Huggett a Theoretical Model for Utilizing Mammalian

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A Theoretical Model for Utilizing MammalianPharmacology and Safety Data to Prioritize PotentialImpacts of Human Pharmaceuticals to FishD. B. Huggett a , J. C. Cook a , J. F. Ericson a & R. T. Williams aa Pfizer Global Research and Development, Groton, Connecticut, USA

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To cite this article: D. B. Huggett, J. C. Cook, J. F. Ericson & R. T. Williams (2003): A Theoretical Model for UtilizingMammalian Pharmacology and Safety Data to Prioritize Potential Impacts of Human Pharmaceuticals to Fish, Human andEcological Risk Assessment: An International Journal, 9:7, 1789-1799

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November 24, 2003 11:33 Human and Ecological Risk Assessment TJ883-18

Human and Ecological Risk Assessment, 9: 1789–1799, 2003Copyright C© ASPISSN: 1080-7039 printDOI: 10.1080/10807030390260498

A Theoretical Model for Utilizing MammalianPharmacology and Safety Data to Prioritize PotentialImpacts of Human Pharmaceuticals to Fish

D. B. Huggett, J. C. Cook, J. F. Ericson, and R. T. WilliamsPfizer Global Research and Development, Groton, Connecticut, USA

ABSTRACTDue to the potential for long-term, low-level exposure of environmental species to

pharmaceuticals in the environment, concerns over chronic ecotoxicity have beenraised. Pharmaceuticals typically have specific enzyme and receptor-based modes ofaction, which are extensively studied in mammals during drug development. A surveyof the literature demonstrated that there is conservation of many enzyme/receptorsystems between mammalian and teleost systems. Based on this conservation ofenzyme/receptor systems across teleost species, a model has been developed to utilizethe information from mammalian pharmacology and toxicology studies to evalu-ate the potential for chronic receptor mediated responses in fish. In this model, ameasured human therapeutic plasma concentration (HTPC) is compared to a pre-dicted steady state plasma concentration (FSSPC) in fish, and an effect ratio (ER =HTPC/FSSPC) is computed. The lower the ER, the greater the potential for a phar-macological response in fish. Data collection and model validation will strengthenthe applicability of this approach as a viable tool for prioritizing research initiativesthat examine the potential impact of pharmaceuticals on fish.

Key Words: environmental assessment, pharmaceuticals, ecotoxicity, drug safety.

INTRODUCTION

The presence and potential hazards of pharmaceuticals in the aquatic environ-ment have received increased attention recently (Daughton and Ternes 1999;Kummerer 2001). This attention is largely the result of a growing number of peer-reviewed papers reporting trace levels of pharmaceuticals in municipal effluent, sur-face water, groundwater and to a lesser extent, drinking water. For instance, a nationalreconnaissance by the United States Geological Survey (USGS) detected 82 pharma-ceutical and personal care products in surface waters of the United States (Kolpinet al. 2002). While pharmaceuticals are being detected in the aquatic environment,

Received 11 November 2002; revised manuscript accepted 11 April 2003.Address correspondence to Duane B. Huggett, Pfizer Global Research and Development,Eastern Point Road, Mailstop 8118D-4050, Groton, CT 06340, USA. E-mail: duane [email protected]

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the levels are low and the science is generally not yet developed enough to determinewhether these low-levels pose a risk to environmental species.

Environmental hazard assessment frameworks based on an initial evaluation ofacute ecotoxicity endpoints have been developed to evaluate the potential impactof pharmaceuticals on aquatic species (FDA 1998; EMA 2001). The science of theseevaluations centers on: 1) the development of a predicted environmental concentra-tion (PEC) to estimate potential aquatic organism exposure, 2) determining acutetoxicity concentrations using algae, Daphnia sp. and fish, and 3) application of mul-tipliers (safety or assessment factors) to account for uncertainties such as inter- orintra-species variability or extrapolation from acute to chronic toxicity. Hazard as-sessment frameworks may trigger investigation of increasingly complex and difficultto measure chronic toxicity endpoints. Depending upon the properties of the drugunder investigation, these tiered evaluation frameworks may result in a conclusionthat no further action is required or the development of a detailed risk character-ization with recommendations for potential precautionary measures as needed. Inaddition, properties of the compound such as Log P and bioaccumulation potentialmay trigger chronic toxicity evaluation outside of the standard acute toxicity/safetyfactor framework.

