration is larger (e.g., a factor of 3 or more) andnonrandom in nature (e.g., declining over time), it may bepossible to apply kinetic models to estimate the steady-stateBCF for the test substance that takes this dynamic behaviorinto account (Gobas and Zhang 1992; van Haelst et al. 1996;Baussant, Sanni, Skadsheim, et al. 2001). In fact, this testdesign forms the basis of the ‘‘adjusted-Banerjee method,’’ inwhich the decline in the aqueous concentration and concom-itant measured increase in fish tissue concentration that areobserved in a static test system are used as model input todetermine the toxicokinetic parameters that define the BCF(de Maagd 1996). Results from a test applying the ‘‘Banerjeemethod’’ and associated models are illustrated in Figure 1.Unlike flow-through tests, this test system typically employshigh fish-to-dilution-water loading so that depletion ofaqueous concentrations and associated fish uptake can bedetermined over a short exposure duration, such as 2 d(Gobas and Zhang 1992). Therefore, while this experimentaldesign has a number of practical advantages over the longer,constant exposure flow-through test, application of thesemodels to test data introduces additional uncertainty intoBCF estimation. Moreover, little work has been done tostandardize such exposure-modeling approaches or to dem-onstrate their equivalence with results from accepted testguidelines. Given that these methods involve transient, short-term exposures, such test conditions may not providesufficient internal doses to allow induction of and subsequentaction of enzymes responsible for biotransformation, as wouldoccur in a guideline BCF test. A recent study of phenanthrenebioconcentration in goldfish determined that accumulationover 48 h may overstate steady-state tissue concentrationsmeasured over longer exposure periods (Sun et al. 2006).Therefore, it is suggested that studies based on the ‘‘adjustedBanerjee’’ method be designated as ‘‘not assignable.’’ How-ever, further research to evaluate and optimize this exper-imental design could lead to a ‘‘reliable’’ alternative in vivotest protocol that reduces fish use and testing costs.

Test conditions

Dissolved oxygen saturation has been included as a qualitycriterion in both OECD and ASTM guidelines. Thesemethods require that .60% oxygen saturation be maintainedin test chambers throughout the study. It is recommendedthat as long as unacceptable mortality does not occur, studies


that deviate in this requirement be considered ‘‘reliable withrestrictions.’’

Both OECD and ASTM guidelines recommend that watertemperature should be maintained constant during the testwith fluctuations of 62 8C from the designated test temper-ature. In bioconcentration studies that last several weeks,temperature fluctuations above the 62 8C guidance may beacceptable if unacceptable mortality does not occur. In caseswhere BCF data are presented at multiple temperatures,results that are reflective of the normal temperature range ofthe test species is preferred because temperature extremesmay result in organism stress and altered metabolic function,thereby potentially confounding interpretation of BCF testdata (Staples et al. 1997).

For chemicals that are ionized at environmental pH, the pHof the dilution water should be reported because the BCF maybe pH dependent. This key parameter has often not beenreported in past bioaccumulation studies for ionizablechemicals (Arnot and Gobas 2006).

The amount of total organic carbon (TOC) in dilutionwater is also an important water quality parameter to considerwhen testing hydrophobic test substances (log KOW . 6)because organic colloids can complex test substance, enhanceapparent solubility, and reduce the bioavailability of measuredaqueous exposure concentrations (Figures 2A and B). OECDand ASTM guidelines indicate that TOC should be below 2and 5 mg/L, respectively. It is therefore suggested that studieswith hydrophobic substances that report TOC above 2 mg/Lbe considered ‘‘not reliable’’ because dilution waters withhigher TOC can result in an underestimation of the BCF forhydrophobic substances. In the absence of information onTOC, provided that the study is conducted under flow-through conditions, it is proposed that the study be judged as‘‘reliable with restrictions.’’ If TOC is not reported for staticor semistatic studies, test results should be judged as ‘‘notassignable.’’

Test endpoint

The first important aspect for judging the reliability of thereported test endpoint is the unambiguous specification ofBCF units (wet, dry, lipid) and tissue type (e.g., whole body,

muscle, fillet, liver, fat). In such cases, where BCF values arespecified for tissue types rather than whole body, it issuggested that test results not be considered adequate fordecision-making or model training purposes unless tissue-specific values can be extrapolated to whole body using anappropriate calculation approach (e.g., lipid normalization).

A 2nd key consideration is that the BCF test result reflectssteady-state conditions. The steady-state BCF value may beobtained using the plateau method, that is, taking the ratio offish to water concentrations when the fish concentrations arenot significantly different between 3 sequential samplingpoints, given constant aqueous exposure during the uptakephase. Alternatively, the full range of concentration data canbe used to calculate the uptake and depuration rate constantsusing a kinetic approach. The BCF is then derived using thekinetic model parameters. Either the plateau or the kineticmethod can be used to determine a reliable estimate of thesteady-state BCF. If neither of these approaches was used tocalculate the BCF value from a test, the study should beconsidered ‘‘not reliable,’’ unless the exposure duration wassufficiently long to provide or allow correction to reflectsteady-state results. The following description provides back-ground on how a BCF can be evaluated and potentiallyadjusted using this 3rd method. However, because of theassumptions that must be invoked for this analysis, it isrecommended to treat BCF data derived using this method as‘‘not assignable.’’

