Traditional toxicological studies often rely on deterministic models that do not account for uncertainty effectively. Bayesian models, on the other hand, are particularly suited for toxicology because they allow for the integration of prior knowledge with new data, leading to more informed decision-making. This is crucial when dealing with chemical exposure and dose-response relationships, where data can be sparse or noisy.
