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Oct 9, 2018
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Quantitative Systems Toxicology Modeling Using DILIsym Suggests That Mitochondrial Biogenesis Could Explain Adaptation to Drug-Induced Liver Injury (DILI)


Resolution of elevations of the liver injury biomarker serum ALT despite continued drug dosing, termed “adaptation”, is commonly observed in clinical trials, but the underlying mechanisms behind this phenomenon remain unclear.
• Mitochondrial dysfunction is one of the major mechanisms underlying DILI. [1] When mitochondrial function is insufficient for energy demand, mitochondrial biogenesis is often activated and contributes to adaptation. [2-4]
• Solithromycin, a 4th generation macrolide developed for the treatment of community acquired pneumonia, caused serum ALT elevations in a minority of patients in clinical studies, with improvement often observed during continued dosing (or with
rapid recovery thereafter). [5]
• DILIsym® is a quantitative systems toxicology (QST) model which integrates in vitro mechanistic toxicity data, in vivo dynamic drug disposition, known biochemistry, and patient characteristics. DILIsym predicts the hepatotoxic potential of new drug candidates and also provides an enhanced understanding of the mechanisms underlying compounds that generate liver signals in the clinic. [6]
• QST modeling of macrolide antibiotics using DILIsym showed that mechanisms underlying ALT elevations were significantly different within the same class of antibiotics. ALT elevations mediated by solithromycin and clarithromycin were predominantly due to mitochondrial electron transport chain (ETC) inhibition, whereas erythromycin effects were mainly due to bile acid (BA) transporter inhibition. [7]
• Mechanism analyses using QST modeling suggest that mitochondrial biogenesis might have contributed to the observed adaptation of solithromycin. In the current study, mitochondrial biogenesis was mechanistically represented within DILIsym, and its impact on time dependent ALT elevations resulting from solithromycin and other drugs was assessed.

Ninth American Conference on Pharmacometrics (ACoP) Annual Meeting, October 6-12, 2018, San Diego, CA

By Kyunghee Yang, Jahid Ferdous, Jeffrey L Woodhead, Paul B Watkins, Brett A Howell, and Scott Q Siler

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