Endpoint estimation methods—Several equations may beused to evaluate if reported BCF test data reflect steady-stateconditions or aid in designing future studies. The accumu-lation of organic compounds by fish and other aquaticorganisms is often described by a dynamic equilibriumbetween the uptake clearance of the chemical from waterby the organism and the rate at which the compound isdissipated by the organism (i.e., elimination and metabolicbiotransformation, along with growth dilution); the degree ofbioconcentration is determined by the relative rates of theseprocesses. Such bioconcentration models consider both thebiological attributes of the fish and the physicochemicalproperties of the chemical, as they collectively determine thediffusive exchange across membranes. Important biological

Figure 1. Illustration of static exposure bioconcentration test methods. In the ‘‘Banerjee’’ method (Banerjee et al. 1984), the decline in the mass of testchemical in water is assumed to be conserved by uptake into fish tissue. Thus, fish concentrations are predicted, not measured. In the ‘‘adjusted Banerjee’’method, both the decline and the accumulation of mass in water and fish are measured. The difference in predicted fish concentrations and resultingbioconcentration factors derived using these models is due to abiotic and biotic losses in the static test system, including biotransformation in fish tissues.


characteristics typically addressed in such models are fishbody weight, respiration rate, lipid content, and growth rate.

A relevant physicochemical property is the n-octanol–water

partition coefficient (KOW) of the substance, which is used as

a surrogate to quantify chemical partitioning to the lipid and

structural organic fractions of the fish. The uptake clearance

(K1) of the chemical into the fish can be related to the

respiration rate of the fish:

K1 ¼ EcV ¼Ecrox

EoxCoxð1Þ

where

EC ¼ gill uptake efficiency of the test substance (unitless)

V¼ fish ventilation rate (mL�gwet�1�d�1)

Eox ¼ gill uptake efficiency of oxygen (unitless)

rox ¼ fish respiration rate (goxygen�gwet�1�d�1)

Cox ¼ dissolved oxygen concentration (goxygen�mL�1)

For substances in the range of log Kow from about 3 to 6,

the ratio of chemical-to-oxygen gill uptake efficiency is

estimated to be approximately 1 (McKim et al. 1985; Black

et al. 1991). However, for more hydrophobic substances,chemical complexation to TOC in dilution water is unavoid-

able and reduces bioavailability. As a result, the ratio of

chemical to oxygen gill transfer efficiencies declines as

predicted by the following bioavailability correction (Gobasand Arnot 2003):

/ ¼ Ec

Eox¼ 1

1þ 0:35POCKow þ 0:08DOCKowð2Þ

where POC and DOC are the particulate and dissolvedorganic carbon concentrations (kg/L) in dilution water,respectively. The respiration rate can be estimated from thetemperature-dependent allometric equation for fish (Thur-ston and Gehrke 1993):

rox ¼ 0:013W�0:195T0:29e0:035TN ¼ 2; 121; R2 ¼ 0:86

where W is fish weight in gwet and T is temperature in 8C.For many neutral organic chemicals, knowledge of fish

weight, test temperature, and dissolved oxygen concentra-tions, along with Equations 1 to 3, allows one to predict thegill elimination rate (K2; Gobas and Arnot 2003):

K2 ¼K1

LKowð4Þ

whereK1¼ uptake clearance of test substance (mL�gwet

�1�d�1)L ¼ lipid fraction of test fish (g lipid�g wet

�1)Kow ¼ octanol–water partition coefficient of the test

substance

Figure 2. Predicted influence of particulate organic carbon (POC) and dissolved organic carbon (DOC) concentrations on the apparent increase in watersolubility (A) and fraction of freely dissolved concentrations (B). Calculations are based on Equation 4.


The time required to approach steady state can beestimated from an assessment of potential first-order lossprocesses:

t90 ¼2:3

K2 þ KE þ KM þ KGð5Þ

wheret90 ¼ time required to approach 90% of steady-state fish

concentration (days)K2¼ gill elimination rate of test substance (per day)KE ¼ fecal egestion rate of test substance (per day)KM ¼ biotransformation rate of test substance (per day)KG ¼ growth rate of fish (per day)The first 3 of these loss rates (i.e., K2) depends in part on

the test substance under investigation, while the last rate (i.e.,KG) depends on experimental design (e.g., life stage and sizeof the fish, the quantity and quality of the dietary ration, andthe experimental temperature), unless exposure to the testsubstance adversely impacts fish growth.

Elimination from the gut (i.e., KE) depends on KOW and canbe estimated by Equation 6 (Gobas and Arnot 2003):

KE ¼0:007W�0:15

5:1 3 10�8KOW þ 2ð6Þ

where W is fish weight expressed in units of gwet.Generic relationships for estimating biotransformation

rates (i.e., KM) are not yet available but are the subject ofongoing research (Arnot et al. 2008). Existing informationindicates that fish biotransformation rates can vary appreci-ably depending on chemical class from negligible to .10 perday (Gobas and Arnot 2003; van der Linde et al. 2001).Because bioconcentration tests often use small juvenile fish(e.g., �1 g) that are fed high-quality diets at a ratio of 1% to2% body weight per day, growth rates of 0.001 to 0.01 per dayare typical. However, lower growth rates (or no growth) mayoccur for adult or larger juvenile fish under certain testconditions.

