S5: Predictive systems toxicology

Predictive systems toxicology: challenges in mechanistic modeling and structure-based assessment

Ayako Yachie, Predictive systems toxicology, OpenTox Asia 2018
PRESENTING AUTHOR: 

Ayako Yachie

INSTITUTION / COMPANY : 

The Systems Biology Institute, Japan

POSITION: 

Senior Scientist

AUTHOR(S): 

Ayako Yachie and Vipul Gupta

ABSTRACT CONTENT / DETAILS: 

The objective of systems toxicology is to predict and provide the best outcome and least adverse effects of chemicals. And the ultimate goal of the field is to do that based on personalized data such as individual genetic background, dietary habits and other characteristics. To this end, mechanism-based mathematical models are required as platforms to integrate the information of input chemical properties and the systems condition. In addition, well-trained simulation models can minimize the cost of experiments including screening of chemical combinations, sensitivity analysis and assessment of systems threshold towards specific chemicals.

Cellular biochemical/regulatory network, which is a functional building unit of living systems, is one of the most applied systems for modeling and simulation. The complexity of cellular network is in each biological layer which has distinct scales of time, space and quantity, while all of which is orchestrated into one cell system. On the other hand, these cellular networks including protein interaction and the biochemical pathways have come to be recognized as explanatory variables of various biological phenomena. It is thus assumed that the integration of the traditional chemical properties - the structural similarity and binding profiles – and their intrinsic cellular network effects will be indispensable for practical prediction of the impact of chemical compound.

In this session, by introducing our resent efforts on cell simulation and cellular network-based chemical classification, the perspective will be discussed for the predictive systems toxicology.