Read-Across of 90-day Rat Oral Repeated-Dose Toxicity: A Case Study for Selected n-Alkanols

Abstract

n-Alkanols provide an excellent example where a category-approach to read-across may be used to estimate the repeated-dose endpoint for a number of untested derivatives (target chemicals) using experimental data for tested derivatives (source chemicals). n-Alkanols are non-reactive and exhibit the unspecific, reversible simple anaesthesia or non-polar narcosis mode of toxic action in that the metabolic products of the parent alcohols do not contribute to the toxic endpoint evaluated. In this case study, the chemical category is limited to the readily bioavailable (C5 to C13) analogues. The toxicokinetic premise includes rapid absorption via the gastrointestinal tract, distribution in the circulatory system, and first-pass metabolism in the liver resulting in metabolism via oxidation to CO2 and with minor elimination of oxidative intermediate as glucuronides. Two analogues have experimental 90-day oral repeated-dose toxicity data which exhibit qualitative and quantitative consistency. Typical findings include decreased body weight, slightly increased liver weight which, in some cases, is accompanied by clinical chemical and haematological changes but generally without concurrent histopathological effects at the Lowest Observed Effect Level (LOEL). Chemical similarity between the analogues is readily defined by a variety of structure-related properties; data uncertainty associated with toxicokinetic and toxicodynamic similarities is low. Uncertainty associated with mechanistic relevance and completeness of the read-across is reduced by the concordance of in vivo and in vitro results, as well as high throughput and in silico methods data. As shown in detail, the 90-day oral repeated-dose toxicity No Observed Effect Level (NOEL) value of 1000 mg/kg bw/d for 1-pentanol and 1-hexanol based on LOEL of very low systemic toxicity can be read across to fill the data gaps of the untested analogues in this category with acceptable uncertainty.