Figure 3 illustrates how the previous equations can aid inassessing if reported BCF test data reflect steady-stateconditions (or in designing future studies). The predictedtime required to approach 90% of steady state, t90, is plottedas a function of log KOW for small (1 g, 3% lipid) and large(100 g, 8% lipid) fish for different growth and biotransfor-mation rate scenarios. For these calculations, a temperature of15 8C, dissolved oxygen concentration of 8.0 mg/L (8 3 10�6

g/mL) and a DOC concentration of 1 mg/L (10�6 kg/L) wereassumed. Results show that smaller, leaner fish approachequilibrium faster than fatter, larger fish. In the absence ofgrowth or biotransformation, regardless of size, fish will notreach the theoretical equilibrium for high log KOW testsubstances despite exposure periods that span several months.For such chemicals, reliable BCFs are best derived fromkinetic analysis of uptake and depuration phases, as theempirical determination of steady-state BCF would beimpractical because of time constraints and cost consider-ations. Figure 3 also highlights the influence that growthdilution and biotransformation processes play in alteringaccumulation kinetics and resulting BCF test results. Forsubstances that have relatively high rates of biotransformation(e.g., KM � 0.1/d), steady-state is approached within a 2-wkexposure period, independent of fish growth, lipid content, orthe log KOW value of the test substance.

DATA QUALITY CONSIDERATIONS IN ASSESSING INVIVO FISH DIETARY BIOACCUMULATION STUDIES

While the previous sections focused on bioconcentrationstudies, many of those considerations also apply to the dataquality evaluation of laboratory dietary bioaccumulation tests.Data from dietary exposure tests offer a number of practicaladvantages over BCF tests, particularly for more hydrophobicchemicals. These data may be used to calculate a biomagni-fication factor (BMF), which is defined as the concentrationratio of test substance in fish tissue at steady state to that in

Figure 3. Predicted time for fish to accumulate 90% of steady-state concentrations in bioconcentration studies with different-size fish, growth scenarios, andbiotransformation rate assumptions. Small and large fish are assumed to have a 3% and 8% lipid content, respectively. Further assumptions and equationsused for these calculations are explained in the text.


the administered diet. If expressed on a lipid-normalizedbasis, substances that exhibit a BMF above 1 may undergobiomagnification, while substances with a BMF below unityexhibit may exhibit trophic dilution in ecosystems. Exper-imental elimination rate data derived from these studies canalso be combined with allometric equations for estimating theuptake clearance (K1), as described earlier, to estimate a BCFfor a tested chemical (Peterson and Parkerton 2004).Furthermore, data derived from laboratory dietary bioaccu-mulation tests provide key inputs for improved calibration offood chain models that predict BAF.

Ad libitum feeding should be avoided. Rather, a fixedfeeding ration, expressed as a fraction of the body weight perday, should be administered throughout the uptake phase ofthe test. Flow-through exposure conditions should be used indietary studies to prevent accumulation of organic carbon inwater that can influence elimination kinetics (Lotufo andLandrum 2002). Additional considerations for dietary studiesare the quality and quantity of the administered diet and thefood spiking method, which can yield differences in uptake ofthe test substance (Clark 1990; Sijm et al. 1993). To ensurethat the spiking method used to dose the feed is appropriate, apositive control such as hexachlorobenzene can be added tothe diet and also analyzed in the fish and the accumulatedamounts compared across subsequent studies. Regardless ofpotential differences in the assimilation efficiency of thepositive control and test substance, the experimental elimi-nation rate (and hence estimated BCF) derived from thedepuration phase of the study should not be influenced byspiking methods.

Similar to aqueous bioconcentration studies, exposureconcentrations in the dietary tests could influence test results.Concentrations in the diet, if too high, could overwhelm thecapacity of biotransformation enzymes and thus overstatebioaccumulation and/or cause toxicity. High test substanceconcentrations might also cause decreased bioavailability,resulting in an underestimate of assimilation efficiency andBMF. Based on limited experience from unpublished studies,dietary concentrations above 1000 mg/kg should be avoidedfor substances exhibiting a nonspecific mode of toxic action.For specifically acting substances (e.g., biocides), much lowerdietary concentrations may be required to avoid adverseeffects. Further work is needed to better standardize dietarybioaccumulation testing and evaluate the extrapolation ofsuch data for BCF estimation before additional guidance forquality assessment can be provided.

PROPOSED CRITERIA FOR INITIAL SCREENINGBased on the previous considerations, data quality screening

criteria are proposed in Table 2. These criteria are intended torapidly identify ‘‘poor quality’’ studies so that a more detailedreview can be directed to studies of potential ‘‘higher quality.’’This pragmatic strategy has been adopted in the HPV testprogram (OECD 2004).