Acute toxicity tests assess toxicity following short exposures (≤96 hr) using theprimary endpoint of death. Hence, these tests generally do not assess the potentialof a test substance to produce effects following chronic, low level exposures. Acutetoxicity of pharmaceuticals at environmentally relevant concentrations has beensuggested to not be a significant issue because the acute effects concentrations his-torically determined are generally well above predicted environmental levels (Webb2001). The biologically active nature of pharmaceuticals, however, has led someto suggest that aquatic organisms may be impacted in ways that are not being de-tected using current test methodologies and data evaluation strategies (Daughtonand Ternes 1999).

The mammalian nonclinical safety profile developed to support registration ofa pharmaceutical and use in a patient population is based on data from a seriesof in vitro and in vivo studies (Table 1). In vitro studies may be used to determinekey characteristics of a pharmaceutical such as metabolism and stability, bioavailabil-ity, mutagenicity and other selected endpoints (e.g., toxic effects to specific tissues).In vivo safety studies are typically performed in rodent and non-rodent animal speciesusing standard, non-clinical toxicology study designs and the intended clinical dos-ing route. A battery of genotoxicity tests are also conducted. Safety pharmacologystudies are conducted to evaluate potential adverse effects at high dosages of thedrug on critical organs such as the heart, lungs, brain, and other organ systems basedon the pharmacology of the drug. The safety assessment studies typically increasein duration as development of a drug continues. Testing includes acute throughsub-chronic (up to three month) studies in two species prior to Phase I clinical in-vestigation, where initial human exposure in small populations of healthy subjectsoccurs.

In conjunction with the progressive phases of clinical development, non-clinicalstudies of increasing duration are performed. During Phase II clinical trials, fertility,developmental toxicity, and pre/postnatal studies (commonly referred to as Seg-ments or Studies I-III) are conducted to assess the safety of the drug in women of

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Environmental Safety of Pharmaceuticals

Table 1. Summary of pharmacology and toxicology studies conducted to supportdrug registration.

Test Test System / Species

Pharmacology tests to establish activity In vitro and in vivo studies based on target systemGenotoxicity Ames, In vitro/In vivo cytogeneticsSafety pharmacology CNS (rat) pulmonary (rat), renal (rat),

cardiovascular (rat, primate), gastricemptying (rat)

Absorption, distribution, excretionand metabolism (ADME)

Rat, dog/primate

Acute toxicity Rat, dog/primateSub-chronic toxicity (1-3 months) Rat, dog/primateChronic toxicity 6-month rat, 9-12 month dog/primateCarcinogenicity Mouse, ratFertility RatDevelopmental toxicity Rat, rabbitPre/Postnatal toxicity RatJuvenile animal Rat, dog

Source: USFDA 2002.

child bearing potential and chronic studies (6-month duration in rodent, one-yearduration in non-rodent) are conducted to assess safety during long-term use. Dur-ing Phase III, carcinogenicity studies are conducted in mice and rats if the drug isintended for chronic usage in patients.

In many ways, fish are not that biochemically different from mammals. Aquaticvertebrates appear to have very similar enzyme and receptor systems as humans(Table 2) (Evans 1993). The National Institutes of Health recognize the zebrafish(D. reno) as a biomedical model to elucidate an understanding of vertebrate devel-opment and disease (NIH 2002). A large number of receptors in fish have beenidentified through cloning and sequencing techniques in both the central and pe-ripheral organs of fish (Table 2). Sequence homologies for receptors and enzymesin fish range from 31 to 88 %. For example, β-adrenergic receptors, peroxisome pro-liferation activated receptors (PPAR γ ), and serotonin receptors (5-HT) have beenidentified in representative fish species with sequence homologies of 63, 47 and72%, respectively (Nickerson et al. 2001; Yamaguchi and Brenner 1997; Andersenet al. 2000). Since fish have many similar enzyme and receptor systems, this poten-tially makes them susceptible to similar biochemical and physiological mechanismsof activation/inactivation. Because of the conservation of enzyme and receptor sys-tems between mammals and these fish, chronic and target organ toxicity identifiedin mammalian safety assessments is likely to be useful in predicting the need foradditional toxicity evaluation in teleosts.

