![]() Toxicology (as all of medicine) does not reach this level of certainty, as the Johns Hopkins scholar William Osler (1849–1919) rightly stated, “ Medicine is a science of uncertainty and an art of probability”, and in this sense toxicology is a very medical discipline. Nothing is as certain as death and taxes 1. ![]() In conclusion, probabilistic risk assessment will be key for constructing a new toxicology paradigm – probably! Additional aspects are opportunities for uncertainty analysis of adverse outcome pathways and their relation to thresholds of toxicological concern. This article gives an overview of methods for probabilistic risk assessment and their application for exposure assessment, physiologically-based kinetic modelling, probability of hazard assessment (based on quantitative and read-across based structure-activity relationships, and mechanistic alerts from in vitro studies), individual susceptibility assessment, and evidence integration. The objective nature of these mathematical tools allows to assign each methodology its fair place in evidence integration, whether in the context of risk assessment, systematic reviews, or in the definition of an integrated testing strategy (ITS) / defined approach (DA) / integrated approach to testing and assessment (IATA). Most importantly, as soon as we agree on uncertainty, this defines room for improvement and allows a transition from traditional to new approach methods as an engineering exercise. Actual assessments of uncertainty can be more realistic than worst-case scenarios and may allow less conservative safety margins. Probabilistic methods and Bayesian approaches seek to characterize these uncertainties and promise to support better risk assessment and, thereby, improve risk management decisions. Traditionally, this is taken into account by using uncertainty / assessment factors and worst-case / precautionary approaches and thresholds. Every toxicological tool delivers only probable results. Acknowledging this uncertainty necessitates embracing probabilities and accepting the remaining risk. Safety sciences must cope with uncertainty of models and results as well as information gaps.
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