Subsequent evaluation of the reliability and adequacy ofstudies that are not rejected via initial screening will dependon the specific objectives of the assessor.

If data from multiple tests are available, a weight-of-evidence approach should be taken giving greater weight tostudies that are the deemed reliable for the intended purpose.We conclude this paper with a practical application of theguidance presented previously to 2 chemicals with consid-erable laboratory fish bioconcentration data. In the case

studies presented here, we define a reliable study as havingthe following attributes: steady-state BCF based on parentsubstance, exposure duration of more than 4 d, reportedexposure concentrations that do not vary by more than afactor of 3, and no unacceptable reported mortality. Studiesthat did not meet these criteria or did not provide sufficientinformation to assess these criteria were designated as‘‘reliable with restrictions’’ or ‘‘not assignable’’ as previouslydiscussed.

CASE STUDIESKey properties relevant to bioconcentration assessment of

these substances are provided in Table 3.

Anthracene

Anthracene has a measured aqueous solubility that is 10-fold lower than predicted QSPR estimates (Table 3). Giventhe log KOW value for this substance and in the absence ofmetabolism, Figure 3 indicates that steady state will beapproached within 4 d for a 1-g fish and after 24 d for a 100-gfish. Under non–flow-through exposure conditions, volatili-zation may pose a significant loss process (cf. river predictionsin Table 3) that reduces aqueous exposure concentrations.Biodegradation is expected to be negligible under the BCFtest conditions. Photodegradation and photoenhanced tox-icity, while key fate processes under field conditions in thepresence of ultraviolet light, are expected to be less significantunder laboratory lighting conditions, which are often selectedto minimize photoactivation processes.

Fifteen bioconcentration studies were identified for anthra-cene, including 10 fish species (Table 4). All studies wereperformed at concentrations near or below the reportedaqueous solubility of anthracene. While only 1 studyspecifically reported observed mortality over the exposureperiod, acute toxicity is not expected to occur at the solubilitylimit of this compound. Three studies were judged ‘‘notreliable.’’ In the study by Linder and Bergman (1984), theexposure duration was too short to reflect steady-stateconditions. In the study by de Maagd (1996) using theadjusted Banerjee method, a poor mass balance in the statictest system was reported. This study was deemed ‘‘notreliable’’ because of the poor mass balance coupled with theshort, decreasing exposure concentration and limited numberof fish tissue samples. The study by Oris and Giesy (1987)

Table 2. Guidance for identifying ‘‘not reliable’’ laboratorybioaccumulation studies

Study element Criteria for rejection

Species information Organism not specified

Substance IDUnclear nature oftest substance

Substance determinationSubstance analysis not per-formed in both exposuremedium and fish tissue

Test conditionsSignificant mortality (orgrowth effects) in treat-ment or control fish

Test endpointAmbiguous units or non–steady-state BCF value


was considered ‘‘not reliable’’ on the basis of ambiguous BCFunits because it was unclear if results were based on dry- orwet-weight fish concentrations. Eleven studies were consid-ered ‘‘not assignable’’ because BCFs were reported on thebasis of total radioactivity with no parent-specific analysis,experimental details were missing (e.g., magnitude andvariance of exposure concentrations), or exposures were tooshort to determine if reliable steady-state BCF values werereported. Two studies were judged ‘‘reliable with restrictions’’given that parent substance–specific analysis was performedand test conditions likely yielded steady-state conditions. Thestudy involving carp was an OECD 305 guideline study thatinvolved long-term, flow-through exposure conditions, andthe variation in measured exposure concentrations was notreported (CITI 1992). The study involving fathead minnowinvolved long-term, flow-through exposure conditions,although the lipid content was not reported (Hall and Oris1991).

Excluding the not reliable studies listed in Table 4, total andparent BCFs in fish expressed on a wet-weight basis foranthracene range from 190 to 9200 (48-fold) and 162 to 7260(45-fold), respectively. If the subset of these studies for whichlipid data were also reported is considered, the range of BCFvalues is 860 to 4033 (,5-fold) if adjusted to a 5% lipidcontent. Thus, in this case, lipid normalization helps to reducethe variability of reported fish BCFs between studies and testspecies. Using only BCF data from studies that wereconsidered to be ‘‘reliable with restrictions’’ reduced therange of parent BCFs to 1870 to 3725 (,2-fold). Twolaboratory dietary bioaccumulation studies have also beenconducted for anthracene using rainbow trout. In the firststudy, a growth-corrected parent substance half-life of 7 d(corresponding to a 1st-order elimination rate¼ 0.099/d) wasreported for fish weighing 850 g (Niimi and Palazzo 1986).With a test temperature of 11 8C and lipid content of 9.5%reported in earlier experiments (Niimi and Oliver 1983) and

Table 3. Properties relevant to bioaccumulation test design and evaluationa

Test substance name Anthracene2,3,7,8-Tetrachlorodibenzo-p-dioxin

(TCDD)

CAS RN 120-12-7 1746-01-6

Structure

Water solubility (lg/L)

12.7 (measured at 5.0 8C)

17.5 (measured at 10.0 8C)