While reports indicate that vertebrates may have receptors similar to those in hu-mans (Evans 1993), the data set for invertebrates is much more limited. In addition,receptor and enzyme systems in invertebrates may be structurally similar to those inmammals, but be physiologically distinct with regard to functionality. For instance,17α-ethinyl estradiol regulates ovarian activity in mammals, but it does not appearto elicit aquatic invertebrate reproductive responses through arthropod hormonal

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Table 2. Summary of select receptor and enzyme expression in teleost species.

System Species Homology1 Reference

Receptor2

PPARγ S. salar 47 Andersen et al. 2000ERα/ERβ D. rerio 47/47 Menuet et al. 2002AR P. major 45 Touhata et al. 19995-HT1A/5-HT1D F. rubripes 72/71 Yamaguchi and Brenner 1997β2-adrenoceptor O. mykiss 63 Nickerson et al. 2001A1A-adrenoceptor O. latipes 61 Yasuoka et al. 1996NMDA (NR1 subunit) A.leptorhychus 88 Dunn et al. 1999GlyR (α subunit) D. rerio 77 David-Watine et al. 1999GluR (R3 subunit) Oreochromis 87 Chang et al. (1998)IGF D. rerio 63 Maures et al. 2002IR Salmon 83 Chan et al. 1997AH D. rerio 43 Andreasen et al. 2002OR1 D. rerio 66 Rodriguez et al. 2000NPY Cod 50 Sharma et al. 1999BK2 D. rerio 35 Duner et al. 2002IL1 S. salar 31 Subramaniam et al. 2002GnRH O. mykiss 45 Madigou et al. 2000FSH I. punctatus 53 Kumar et al. 2001LH I. punctatus 47 Kumar et al. 2001bTSH M. saxatilis 57 Kumar et al. 2000GH C. auratus 42 Lee et al. 2001RARα F. rubripes 58 Wentworth et al. 1999SST C. auratus 62 Lin et al. 2000

EnzymeLipoprotein Lipase O. mykiss 56 Lindberg and Olivecrona 2002P450 1beta-hydroxylase O. mykiss 33 Kusakabe et al. 2002COX D. rerio 67 Grosser et al. 2002P450 Aromatase D. labrax 50 Valle et al. 2002Creatine Kinase D. rerio 86 Dickmeis et al. 2001.Caspase-3 D. rerio 60 Yabu et al. 2001Stearoyl-CoA desaturase C. chanos 63 Hsieh al. 2001ADH D. rerio 81 Dasmahapatra et al. 2001iNOS O. mykiss 62 Wang et al. 2001AChE D. rerio 62 Bertrand et al. 2001

1Percent Homology to Mammalian Receptor/Enzyme.2 PPAR = peroxisome proliferator activated receptor, ER = estrogen receptor, AR = androgenreceptor, 5-HT = serotonin receptor, B-AR = beta adrenoceptor, A-AR = alpha adrenocep-tor, NMDA = N-methyl-D-aspartate receptors, GlyR = glycine receptor, GluR = glutamatereceptor, IGF = insulin like growth factor, IR = insulin receptor, AH = aryl hydrocarbon,OR = opiate receptor, NPY = neuropeptide Y, BK = bradykinin, IL = interleukin, GnRH =gonadotropin releasing hormone, FSH = follicle stimulating hormone, LSH = leutinizinghormone, TSH = thyroid stimulating hormone, GH = growth hormone, RAR = retinoicasid receptor, SST = somatostatin , COX = cyclooxygenase, ADH = alcohol dehydrogenase,iNOS = inducible nitric oxide synthase, AChE = acetylcholinesterase.


