Mathematical models for biomarker calculation of drug-induced liver injury in humans and experimental models based on gadoxetate enhanced magnetic resonance imaging

BACKGROUND: Drug induced liver injury (DILI) is a major concern when developing new drugs. A promising biomarker for DILI is the hepatic uptake rate of the contrast agent gadoxetate. This rate can be estimated using a novel approach combining magnetic resonance imaging and mathematical modeling. However, previous work has used different mathematical models to describe liver function in humans or rats, and no comparative study has assessed which model is most optimal to use, or focused on possible translatability between the two species. AIMS: Our aim was therefore to do a comparison and assessment of models for DILI biomarker assessment, and to develop a conceptual basis for a translational framework between the species. METHODS AND RESULTS: We first established which of the available pharmacokinetic models to use by identifying the most simple and identifiable model that can describe data from both human and rats. We then developed an extension of this model for how to estimate the effects of a hepatotoxic drug in rats. Finally, we illustrated how such a framework could be useful for drug dosage selection, and how it potentially can be applied in personalized treatments designed to avoid DILI. CONCLUSION: Our analysis provides clear guidelines of which mathematical model to use for model-based assessment of biomarkers for liver function, and it also suggests a hypothetical path to a translational framework for DILI.
Funding: Swedish Research Council: VR/MH [2020-04826, 2020.0182]; County Council; Swedish Research Council: VR/NT [777107]; Center for Industrial Information Technology (CENIIT); Swedish foundation for Strategic Research; SciLifeLab; KAW; H2020 project PRECISE4Q; Swedish Fund for Research without Animal Experiments; Excellence Center at Linkoping -Lund in Information Technology (ELLIIT); [2018-03319]; [2007-2884]; [2018-05418]; [15.09]; [ITM17-0245]