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Oct 15, 2009 (Vol. 29, No. 18)

Assessment of Drug Interaction Potential

Biomimetic Oxidation Can Facilitate the Generation of Metabolites for Testing Purposes

  • Click Image To Enlarge +
    Tentative (bracketed) structure assignments of metabolites M1a (top) and M2 (bottom) based on MS/MS data.

    For at least a dozen years since the publication of a 1997 FDA guidance on in vitro metabolism studies, drug developers have been required to perform in vitro tests of drug interaction potential prior to clinical trials. The 1997 guidance has been updated by a 2006 draft guidance, and, in some cases, it is now advisable to test metabolites as well. 

    For example, a glucuronide conjugate of gemfibrozil causes a 19-fold increase in the AUC of repaglinide when gemfibrozil is co-administered with itraconazole. Examples such as this highlight the importance of testing for potential drug interactions involving metabolites, in addition to new drugs themselves.

    Testing metabolites introduces additional questions and levels of complexity, including:

    • Which metabolites to test? (not obvious a priori and impossible to predict)
    • Which preclinical species is most appropriate for in vivo testing? In other words, in which species is the metabolite profile most similar to human? (can be determined in vitro)
    • Are there any metabolites unique to or disproportionately abundant in humans? (can be determined in vivo)
    • How to generate metabolites for testing?

    One approach to generating metabolites is biomimetic oxidation, which is currently being applied by Absorption Systems.

  • Biomimetic generation of metabolites is based on the use of complexes of transition metals, usually with synthetic porphyrins, to imitate oxidative metabolism catalyzed in biological systems by cytochrome P450  enzymes. For preparative purposes, biomimetic systems offer several advantages over biological matrices, including the fact that organic solvents can be used, which increases the solubility of many drugs; the variability inherent in biological systems is not an issue; scale-up is simple and feasible; and purification of metabolites is greatly simplified by the less-complex matrix.

    Ritonavir was used as a model substrate to demonstrate the value of the biomimetic approach. Initially, four different catalysts were tested, along with three organic solvents and two oxygen donors, all at ambient temperature for up to 24 hours. The yield of metabolites was consistently lower when dichloromethane was the solvent compared with acetonitrile or methanol. 

    Cumene peroxide was a more effective oxygen donor than hydrogen peroxide. Iron-based catalysts, particularly Fe(III)meso-tetra(pentafluorophenyl) porphine chloride, were more efficient in generating mono-oxidative metabolites. The amount of mono-oxidative metabolites peaked at 10 to 15 minutes, then decreased, presumably due to further (not biologically relevant) oxidation.

    For the purpose of producing preparative quantities of metabolites, the biomimetic system was scaled up using optimized conditions:

    • Solvent: methanol
    • Catalyst: Fe(III)meso-tetra(pentafluorophenyl) porphine chloride
    • Molar ratio of ritonavir/catalyst/ cumene peroxide: 10/1/50
    • Incubation time: 15 minutes

    Under these conditions, approximately 50% of the starting amount of ritonavir was recovered at the end of the incubation, along with two biologically relevant metabolites, mono-oxidative M1a (7.8 mg) and N-dealkylated M2 (5.7 mg). A number of other oxidative products were generated biomimetically but were not characterized. The biomimetically generated metabolites M1a and M2 were initially accepted to be identical to the biological metabolites based on their co-elution and indistinguishable MS/MS spectra (Figure). Final structure confirmation was performed by NMR.



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