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The assessment of safety in traditional toxicology protocols relies on evidence arising from observed adverse events (AEs) in animals and on establishing their correlation with different measures of drug exposure (e.g., Cmax and AUC). Such correlations, however, ignore the role of biomarkers, which can provide further insight into the underlying pharmacological mechanisms. Here we use naproxen as a paradigm drug to explore the feasibility of a biomarker-guided approach for the prediction of AEs in humans. A standard toxicology protocol was set up for the evaluation of effects of naproxen in rat, in which four doses were tested (7.5, 15, 40 and 80 mg/kg). In addition to sparse blood sampling for the assessment of exposure, thromboxane B2 and prostaglandin E2 were also collected in satellite groups. Nonlinear mixed effects modelling was used to evaluate the predictive performance of the approach. A one-compartmental model with first order absorption was found to best describe the pharmacokinetics of naproxen. A nonlinear relationship between dose and bioavailability was observed which leads to a less than proportional increase in naproxen concentrations with increasing doses. The pharmacodynamics of TXB2 and PGE2 was described by direct inhibition models with maximum pharmacological effects achieved at doses > 7.5 mg/kg. The predicted PKPD relationship in humans was within 10-fold of the values previously published. Moreover, our results indicate that biomarkers can be used to assess interspecies differences in PKPD and extrapolated data from animals to humans. Biomarker sampling should be used systematically in general toxicity studies.Prediction of a drug's safety profile from preclinical protocols remains challenging.Pharmacokinetic measures of safe exposure (e.g., AUC) ignore the role of biomarkers.PKPD relationships enable the evaluation of adverse events in a mechanistic manner.Major differences exist between rats and humans in the effects of naproxen on TXB2.A biomarker-guided approach may facilitate the prediction of adverse events in humans.