Armin Wolf is Chief Scientific Officer at InSphero AG and Professor of Toxicology at the Technical University of Kaiserslautern, Germany. An accomplished pharmaceutical R&D executive and board-certified toxicologist with more than 30 years cumulative experience at Janssen and Novartis, Armin offers a first-hand perspective on the challenges facing the pharmaceutical industry.  

OpenTox Euro 2019 talk: Pragmatic applications of Adverse Outcome Pathways in Investigative Toxicology in the Deconvolution of DILI mechanisms

The Pharma Discovery average of non-clinical attrition rates due to Drug-induced Liver Injury (DILI) is between 30 % - 45 %. Idiosyncratic DILI is the cause for the withdrawn of already registered drugs from the market. The mechanisms leading to DILI are not fully understood. Possible mechanisms involved in most of the observed DILI cases include the formation of reactive drug metabolites, the formation of reactive oxygen species, inflammatory stimuli, the inhibition of bile acid transport functions, and mitochondrial toxicity. 

AOP (adverse outcome pathways) has been demonstrated to be helpful in the understanding of the mechanisms leading to DILI. However, the tools available for constructing AOPs for human DILI are compromised by the lack of predictability of the applied animal studies and 2D cultures. Omics based pathway analyses does not show the sequence of events and the causal link between pathway changes and key events. In the current presentation, 3D human liver micro-tissues (3D-hLiMT) were used which exhibit longevity, stable metabolic competence, preserved structural and functionality compared to 2D cultures. We show results from causality cytotoxicity assays for the most important basic DILI mechanisms with specific pathway modulator (agonist/antagonists) by concomitant treatment with reference model compounds. A shift of the IC50 in the presence of the modulator indicates a causal relationship.

The 3D-hLiMT model, consisting of primary hepatocytes, Kupffer and liver endothelial cells has been demonstrated to have higher translatability for human compared to 2D models. Thus, the obtained results have higher value for DILI de-risking programs in drug development. hLiMTs can be cultured in 384-well plates enabling robust reproducible data for high throughput testing.