You are here:
Predictive Modeling and Computational Toxicology
Citation:
KLEINSTREUER, N. C. AND T. B. KNUDSEN. Predictive Modeling and Computational Toxicology. Third Edition, Chapter 23, Ronald D.Hood (ed.), Developmental and Reproductive Toxicology: A Practical Approach. Informa Healthcare Books, UK, London, Uk, , 578-591, (2011).
Impact/Purpose:
Newer HTS-HCS technologies in genomics, molecular biology, metabolomics, small model organisms, and complex cellular cultures are providing more data and more detailed information relevant to all stages of embryogenesis and chemical exposure levels. Virtual tissue models that simulate cellular behaviors and interactions can utilize these extensive data and knowledge about the system to rapidly follow potential developmental trajectories and chemical perturbations. They can thus incorporate a wider variety of information and providing deeper insights into mechanisms of toxicity than is possible solely by analyzing individual data sources, and certainly by animal testing. Computational embryology promotes the development of in silico models that may bridge the gap between in vitro profiling and in vivo response after in utero exposure to environmental compounds. As the field continues to grow, these computational models will continue to become more relevant with regard to human risk assessment.
Description:
Embryonic development is orchestrated via a complex series of cellular interactions controlling behaviors such as mitosis, migration, differentiation, adhesion, contractility, apoptosis, and extracellular matrix remodeling. Any chemical exposure that perturbs these cellular processes has the potential to disrupt development and result in adverse pregnancy outcomes, such as low fetal birth weight, structural malformations, functional deficits, and prenatal death. Evaluating these endpoints in standardized animal bioassays of in vivo developmental toxicity (e.g., OECD guideline 414) provides regulatory information with which to assess the overt teratogenic potential of a compound, usually at high doses. However, traditional animal testing offers little mechanistic insight into the cellular- and tissue-level chemical interactions underlying this potential at lower dosages that may be more realistic for human exposure. An additional layer of complexity arises from varied toxicological susceptibilities between developmental stages and vertebrate species, making the task of extrapolating prenatal animal data to human pregnancy risk scenarios even more challenging.