22.2 (measured at 14.1 8C) 0.013 (measured at 4.3 8C)

28.1 (measured at 18.3 8C) 0.483 (measured at 17.3 8C)

37.2 (measured at 22.4 8C) 0.008–0.317 (measured at 25.0 8C)

43.4 (measured at 24.6 8C) 1.1–3.8 (predicted at 25 8C )

690–959 (predicted at 25 8C)

Log KOW 4.45 (measured) 6.80 (measured)

4.35 (predicted) 6.92 (predicted)

River model15.4 22.8

Volatilization half-life (h)

Survey modelWeeks Weeks

Primary biodegradation

BCFWIN v.2.15Fish BCF (wet-weight basis)

533 34360

Acute fish LC50 (lg/L) . Water solubilityb 0.0019 (28 d)c

Henry’s Law constant (atm�L�mole�1) .5 2.4a Predicted values were obtained using EPISuite v.3.12, with the exception of measured water solubility data, which were taken fromMackay et al. (2006a, 2006b), and acute fish toxicity data as cited.

b Oris et al. (1984).c Adams et al. (1986).


Table

4.Example

data

qualityreview

summary

ofanthracenebioco

ncentrationstudies

Chemical

purity

(%)

Exp

osu

retypea

Water

analysisb

Tissue

analysisb

Test

phasesc

Weight

(gwet)

Lipid

(%)

Temp.(8C)

Exp

osu

reco

ncn

.(lg/L)

Exp

osu

reduration(d)

TotalBCF

(wet)

ParentBCF

(wet)

Reference

sdStu

dy

reliabilitye

Carassiusauratus(goldfish)

NR

NR

AA

U2

NR

NR

NR

NR

—162

a4

LeuciscusIdusmelanotus(golden

orfe)

98

SB

BU

1.5

NR

20–2

526

3910

—b

4

Brach

ydanio

rerio(zeb

rafish)

93

SB

BU

0.22

NR

20

62

11.8

623

30

229f

—c

4

Gambusiaaffins(m

osq

uitofish)

.99.9

SA,B

A,B

UNR

NR

26

61

NR

33

2130

1029

d4

Onco

rhyn

chusmykiss(rainbow

trout)

98

SB

A,B

U10.2

NR

13

61

36!

91.25

190–2

70g

184–2

62g

e3

98

SR

BB

U/D

10

NR

12

60.5

NR

39000–9

200

—f

4

Lepomis

macroch

irus(bluegill

sunfish)

97.4

SB

A,B

U/D

0.35

NR

23–2

40.7

0.25

900

675

g4

High

FTA

AU

0.75

NR

22

NR

2—

1369

h4

Poecilia

reticu

late

(guppy)

.96

SA

AU

0.13

923

40!

72

—7260

i4

.96

SR

AA

U/D

0.13

923

;40

4—

4500

I4

Pim

ephalespromelas(fathea

dminnow)

High

SR

AA

ULarvae

NR

24

61.5

6.6,13.1,19.1

1—

1016

6116

j4

High

FTA

AU

Adults

NR

25.8

61.1

11.6

60.5

21

—2354h

k2

High

FTA

AU

Adults

NR

25.8

61.1

20.1

63.5

21

—3725h

k2

High

SR

AA

ULarvae

NR

24

5.4

4—

3869

l3

.99

SA

AU

0.52

NR

20

61

7!

0.5

2—

6760

m3

Cyp

rinuscarpio

(carp)

NR

FTA

AU

30

525

62

1.5

56

—1870

n2

NR

FTA

AU

30

525

62

15

56

—2240

n2


assuming a dissolved oxygen and organic carbon concen-tration of 8 and 1 mg/L, respectively, Equation 1 can be usedto estimate the uptake clearance. The estimated clearancedivided by a measured 1st-order elimination rate yields a BCFof 681, adjusted to a standardized 5% lipid content. In a 2ndstudy, a parent substance growth-corrected half-life of 0.6 d(1st-order elimination rate ¼ 1.15/d) was reported for troutweighing 0.9 g (ExxonMobil Biomedical Sciences Inc. 2005).Given these data and the reported test temperature of 13 8Cand a measured lipid content of 2.3%, an estimated BCF of1038 is derived using the same approach when adjusted to 5%lipid content. Thus, BCF values estimated from 2 indepen-dent dietary bioaccumulation studies with anthracene andrainbow trout are consistent and within the range of lab-measured BCFs (Table 4).

This critical evaluation process can provide greater mech-anistic understanding of bioaccumulation processes, not justBCF values. For example, the collective dietary and water-borne exposure data suggest that turbot and rainbow troutmight have higher biotransformation rates than guppiesbecause, despite adjustment for lipid differences, turbot andtrout steady-state BCFs are lower by 3-fold. This systematicreview also suggests BCFWIN v.2.15 (Table 3) may under-estimate the bioconcentration potential for anthracene insome fish species when compared to measured data that areadjusted to 5% lipid content. Moreover, because the simpletheoretical prediction obtained by multiplying the assumedlipid fraction by the octanol–water partition coefficient (0.053 104.45¼1409) falls within the range of these measured data,this indicates the limited role of biotransformation relative topassive elimination processes for this test substance in somefish species.

