(Q)SARs for Predicting Effects Relating to Reproductive Toxicity

Abstract

This paper reviews the current status of structure-based methods for predicting adverse reproductive effects in mammals. The methods described include (Quantitative) Structure -Activity Relationships ((Q)SARs), expert systems and the less formalised approaches of read-across within (chemical) categories. There are a number of problems with applying QSARs to reproductive toxicology notably the complexity, subtlety and sometimes ill-defined nature of the endpoints and lack of data available for modelling. A small number of ((Q)SARs have been developed for individual classes of compounds for well-defined effects. These are supplemented by expert systems approaches of all types [e.g. DEREK for Windows, TOPKAT, MC4PC, PASS, Organisation for Economic Cooperation and Development (OECD) QSAR Application Toolbox] for a variety of endpoints associated with reproductive toxicology. By far the largest, and best developed, group of models are those for receptor binding effects related to endocrine disruption, in particular to the Oestrogen Receptor (ER) and, to a lesser extent, the Androgen Receptor (AR). Strategies to improve predictive capabilities for reproductive toxicology are suggested.

Application of quantitative structure–activity relationships for modeling drug and chemical transport across the human placenta barrier: a multivariate data analysis approach

“…However, the complexity, subtlety and sometimes illdefi ned nature of endpoints combined with the lack of reliable available data constitute major drawbacks for the development of computational classifi cation and prediction models in the area of reproductive toxicology (Cronin and Worth, 2008). Thus, a relatively small number of QSARs has been reported in the area of reproductive toxicology compared with other human and environmental toxicity endpoints (Cronin and Worth, 2008). In contrast, a signifi cant number of studies relating to the prediction of ADME processes, such as passive membrane permeation, have been reported in the literature (Yamashita and Hashida, 2004).…”

“…In this case, drug permeation in biomembranes has been well predicted on the basis of physicochemical and molecular properties (Malkia et al, 2004). Since the placental transfer process includes membrane permeation as an essential step among others, it could be considered as an ADME endpoint relating to reproductive toxicology with enhanced chance to be eff ectively predicted by QSAR analysis (Cronin and Worth, 2008).…”

Applicability of QSAR analysis to the evaluation of the toxicological relevance of metabolites and degradates of pesticide active substances for dietary risk assessment

“…decision tree approaches) can be grouped into the following categories: a) local models for the reprotoxic effects of individual series of compounds; b) global models for the reprotoxic effects of heterogeneous groups of compounds; c) models for ADME properties; d) models relating to endocrine activity and endocrine disruption potential; and e) chemical categories and read-across assessments. The status of these methods up to 2008 has been reviewed elsewhere (Cronin & Worth, 2008).…”

Development of QSAR models using artificial neural network analysis for risk assessment of repeated-dose, reproductive, and developmental toxicities of cosmetic ingredients

“…For developmental or reproductive toxicity, there are some software tools based on QSAR (reviewed in Cronin and Worth, 2008;Piparo and Worth, 2010), but these were constructed to predict hazards related to developmental or reproductive toxicity (i.e., they are limited to qualitative analysis) and no quantitative model has been reported.…”