Toxicokinetic–Toxicodynamic Modeling of the Effects of Pesticides on Growth of Rattus norvegicus

Ecological risk assessment is carried out for chemicals such as pesticides before they are released into the environment. Such risk assessment currently relies on summary statistics gathered in standardized laboratory studies. However, these statistics extract only limited information and depend on duration of exposure. Their extrapolation to realistic ecological scenarios is inherently limited. Mechanistic effect models simulate the processes underlying toxicity and so have the potential to overcome these issues. Toxicokinetic–toxicodynamic (TK–TD) models operate at the individual level, predicting the internal concentration of a chemical over time and the stress it places on an organism. TK–TD models are particularly suited to addressing the difference in exposure patterns between laboratory (constant) and field (variable) scenarios. So far, few studies have sought to predict sublethal effects of pesticide exposure to wild mammals in the field, even though such effects are of particular interest with respect to longer term exposure. We developed a TK–TD model based on the dynamic energy budget (DEB) theory, which can be parametrized and tested solely using standard regulatory studies. We demonstrate that this approach can be used effectively to predict toxic effects on the body weight of rats over time. Model predictions separate the impacts of feeding avoidance and toxic action, highlighting which was the primary driver of effects on growth. Such information is relevant to the ecological risk posed by a compound because in the environment alternative food sources may or may not be available to focal species. While this study focused on a single end point, growth, this approach could be expanded to include reproductive output. The framework developed is simple to use and could be of great utility for ecological and toxicological research as well as to risk assessors in industry and regulatory agencies.

[1]  Theo Vermeire,et al.  Risk assessment of chemicals , 2021, Bioanalytical Tools in Water Quality Assessment.

[2]  E J Calabrese,et al.  Sex differences in susceptibility to toxic industrial chemicals. , 1986, British journal of industrial medicine.

[3]  Steve Norman,et al.  Modelling effects of time-variable exposure to the pyrethroid beta-cyfluthrin on rainbow trout early life stages , 2018, Environmental Sciences Europe.

[4]  Kingma,et al.  Beyond the classic thermoneutral zone : including thermal comfort , 2014 .

[5]  Roman Ashauer,et al.  Physiological modes of action across species and toxicants: the key to predictive ecotoxicology. , 2018, Environmental science. Processes & impacts.

[6]  M. Power,et al.  Risk assessment of chemicals: an introduction , 1997 .

[7]  B. Kingma,et al.  Beyond the classic thermoneutral zone , 2014, Temperature.

[8]  V. Moser,et al.  Age- and gender-related differences in sensitivity to chlorpyrifos in the rat reflect developmental profiles of esterase activities. , 1998, Toxicological sciences : an official journal of the Society of Toxicology.

[9]  G. Séralini,et al.  New Analysis of a Rat Feeding Study with a Genetically Modified Maize Reveals Signs of Hepatorenal Toxicity , 2007, Archives of environmental contamination and toxicology.

[10]  M. Prieto,et al.  NOEC and LOEC as merely concessive expedients: two unambiguous alternatives and some criteria to maximize the efficiency of dose-response experimental designs. , 2013, The Science of the total environment.

[11]  Jens Timmer,et al.  Profile likelihood in systems biology , 2013, The FEBS journal.

[12]  Keith R. Godfrey,et al.  Modelling the Double Peak Phenomenon in pharmacokinetics , 2011, Comput. Methods Programs Biomed..

[13]  Sebastiaan A L M Kooijman,et al.  Making Sense of Ecotoxicological Test Results: Towards Application of Process-based Models , 2006, Ecotoxicology.

[14]  Thomas Brox,et al.  Maximum Likelihood Estimation , 2019, Time Series Analysis.

[15]  J. Gillet,et al.  The effects of diet, ad Libitum feeding, and moderate and severe dietary restriction on body weight, survival, clinical pathology parameters, and cause of death in control Sprague-Dawley rats. , 2000, Toxicological sciences : an official journal of the Society of Toxicology.

[16]  Tjalling Jager,et al.  Physiological modes of action of toxic chemicals in the nematode Acrobeloides nanus , 2006, Environmental toxicology and chemistry.

[17]  D. Westerlund,et al.  Dose‐dependent absorption of amoxycillin and bacampicillin , 1985, Clinical pharmacology and therapeutics.

[18]  T. Jager Bad habits die hard: The NOEC's persistence reflects poorly on ecotoxicology , 2012, Environmental toxicology and chemistry.

[19]  T. Jager All individuals are not created equal; accounting for interindividual variation in fitting life-history responses to toxicants. , 2013, Environmental science & technology.

[20]  V. Grimm,et al.  Ecological Models in Support of Regulatory Risk Assessments of Pesticides: Developing a Strategy for the Future , 2009, Integrated environmental assessment and management.