2,3,7,8-Tetrachloro-p-dioxin

Measured aqueous solubility values for 2,3,7,8-tetrachloro-p-dioxin (TCDD) are highly variable and appear to be below1 lg/L, as predicted by QSPR models. Given a measured logKOW of 6.8, Figure 3 indicates that steady state in exposedorganisms will be approached in about 100 d for both 1-g and100-g fish, assuming reasonable experimental growth ratesand lipid content but no TCDD metabolism. As in the case ofanthracene, volatilization may pose a significant loss processreducing aqueous exposure concentrations, while biodegra-dation is not expected to be a significant loss process. Thehigh and nonreversible nature of chronic TCDD fish toxicityis a critical concern and potential confounding factor in theinterpretation of bioaccumulation data for this substance.

Ten bioconcentration studies were identified for TCDDthat included 8 fish species (Table 5). Most studies wereperformed at concentrations well below the reported aqueoussolubility of TCDD, presumably in an attempt to avoid fishtoxicity. However, BCFs reported in several studies werecategorised as ‘‘not reliable’’ because of significant testorganism mortality (.30%) that appeared to be TCDDrelated (Mehrle et al. 1988; Kim and Cooper 1999). In thestudy by Isensee and Jones (1975), the exposure duration wastoo short to reflect steady-state conditions. Five studies wereconsidered ‘‘not assignable’’ because BCFs were reported onthe basis of total radioactivity with no parent-specific analysis(Branson et al. 1985; Adams et al. 1986; Schmieder et al.1992; Kim and Cooper 1999) or it was unclear if steady statewas attained (Sijm 1992). The study by Cook et al. (1991)was judged ‘‘reliable with restrictions’’ because flow-throughTa

ble

4.Continued

.

Chemical

purity

(%)

Exp

osu

retypea

Water

analysisb

Tissue

analysisb

Test

phasesc

Weight

(gwet)

Lipid

(%)

Temp.(8C)

Exp

osu

reco

ncn

.(lg/L)

Exp

osu

reduration(d)

TotalBCF

(wet)

ParentBCF

(wet)

Reference

sdStu

dy

reliabilitye

Sco

phthalm

usmaximus(turbot)

NRi

FTA

AU

10

3.4

20

61

;0.08

21

—585

o4

aS¼static;

SR¼

staticrenew

al;FT¼

flow-through.

bA¼

parent-sp

ecific

method;B¼

non–p

arent-sp

ecific

method.

cU¼

uptake

phase;D¼

dep

urationphase.

da:Ogata

etal.1984;b:Freitaget

al.1982;c:

Djomoet

al.1996;d:Lu

etal.1978;e:

Linder

andBergman1984;f:Linder

etal.1985:g:Spacieet

al.1983;h:OrisandGiesy

1985;i:deVoogtet

al.

1991;j:Oriset

al.1990;k:

HallandOris1991;l:OrisandGiesy

1987;m:deMaagd1996;n:CITI1992;o:Baussant,Sanni,Jonsson,et

al.2001.

e2¼

relia

ble

withrestrictions;

3¼

notrelia

ble;4¼

notassignable;NR¼

notreported

.fMaximum

bioco

ncentrationfactor(BCF)

after

1d;reported

BCFafter

30dwas42.

gEviden

ceofnon–steadystate

reported

.hAverageofmale

andfemale

carcass

BCFs.

iAnthracenedosedviamulticomponen

toilmixture.


Table

5.Example

data

qualityreview

summary

of2,3,7,8-tetrach

loro-p-dioxin(2,3,7,8-TCDD)bioco

ncentrationstudies

Chemical

purity

(%)

Exp

osu

retypea

Water

analysisb

Tissue

analysisb

Test

phasesc

Weight

(gwet)

Lipid

(%)

Temp.(8C)

Exp

osu

reco

ncn

.(ng/L)

Exp

osu

reduration(d)

TotalBCF

(wet)

ParentBCF

(wet)

Reference

sdStu

dy

reliabilitye

Gambusiaaffinis(m

osq

uitofish)

NR

SB

BU

NR

NR

NR

1330

3f

200

—a

3

SB

BU

NR

NR

NR

239

31840

——

3

SB

BU

NR

NR

NR

48

32260

——

3

SB

BU

NR

NR

NR

18

34660

——

3

SB

BU

NR

NR

NR

73

2580

——

3

SA,B

A,B

UNR

NR

NR

7.1

312320

12362

—3

SA,B

A,B

UNR

NR

NR

0.66

312660

12471

—3

SB

BU

NR

NR

NR

0.26

34540

——

3

SB

BU

NR

NR

NR

0.05

34800

——

3

Ictaluruspunctatus(channel

catfish)

NR

SB

BU

NR

NR

NR

239

6f

600

—a

3

SB

BU

NR

NR

NR

48

6460

——

3

SB

BU

NR

NR

NR

18

61340

——

3

SB

BU

NR

NR

NR

76

2280

——

3

SA,B

A,B

UNR

NR

NR

76

2880

2920

—3

SA,B

A,B

UNR

NR

NR

0.66

65580

5843

—3

SB

BU

NR

NR

NR

0.26

6920

——

3

SB

BU

NR

NR

NR

0.05

6400

——

3

NA

Carassiusauratus(goldfish)

