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Quantifying the biological impact of active substances using causal network models

 
: Sewer, A.; Martin, F.; Schlage, W.K.; Hoeng, J.; Peitsch, M.C.

:

Hoeng, Julia:
Computational Systems Toxicology
New York/NY: Springer Science+Business Media, 2015 (Methods in pharmacology and toxicology)
ISBN: 978-1-4939-2777-7 (Print)
ISBN: 978-1-4939-2778-4 (Online)
S.223-256
Englisch
Aufsatz in Buch
Fraunhofer SCAI ()

Abstract
In this chapter a five-step strategy is described that provides comparative evaluations of the effects of biologically active substances. These evaluations constitute an integral part of the determination of the risks for the human population to exposure to these substances. The strategy is based on the concept of biological impact quantification for which novel computational methodologies have been developed in the past few years; these methodologies are reviewed in this chapter. The effects of the active substances are then described in terms of networks containing the biological mechanisms involved in the response to the exposure. As a consequence, the biological impact assessment represents a systems-wide metric of network- based perturbed biological mechanisms. The implementation of the strategy involves the generation of transcriptomics data following the exposure experiment and their evaluation in the context of causal network models. After the five-step strategy for biological impact quantification has been described in some detail, its application in a concrete case of a mouse smoking-cessation experiment is presented. The results show how mechanistic insights into the potential toxic effects of exposure to active substances can benefit the safety assessment.

: http://publica.fraunhofer.de/dokumente/N-418394.html