Litter-based methods in developmental toxicity risk assessment

Abstract

Developmental toxicity experiments are designed to assess potential adverse effects of drugs and other exposures on developing fetuses from pregnant dams. Extrapolation to humans is a very difficult problem. An important issue here is whether risk assessment should be based on the fetus or the litter level. In this paper, fetus and litter-based risks that properly account for cluster size are defined and compared for the beta-binomial model and a conditional model for clustered binary data. It is shown how the hierarchical structure of non-viable implants and viable but malformed offspring can be incorporated. Risks based on a joint model for death/resorption and malformation are contrasted with risks based on an adverse event defined as either death/resorption or malformation. The estimation of safe exposure levels for all risk types is discussed and it is shown how estimation of the cluster size distribution affects variance estimation. The methods are applied to data collected under the National Toxicology Program and in large sample simulations.