(flyash)g

SA

AU/D

;4

0.5

NR

0.59!0.43

0.33

—24547

b,c

4

NA

Poecilia

reticu

lata

(guppy)

(flyash)g

FTA

AU

0.8

8.0

25

0.08

60.02

21

—13902

d4

Onco

rhyn

chusmykiss(rainbow

trout)

NR

SA,B

A,B

U/D

35

NR

10–1

3107

67

0.25

9270h

e4

.99

FTA,B

A,B

U/D

0.38

NR

11

0.038

60.005

28

;55714

39000i

f3

FTA,B

A,B

U/D

0.38

NR

11

0.079

60.015

28

—37560i

—3


Table

5.Continued

.

Chemical

purity

(%)

Exp

osu

retypea

Water

analysisb

Tissue

analysisb

Test

phasesc

Weight

(gwet)

Lipid

(%)

Temp.(8C)

Exp

osu

reco

ncn

.(ng/L)

Exp

osu

reduration(d)

TotalBCF

(wet)

ParentBCF

(wet)

Reference

sdStu

dy

reliabilitye

FTA,B

A,B

U/D

0.38

NR

11

0.176

60.042

28

—86000i

—3

FTA,B

A,B

U/D

0.38

NR

11

0.382

60.101

28

—36637i

—3

Pim

ephalespromelas(fathea

dminnow)

SR

BB

U/D

0.5–1

.0NR

21–2

31.00

60.22

28

7900

—g

4

FTA

AU/D

1.0

5.3

25

0.049

71

—97000

h2

FTA

AU/D

1.0

5.3

25

0.067

71

—159000

h2

Cyp

rinuscarpio

(carp)

FTA

AU/D

1.0

5.5

25

0.057

71

—89000

h2

FTA

AU/D

1.0

8.5

25

0.061

71

—64000

h2

FTA

AU/D

1.0

9.6

25

0.067

71

—49000

h2

Oryziaslatipes(Japanese

med

aka

)

SB

BU/D

0.02

NR

25

1.78

60.06

45516j

—i

4

SB

BU/D

0.02

NR

25

2.75

60.06

47548i

—i

3

SB

BU/D

0.02

NR

25

3.67

60.09

47560i

—i

3

FTB

BU/D

0.175

825

0.110

12

344000h

—j

4aNR¼notreported

S¼

static;

SR¼

staticrenew

al;FT¼

flow-through.

bA¼p

arent-sp

ecific

method;B¼

non–p

arent-sp

ecific

method.

cU¼

uptake

phase;D¼

dep

urationphase.

da:Isen

seeandJones

1975;b:Sijm

etal.1989;c:

Sijm

1992;d:Lo

onen

etal.1994;e:

Bransonet

al.1985;f:Meh

rleet

al.1988;g:Adamsetal.1986;h:Cooketal.1991;i:Kim

andCooper

1999;j:

Sch

mieder

etal.1992.

e2¼

relia

ble

withrestrictions;

3¼

notrelia

ble;4¼

notassignable.

fExp

osure

periodexpectedto

reflectnon–steady-state

conditions.

g2,3,7,8-TCDD

dosedviaflyash

extract.

hRep

orted

BCFvalues

wereco

rrectedforgrowth

dilu

tion.

iSignificantmortalityreported

duringtest.

jSteady-state

bioco

ncentrationfactor(BCF)

calculatedfrom

reported

6-d

BCFs

andelim

inationhalf-lives

assumingfirst-order

kinetics.


exposure conditions were used, parent substance–specificanalysis was performed, and test conditions likely yieldedsteady-state conditions. It was also noted that no attempt wasmade to correct for growth dilution because of the largevariation of chemical concentrations in, and general wastingof, fish during the depuration phase as a result of TCDDexposure. As a result, preference should be given to the BCFvalues derived from the lowest exposure concentration in thisstudy. While Sijm et al. (1993) involved only an 8-h uptakephase, this study included a 17-d depuration phase thatenabled a steady-state BCF to be derived. No attempt tocorrect for growth dilution was mentioned in this studydespite the fact that fish were fed clean food during thedepuration period.

Based on all data except those studies deemed ‘‘notreliable’’ (Table 5), total and parent BCFs for TCDD rangefrom 5516 to 344000 (62-fold) and 13902 to 159000 (11-fold), respectively. Using only BCF data from studies thatwere considered to be ‘‘reliable with restrictions,’’ BCF valuesfall within a factor of 2 if adjusted to a standardized 5% lipidcontent, that is, 91509 (fathead minnow) and 80909 (carp). Itis interesting to note that the lipid-adjusted BCF value of215000 for the 12-d flow-through test with medaka based ontotal radioactivity is about a factor of 2 higher. In contrast,reported BCFs based on total radioactivity of 5516, 7900, and9270 for medaka, fathead minnow, and trout, respectively,appear to understate the bioconcentration potential of TCDD(Branson et al. 1985; Adams et al. 1986; Kim and Cooper1999). While BCFs based on total radioactivity are usuallyassumed to overestimate the bioconcentration potential ofparent test substance, the low BCFs cited previously wereunexpected and are likely explained by the static exposuredesign employed in these studies. Under these test conditions,organic carbon in the water is expected to increase with timebecause of diet and fish waste. Complexation of TCDD toorganic carbon will reduce the bioavailability of thissubstance, thereby lowering the experimentally derivedBCF. These findings support our earlier recommendationthat bioconcentration studies conducted with hydrophobictest substances under static exposure conditions must beinterpreted with caution.

