164
Z. Liu et al.
Fig. 9.2 Key questions in the toxicogenomics field
properties and host information on DILI [ref]. More importantly, a reproducible DILI
classification scheme was developed for facilitating DILI prediction model development [34, 35]. Furthermore, Wen et al. [36] developed a drug-induced rhabdomyolysis atlas (DIRA) that mainly provides three folds of drug-induced rhabdomyolysis
related information including a classification scheme for drugs’ potential to rhabdomyolysis, post-marketing surveillance data of drug-induced rhabdomyolysis and
drug property information.
From a translational toxicology perspective, it is of great importance to comprehensively explore assay transferability among the testing systems and provide useful
information for preclinical toxicity screening. Our study looks to use TGx techniques
computationally to answer the following five questions from a translational science
point of view (Fig. 9.2):
1. Can in vitro analysis predict in vivo results?
2. Can short-term assays (as short as one day) replace long-term assays (such as
twenty-eight-day assays)?
3. Is the extrapolation between assay systems endpoint dependent?
4. Is the extrapolation between assay systems adverse outcome pathways (AOPs)
related?
5. Can a TGx system provide extra value to Read-Across?
Z. Liu et al.
Fig. 9.2 Key questions in the toxicogenomics field
properties and host information on DILI [ref]. More importantly, a reproducible DILI
classification scheme was developed for facilitating DILI prediction model development [34, 35]. Furthermore, Wen et al. [36] developed a drug-induced rhabdomyolysis atlas (DIRA) that mainly provides three folds of drug-induced rhabdomyolysis
related information including a classification scheme for drugs’ potential to rhabdomyolysis, post-marketing surveillance data of drug-induced rhabdomyolysis and
drug property information.
From a translational toxicology perspective, it is of great importance to comprehensively explore assay transferability among the testing systems and provide useful
information for preclinical toxicity screening. Our study looks to use TGx techniques
computationally to answer the following five questions from a translational science
point of view (Fig. 9.2):
1. Can in vitro analysis predict in vivo results?
2. Can short-term assays (as short as one day) replace long-term assays (such as
twenty-eight-day assays)?
3. Is the extrapolation between assay systems endpoint dependent?
4. Is the extrapolation between assay systems adverse outcome pathways (AOPs)
related?
5. Can a TGx system provide extra value to Read-Across?