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systems (Hutchinson 2002). As another example, HMG-COA reductase is an im-portant enzyme in invertebrate juvenile hormone production, compared to being amediator in cholesterol formation in mammals (Debernard et al. 1994). The mostextensive comparative dataset with the best homology exists between mammals andfish (Table 2). Therefore, use of this model to target areas worthy of additional studyinitially should be limited to fish.

The purpose of this paper is to present a theoretical model which utilizes the ex-tensive scientific and mechanistic understanding of pharmaceuticals in mammaliansystems to aid in prioritizing which pharmaceuticals may require additional chronicecotoxicity testing in teleosts. The premise for the model described in this paper isthat the drugs with the highest potential for additional chronic testing in fish arethose where the anticipated plasma concentration in fish approaches the plasma con-centration in humans at which therapeutic effects are observed. It is assumed thata pharmacological response would occur prior to a toxicological response, due tothe specificity of a compound for its respective target. Much like in human pharma-cology, the dose determines the response, whether it be pharmacological or toxico-logical. Therefore, a receptor/enzyme mediated therapeutic response in non-targetorganisms may be viewed as a precursor or surrogate response when compared totraditional toxicological effects (survival, growth, or reproduction).

The European Agency for the Evaluation of Medicinal Products guidance on envi-ronmental risk assessment for medicinal products (EMA 2001) specifically requiresthat the assessment utilize toxicology, mechanism of action, and other informationprovided in the marketing application to determine if there is any potential for ad-verse ecotoxicological effects. This model is not intended to change the conditionsthat trigger an environmental assessment for pharmaceuticals either in the UnitedStates or Europe. However, with validation and further development, the model hasthe potential to be a valuable component of the environmental impact assessmentprocess.

MODEL DESCRIPTION

The key assumption for the model is that many receptors and enzyme systemsare conserved across mammalian and non-mammalian species, thus making mech-anism of action extrapolations possible (Table 2). The model requires comparisonof human and aquatic vertebrate plasma concentrations for a given pharmaceuti-cal. Ideally, the model would be based on the highest human plasma steady stateconcentration measured that corresponds to a No Observable Effect Concentration(NOEC). Such a human plasma concentration at the NOEC (HSSPC NOEC) fora given pharmaceutical could then be compared to a measured fish steady stateplasma concentration (FSSPC ) derived from an environmental exposure. If thesedata were available, the ratio of these two plasma concentrations could be expressedas a plasma based margin of safety:

Margin of SafetyPB = HSSPC NOEC/FSSPC

Ideally, anthropogenic compounds would have a margin of safety that is as large aspossible. Unfortunately, drug levels in humans and/or mammalian test species are


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traditionally reported at the recommended human dose rather than at the NOEC.As would be expected, there is a very limited amount of published steady state fishplasma data for pharmaceuticals linked to an actual aqueous exposure. These twosituations of limited data availability mean that this margin of safety approach forcomparing human and environmental species plasma levels is currently not feasible.

As an alternative to the margin of safety approach, an effect ratio (ER) can becalculated (Figure 1). The human therapeutic plasma concentration (HTPC) at themaximum dose of a drug is commonly available and can be utilized instead of aHSSPC NOEC. For the fish plasma level, a predicted or measured environmentalconcentration can be used in conjunction with its respective Log Kow to calculate aFSSPC. These values can then be used to derive an ER:

ER = HTPC/FSSPC

As in the case with a margin of safety, the ER ratio would ideally be as large as possibleunder environmental exposure conditions. An ER ≤ 1 indicates that the predicteddrug concentration in the fish plasma is equal to or greater than the drug concen-tration in human plasma that elicits a therapeutic effect. This plasma concentrationrelationship would indicate that there is a potential for receptor mediated responsesin fish, especially if the target enzyme or receptor is expressed in the fish. Therefore,the lower the ER, the greater the potential need for additional chronic investigationin fish. Conversely, if the ER > 1 then the predicted fish plasma drug concentrationis less than the human therapeutic plasma drug concentration, indicating a lowerlikelihood of receptor mediated responses in fish.