[21]  P. Pahl Growth curves for body weight of the laboratory rat. , 1969, Australian journal of biological sciences.

[22]  Sebastiaan A.L.M. Kooijman,et al.  Analysis of toxicity tests on Daphnia survival and reproduction , 1996 .

[23]  L. Lesko,et al.  Dose-dependent Elimination Kinetics of Theophylline , 1979, Clinical pharmacokinetics.

[24]  Jianxin Pan,et al.  Growth curve models and statistical diagnostics , 2002 .

[25]  Thomas G. Preuss,et al.  Demographic Toxicokinetic-Toxicodynamic Modeling of Lethal Effects. , 2016, Environmental science & technology.

[26]  C. Cooper,et al.  Temporal Analysis of Rat Growth Plates: Cessation of Growth with Age Despite Presence of a Physis , 2003, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.

[27]  Paul A Murtaugh,et al.  In defense of P values. , 2014, Ecology.

[28]  Christian Sonne,et al.  Using energy budgets to combine ecology and toxicology in a mammalian sentinel species , 2017, Scientific Reports.

[29]  OECD GUIDELINES FOR THE TESTING OF CHEMICALS , 2008 .

[30]  S. H. Bennekou,et al.  Scientific Opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) effect models for regulatory risk assessment of pesticides for aquatic organisms , 2018, EFSA journal. European Food Safety Authority.

[31]  Sebastiaan A.L.M. Kooijman,et al.  Dynamic Energy and Mass Budgets in Biological Systems , 2000 .

[32]  Volker Grimm,et al.  Mechanistic effect modeling for ecological risk assessment: Where to go from here? , 2013, Integrated environmental assessment and management.

[33]  Gonçalo M. Marques,et al.  The AmP project: Comparing species on the basis of dynamic energy budget parameters , 2018, PLoS Comput. Biol..

[34]  S. Lindstedt,et al.  Use of allometry in predicting anatomical and physiological parameters of mammals , 2002, Laboratory animals.

[35]  Elke I. Zimmer,et al.  Prediction of long-term variation in offspring metabolism due to BPA in eggs in rainbow trout using the DEB model , 2019, Journal of Sea Research.

[36]  K. Kanosue,et al.  Autonomic and behavioural thermoregulation in starved rats , 2000, The Journal of physiology.

[37]  Tjalling Jager,et al.  DEBkiss or the quest for the simplest generic model of animal life history. , 2013, Journal of theoretical biology.

[38]  Sebastiaan A.L.M. Kooijman,et al.  The “covariation method” for estimating the parameters of the standard Dynamic Energy Budget model II: Properties and preliminary patterns , 2011 .

[39]  João Pedro de Magalhães,et al.  Human Ageing Genomic Resources: new and updated databases , 2017, Nucleic Acids Res..

[40]  JustinW . Brown,et al.  Characterization of the Thermoneutral Zone of the Laboratory Rat , 2008 .

[41]  J. Koolhaas,et al.  Behavioral and physiological responses to stress are affected by high-fat feeding in male rats , 2001, Physiology & Behavior.

[42]  J. Stephenson,et al.  Body temperature regulation and thermoneutrality in rats. , 1977, Quarterly journal of experimental physiology and cognate medical sciences.

[43]  Pernille Thorbek,et al.  A toxicokinetic model for thiamethoxam in rats: implications for higher-tier risk assessment , 2013, Ecotoxicology.

[44]  Roman Ashauer,et al.  Toxicokinetic-toxicodynamic modelling of survival of Gammarus pulex in multiple pulse exposures to propiconazole: model assumptions, calibration data requirements and predictive power , 2012, Ecotoxicology.

[45]  Roman Ashauer,et al.  How to Evaluate the Quality of Toxicokinetic—Toxicodynamic Models in the Context of Environmental Risk Assessment , 2018, Integrated environmental assessment and management.

[46]  Sebastiaan A.L.M. Kooijman,et al.  The “covariation method” for estimating the parameters of the standard Dynamic Energy Budget model I: Philosophy and approach , 2011 .

[47]  D. Baird,et al.  Among‐ and within‐population variability in tolerance to cadmium stress in natural populations of Daphnia magna: Implications for ecological risk assessment , 2002, Environmental toxicology and chemistry.

[48]  Tg Repeated Dose 90-Day Oral Toxicity Study in Rodents (OECD TG 408) , 2018, OECD Series on Testing and Assessment.

[49]  P. Calow,et al.  Promises and problems for the new paradigm for risk assessment and an alternative approach involving predictive systems models , 2012, Environmental toxicology and chemistry.

[50]  Sebastiaan A.L.M. Kooijman,et al.  The Analysis of Aquatic Toxicity Data , 1996 .

[51]  M. Begon,et al.  Individual growth rates in natural field vole, Microtus agrestis, populations exhibiting cyclic population dynamics , 2010, Oecologia.