One of the main challenges that needs to be addressed before OMICS technologies receive regulatory acceptance in chemical risk assessment is a specific and quantitative connection to adverse outcomes of regulatory concern. We present a multidisciplinary pipeline that can be used to develop causal biological networks that describe the current knowledge on adverse outcomes of interest and evaluate the perturbation of the network. Here we present an example of a developed zebrafish cardiotoxicity causal network, split into putative AOP-like pathways using graph theoretical approaches. The pathways are then integrated with transcriptomic datasets and scored for perturbation. The advantage of using our approach is that one can use a single transcriptomic dataset to evaluate toxicity over all existing AOPs and AOP-like pathways.