HTPC Derivation

Human therapeutic plasma concentrations (HTPC) are determined as a standardpart of the drug development process and are expressed as Cmax (maximum con-centration) or AUC (area under the curve) values. HTPC describes the presence ofa drug in the systemic circulation system at either a single point in time (Cmax) oras a function of time (AUC) (Hardman et al. 1996). For the ER model, the Cmaxand AUC values can be obtained from the Online Physicians Desk Reference (2002)or DrugDex Drug Evaluations (2002).

FSSPC Derivation

Fish steady state plasma concentrations (FSSPC) can be predicted utilizing aLog Kow value and a measured or predicted environmental concentration (EC).In general, Log Kow values and measured ECs for drugs can be obtained from theliterature or calculated (ACD/LogD software, ACD Labs, Ontario Canada; Huangand Sedlak 2001; Ternes 1998; Synder et al. 1999; Koplin et al. 2002).

For the purpose of this model, fish steady state blood concentrations were basedsolely on calculations using hydrophobicity . Accumulation via the food chain wasnot considered (i.e ., trophic transfer). Partitioning between the aqueous phase andarterial blood in trout has been described with the equation (Fitzsimmons et al.2001):

Log PBlood:Water = 0.73 × Log Kow − 0.88.


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A very similar relationship was described by Veith et al. (1979), indicating that fishbioconcentration was related to the following relationship:

LogBCF = 0.85(logKow) − 0.70.

Utilizing these relationships, drug partitioning between blood and water for agiven predicted/measured EC can then be equated to a fish steady state plasmaconcentration:

FSSPC = EC × (PBlood:Water).

The major assumption in FSSPC derivation is that the driving force behind acompound crossing from the aquatic media into the blood stream of a fish is itshydrophobicity (i.e ., Log Kow). The reasonableness of this assumption for estimationpurposes has been demonstrated (Veith et al. 1979; Fitzsimmons et al. 2001). Theproposed model further assumes that no metabolism, excretion or protein bindingoccurs in the fish (this is a worst case scenario for producing and maintaining amaximum blood level). Once a compound crosses the gill into the arterial blood,we assume that it stays in the blood plasma fully dissolved and bioavailable.

ER Derivation

The outcome of the model will be an effect ratio (ER). The ER will be defined as:

ER = HTPC/FSSPC.

An ER ≤ 1 indicates that the predicted drug concentration in the fish plasma is equalto or greater than the drug concentration in human plasma that elicits a therapeuticeffect, while an ER > 1 occurs when the fish drug plasma concentration is lowerthan the plasma drug concentration in humans that elicits a therapeutic effect. Thelower the ER, the greater the potential need for additional chronic fish testing todetermine if there are concerns.

Safety Factor Analysis

Safety factors should be used to refine the degree of uncertainty expressed in themodel. Using standard U.S. Environmental Protection Agency (USEPA) guidelines,a safety factor of 1000 could be used as an initial approach (USEPA 1989). Thisfactor is derived by applying a 10-fold factor for extrapolation of humans to animals,a 10-fold factor for sensitivity differences, and 10-fold factor for extrapolating frommammalian to non-mammalian species. Based on these assumptions, compoundswith an ER < 1000 might warrant additional assessment in fish. The SF of 1000 shouldbe viewed as an initial assessment, since no fish uptake and receptor activation datahas been developed with human pharmaceutical compounds. As data are developedin support of this model, the SF can be further refined.

CONCLUSIONS

This model approach has begun to leverage the extensive mammalian pharma-cological and toxicological data that are available on pharmaceutical products. The


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crux of this approach lies in the understanding of pharmaceutical mechanisms ofaction in humans and the homology between enzyme and receptor expression acrossmammalian and teleost species. Further data collection, model validation and re-finement will strengthen the applicability of this approach.

ACKNOWLEDGMENTS

The authors thank Dr. Robert Chapin, Pfizer Inc, for review and constructivecomments made regarding this manuscript.

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