1. Academic Validation
  2. Metabolism of mofarotene in hepatocytes and liver microsomes from different species. Comparison with in vivo data and evaluation of the cytochrome P450 isoenzymes involved in human biotransformation

Metabolism of mofarotene in hepatocytes and liver microsomes from different species. Comparison with in vivo data and evaluation of the cytochrome P450 isoenzymes involved in human biotransformation

  • Drug Metab Dispos. 1995 Oct;23(10):1051-7.
B Valles 1 C D Schiller P Coassolo G De Sousa R Wyss D Jaeck A Viger-Chougnet R Rahmani
Affiliations

Affiliation

  • 1 Pharma Division, F. Hoffmann-La Roche, Basel, Switzerland.
PMID: 8654192
Abstract

The arotinoid mofarotene is a novel potent Anticancer compound. The metabolic profiles obtained from rat, dog, and human plasma showed a good correlation with the corresponding in vitro profiles observed with liver microsomes and hepatocytes. Interspecies differences in its metabolism were investigated using microsomes prepared from the livers of the mouse, rat, dog, cynomolgus monkey, and humans. These in vitro experiments showed that, both qualitatively and quantitatively, the metabolic profiles obtained with cynomolgus monkey liver samples were similar to those observed with human liver material. However, rat and dog were also confirmed to be suitable species for assessing the safety of mofarotene, and were used in toxicology. The involvement of Cytochrome P450 (CYP) in the metabolism of mofarotene was examined with human liver microsomes. CYP3A4 plays a major role in the metabolism, and CYP1A2 might be responsible for a minor pathway. Finally, the potential induction by mofarotene of four major CYP isoenzymes was investigated in rats. These experiments showed that CYP1A1 was clearly induced, whereas a slight induction of CYP3A and CYP2B was observed. Repeated administration of mofarotene had no effect on CYP2E1. These studies with liver microsomes and hepatocytes aided the selection of appropriate species for toxicology, and have provided information that will help to predict potential drug-drug interactions in clinical trials.

Figures
Products