The use of in vitro metabolic surrogates (e.g. microsomes, recombinant CYP450s, cyro-preserved hepatocytes) is now widespread in drug discovery and evermore refined methods improving the utility of these model are in constant development. However, as any IVIV extrapolation is always subject to the reduced complexity of those model systems it is vital to understand their limitations (e.g. reduced expression of CYP3A4, PXR and CAR in CACO-2s; rapid loss of metabolic competence, canalicular and basolateral efflux transport in freshly isolated hepatocytes.) to avoid misinterpretation of data
In order to predict possible Drug-Drug Interactions (DDIs) it is necessary to understand the relative contribution of individual CYPs to the overall phase I metabolism of an NCE and to this end Relative Activity Factor (RAF), developed twenty years ago (1), has been used alongside inhibition approaches to elucidate the CYP reaction phenotype. Individual recombinant CYPs (rCYP), expressed in and isolated on bacterial membranes, can be used to measure the clearance (CLrCYP) of a CYP-selective probe. The probe is then assayed in microsomes to obtain CLHLM and a correlation made of the relative levels of clearance in each system (RAF) for that particular CYP. Once established the RAFs for each CYP can be used to assess the relative contribution of the individual CYPs to the metabolism of a NCE in microsomes.
Highly diverse RAFs are generated between various institutions due to the variability of microsome batches, rCYP expression levels and assay conditions but as long as these variables are maintained within any given laboratory the RAFs should generate internally consistent data. However, whilst it has been known for some time that the promiscuity of CYPs may be facilitated by multiple binding regions in the active site (2), until recently no one has directly assessed the effect of probe choice on whether the scaling from rP450 to HLMs is consistent between various P450-selective probe reactions and those of the test NCE by that P450 isoform.
To demonstrate this issue Sui et al (3) generated RAFs for 2C9 and 3A4 from three CYP-selective probes each.
Using the RAF generated by one probe the predicted microsome clearance (CLHLM (p)) was calculated for the other two probes then compared with the directly measured CLHLM for those probes. This was performed in a crossover manner for each of the probes.
The CLrCYP and CLHLM were derived using standard Michaelis-Menton kinetics
The RAF was then generated as a ratio between CLHLM and CLrCYP.
In each crossover the CLHLM (p) was then simply calculated as the measured clearance of the test probe with rCYP multiplied by the RAF.
These predicted CLHLM(p) values were then subsequently compared with the actual measured CLHLM to give a value for the Intersystem Clearance Ratio (ICR)
Fig 1. Crossover analysis of ICRs based on the RAFs derived from A = Diclofenac, B = tolbutamide and C = Warfarin for 2C9 and D = Midazolam, E = Nifedipine and F = Testosterone for 3A4
Whilst it is clear to see the effects of probe choice on ICR this then has a knock on effect when determining the relative CYP contribution to the metabolism of a test NCE. Fig 2. Shows the comparison of % relative contributions for CYP metabolism of substrates with RAFs generated from various combinations of 2C9 and 3A4 probes (RAFs generated 1A2, 2C19, and 2D6 from single probe throughout)
Fig 2. Variations in relative CYP contribution (fm, fraction of total metabolism attributed to specific CYPs) calculations subject to probe choice
With Physiologically based pharmacokinetic (PBPK) modelling and simulation playing an increasingly large role in drug development the accuracy of the input data is therefore crucial to the predictive accuracy of a model. Here, the generation of fm is demonstrably affected by probe choice and if the RAFs for a given probe/CYP pair are not appropriate for the test NCE, deviations in fm from the true value may significantly impact, for instance, generation of risk assessments for drugs as potential DDI victims.
This study would suggest that for test NCEs, fm should be generated using various combinations of a limited number of CYP-specific probes which represent the full range of specific substrate binding sites for a given CYP. Presently our understanding of CYP binding site multiplicity is limited although studies indicate that we may soon have probe/inhibitor pairs for discreet pharmacophores (4, 5) facilitating increased accuracy of fm prediction.
Blog written by Marcus Hanley
- Clarke S. E. (1998) In vitro assessment of human cytochrome P450. xenobiotica, 1998, vol. 28, no. 12, 1167-1202
- Korzekwa, K R (1998) Evaluation of atypical cytochrome P450 kinetics with two-substrate models: evidence that multiple substrates can simultaneously bind to cytochrome P450 active sites. Biochemistry, 24 March 1998, Vol.37(12), pp.4137-47
- Siu Y.A (2017) Impact of Probe Substrate Selection on Cytochrome P450 ReactionPhenotyping Using the Relative Activity Factor. Drug Metab Dispos 45:183–189
- Kumar V. (2006) CYP2C9 Inhibition: Impact of Probe Selection and Pharmacogenetics on in Vitro Inhibition Profiles. Drug Metab Dispos Vol. 34 (12):1966-1975
- Foti R.S. (2008) CYP2C19 Inhibition: The Impact of Substrate Probe Selection on in Vitro Inhibition Profiles. Drug Metab Dispos Vol. 36 (3): 523-528