Multiscale zonation-resolved modeling of dose-dependent determinants of acetaminophen-induced liver injury

Drug-induced liver injury (DILI) is a major cause of morbidity and mortality and has an important impact on drug attrition. Recent guidelines from the FDA and previous research encourage the development of virtual twin in silico modeling as a solution to reduce DILI impact.

In this study, we used our virtual, scalable model of the human liver lobule coupled with an acetaminophen (APAP) metabolic injury model to expand the mechanistic understanding of metabolic zonation parameters involved in APAP hepatotoxicity. Using clinical overdose data, we generated a representative in silico patient cohort, encompassing both lower and higher APAP overdoses, and analyzed how zonal variations in metabolism factors impacted the generation of liver damage.

The results showed a significant difference in the sensitivity of the metabolic parameters at different overdose levels. Some, such as drug uptake rate, led to increased damage; others, such as CYP450 enzymatic activity, showed overdose-dependent effects, and others, such as the sulfation rate, showed only limited effects.

Overall, this study highlights the importance of collecting proper metabolic expression (specifically drug uptake rate, CYP450 enzymatic activity, and glutathione quantity) to ensure an accurate estimation of patient damage.