PREDICTIVE TOXICODYNAMICS - EMPIRICAL MECHANISTIC APPROACHES/

A major objective of the toxicological sciences is to predict the in v ivo toxicological consequences of human exposure to pure chemicals, co mplex mixtures and commercial formulations. Historically, the experime ntal approach to this goal has been to investigate toxicological proce sses in whole animal models and extrapolate the results obtained to pr edict human risk using various extrapolation procedures (high-dose/low -dose extrapolation, interspecies extrapolation and route-to-route ext rapolation). Can in vitro methods be more widely employed in quantitat ive risk assessment? One major limitation to the broader application o f in vitro toxicity testing methods is the lack of validated technique s for the extrapolation of in vitro-derived toxicodynamic data to the in vitro situation. The objective of this paper is to describe some ap proaches to the development of techniques to extrapolate in vitro toxi city testing data to predict in vivo toxicological responses. An empir ical approach within the context of a mechanistic framework is explore d. The basic hypothesis is that the in vivo response can be constructe d from a cellular toxicity factor that accounts for the cellular respo nse and a toxicodynamic factor that relates toxicological events at th e cellular level to the observable in vivo responses. A predictive par adigm to describe the in vivo acute target organ toxicity (hepatotoxic ity) of a model chemical (cadmium) is discussed. The cellular toxicity factor is derived from in vitro toxicity testing studies using isolat ed rat hepatocytes. The toxicodynamic factor is derived through Biolog ically-Based Response (BBR) modelling techniques to predict target org an toxicity markers (i.e. plasma hepatic enzyme levels as markers for acute hepatotoxicity). The ultimate goal is to develop validated extra polation procedures that can be applied to predicting target organ tox icity quantitatively in human populations based on in vitro toxicity s tudies using human cellular models. (C) 1997 Published by Elsevier Sci ence Ltd.