A laboratory dietary bioaccumulation study for TCDD isavailable in which half-lives of 77 and 34 d were reported forrainbow trout and whitefish, respectively (Fisk et al. 1997).Given a fish weight of 9 g, a test temperature of 10 8C, andlipid content of 6.2% and using the same assumptions fordissolved oxygen and organic carbon concentrations asdescribed previously, application of Equation 1 yields anestimated BCF for trout of 26249 if adjusted to a 5% lipidcontent. This value is within a factor of 2 of the aqueous BCFsreported for rainbow trout by Mehrle et al. (1988), providingevidence that the .20% mortality observed in this study maynot have impacted the validity of the BCFs reported. Given aweight of 8 g and lipid content of 8.4% for whitefish, a BCFvalue of 8754 is similarly derived when adjusted to a 5% lipidcontent. This value is approximately 10-fold lower than theaqueous BCFs judged reliable, suggesting that differences maybe related to species-specific metabolism. Thus, whitefish andtrout appear to have higher metabolic biotransformation ratesfor TCDD than carp and fathead minnows.

This critical review indicates that the BCF prediction fromBCFWIN v2.15 falls within the range of experimentallyderived estimates. In contrast, the simple theoretical pre-

diction based on equilibrium partitioning using the octanol–water partition coefficient (0.05 3 106.8 ¼ 315479), whichignores the mitigating influence of reduced bioavailability andbiotransformation, is well above the reported upper range ofmeasured BCF data. The limitation of using octanol–waterpartition coefficient to estimate the BCF for TCDD isconsistent with previous literature indicating that the linearrelationship between these 2 parameters breaks down forhydrophobic substances above a log KOW of approximately 6(Gobas et al. 1989; Bintein et al. 1993).

SUMMARYA method to conduct a preliminary quality screening of

laboratory bioaccumulation data is recommended. Studiesthat 1) do not clearly specify the test substance or test species,2) fail to include measured concentrations in both exposuremedium and fish tissue, 3) involve significant (e.g., .20%)test organism mortality, or 4) do not report bioconcentration(or dietary biomagnification) factors that reflect steady-stateconditions should generally be regarded as ‘‘not reliable’’ fordecision-making purposes and/or QSPR model development.Additional considerations associated with the specific detailsof study conduct and design that must be taken into accountwhen assessing the reliability of reported in vivo fishbioaccumulation studies have been described. Relationshipshave also been provided to conservatively estimate theexposure duration required to approach steady-state con-ditions based on test substance hydrophobicity, organismweight and lipid content, and test temperature. Particularcaution must be exercised in the interpretation of BCF valuesderived using nonspecific analysis (e.g., total radioactivity) orshort-term transient exposure conditions such as the ad-justed-Banerjee test method. Application of this guidance toin vivo fish data for 2 data-rich substances demonstrated thepractical utility of a systematic data quality review, asvariability in reported BCFs (.50-fold) was significantlyreduced when data reliability and lipid normalization wereconsidered. Species-specific differences in biotransformationmay help explain the observed variation in reliable BCF valuesfor a given substance. Bioconcentration tests for very hydro-phobic substances under static exposure conditions may beconfounded by bioavailability limitations and should bejudged critically. Case studies also highlighted that dietarystudies can provide useful in vivo test data for assessingbioaccumulation potential. Use of guidance presented in thispaper will foster more consistent QSPR models, improveconduct and reporting of future laboratory studies, andstrengthen the technical basis of decision making in bio-accumulation assessment. Future research aimed at quantify-ing the importance of species differences is needed, and recentadvances in in vitro test methods appear well suited for thispurpose (Nichols et al. 2006; Han et al. 2007).

Acknowledgment—International Life Sciences Institute (IL-SI) Health and Environmental Sciences Institute (HESI) withsupport from the Society of Environmental Toxicology andChemistry (SETAC) funded the workshop from which thisreport resulted. We thank Karluss Thomas for coordinatingthe workshop and John Nichols, Tala Henry, and BramVersonnen for helpful comments on an early draft of thismanuscript. The information in this document has beenfunded in part by the US Environmental Protection Agency. Ithas been subjected to review by the National Health and


Environmental Effects Research Laboratory and approved forpublication. Approval does not signify that the contentsreflect the views of the Agency, nor does mention of tradenames or commercial products constitute endorsement orrecommendation for use.

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Documents

Guidance for Evaluating In Vivo Fish Bioaccumulation Data