THE VALIDATION OF TOXICOLOGICAL PREDICTION MODELS

An alternative method is shown to consist of two parts: the test syste m itself; and a prediction model for converting in vitro endpoints int o predictions of in vivo toxicity. For the alternative method to be re levant and reliable, it is important that its prediction model compone nt is of high predictive power and is sufficiently robust against sour ces of data variability. In other words, the prediction model must be subjected to criticism, leading successful models to the state of conf irmation. It is shown that there are certain circumstances in which a new prediction model may be introduced without the necessity to genera te new test system data.