Modelling effects of variability in feeding rate on growth – a vital step for DEB-TKTD modelling

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Abstract

A major limitation of dietary toxicity studies on rodents is that food consumption often differs between treatments. The control treatment serves as a reference of how animals would have grown if not for the toxicant in their diet, but this comparison unavoidably conflates the effects of toxicity and feeding rate on body weight over time. A key advantage of toxicity models based on dynamic energy budget theory (DEB) is that chemical stress and food consumption are separate model inputs, so their effects on growth rate can be separated. To reduce data
requirements, DEB convention is to derive a simplified feeding input, f, from food availability; its value ranges from zero (starvation) to one (food available ad libitum). Observed food consumption in dietary toxicity studies shows that, even in the control treatment, rats limit their food consumption, contradicting DEB assumptions regarding feeding rate. Relatively little work has focused on addressing this mismatch, but accurately modelling the effects of food intake on growth rate is essential for the effects of toxicity to be isolated. This can provide
greater insight into the results of chronic toxicity studies and allows accurate extrapolation of toxic effects from
laboratory data. Here we trial a new method for calculating f, based on the observed relationships between food consumption and body size in laboratory rats. We compare model results with those of the conventional DEB method and a previous effort to calculate f using observed food consumption data. Our results showed that the new method improved model accuracy while modelled reserve dynamics closely followed observed body fat percentage over time. The new method assumes that digestive efficiency increases with body size. Verifying this
relationship through data collection would strengthen the basis of DEB theory and support the case for its use in ecological risk assessment.
Original languageEnglish
Article number113231
Number of pages13
JournalEcotoxicology and environmental safety
Volume232
Early online date29 Jan 2022
DOIs
Publication statusPublished - 1 Mar 2022

Keywords

  • TKTD
  • Ecotoxicology
  • modelling

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