# Interlaboratory clinical chemistry parameter variation in seven-day acute hydrazine toxicity studies in the Sprague-Dawley rat

## TL;DR

This study examines how different labs measure the effects of hydrazine toxicity in rats, finding consistent biochemical patterns despite variability.

## Contribution

The study identifies a consistent biochemical signature of hydrazine toxicity across multiple labs using multivariate analysis.

## Key findings

- Hydrazine exposure consistently increased serum bilirubin and BUN while decreasing serum protein concentrations.
- Early biomarkers like AST, ALT, total protein, and calcium strongly predict 48-hour toxicity profiles.
- Multivariate analysis revealed a core pathological response despite inter-laboratory variability.

## Abstract

Clinical chemistry retains its position as a cornerstone of toxicological assessment, yet inter-laboratory variability in baseline values remains a challenge for the integration and interpretation of multisite datasets. This study leveraged a publicly available clinical chemistry database to assess the impact of inter-laboratory variability in response to hydrazine-induced steatosis. Seventeen clinical chemistry and physico-chemical parameters were evaluated in response to a single dose of hydrazine (at 30 mg/kg or 90 mg/kg) administered to Sprague-Dawley rats (n = 83) across five different pharmaceutical companies and compared with sham-dosed control animals. Hydrazine exposure produced a distinct and consistent biochemical signature at 48 h post-dose across the combined sample set from all laboratory sites, characterised by increased serum bilirubin and BUN and decreased serum protein concentrations, alongside atypical reductions in ALT and AST due to transaminase inhibition. Despite sizable inter-laboratory differences in response when considering single assays, multivariate analysis of the complete dataset was able to extract a core pathological response signature. Early changes at 24 h post-dose in AST, ALT, total protein, and calcium demonstrated strong predictive value for 48-h toxicity profiles (AUROC 0.98), underscoring the translational potential of early biomarkers. This study highlights both the robustness and contextual limitations of clinical chemistry data in toxicological studies. It underscores the importance of matched-control designs and multivariate approaches for multisite studies and advocates for the integration of early predictive modelling to optimise study design and align with the principles of the Replace, Reduce, and Refine initiative.

The online version contains supplementary material available at 10.1007/s00204-025-04227-5.