Microsomal stability assay

Microsomal stability assay protocol

Data from Cyprotex's Microsomal Stability Assay

Figure 1
Comparison of CL_int values generated in 3 separate assays, based on mean CL_int (n=3) per assay. Incubations performed using human liver microsomes 0.5 mg/ml, 0.1 M phosphate buffer pH 7.4, 1 mM NADPH, 1 µM substrate concentration. The graph illustrates the reproducibility of the assay, inter-assay co-efficient of variation was 20.2% (8.5% excluding compounds with CL_int <10.6 µL/min/mg (limit of quantification)).

*CL_int values generated for compound outside of axis range (860, 872, 947).

Figure 2
In vitro/in vivo clearance correlation in Cyprotex’s human microsomal stability assay. In vitro CL_int data, for 22 literature compounds including acid, base and neutral compounds, was scaled (predicted CL_int,ub) and compared to values of in vivo intrinsic clearance back-calculated from observed in vivo clearance using the well-stirred model.

Dashed line shows line of regression. Dotted lines show 2-fold and 3-fold range from unity line (solid).

A range of literature compounds were assessed in the Cyprotex microsomal stability assay (1 µM, 45 minute incubation, n=3 assays) and intrinsic clearance (CL_int µL/min/10⁶ cells) determined. Predicted in vivo CL_int (mL/min/kg) values were calculated using a microsomal protein value of 40 mg/g liver, a human liver weight of 25.7 g liver/kg³ and taking into account fu_inc (fraction unbound in vitro incubation)⁴. Observed in vivo CL_int,ub were back-calculated from observed microsomal clearance using the well-stirred model, published intravenous human blood clearance values, human liver blood flow of 20.7 ml/min/kg and f_ub (fraction unbound in blood)⁴. A 2-3 fold under prediction of in vivo clearance was observed in human liver microsomes consistent with other reports in the literature⁵.

Questions and answers on microsomal stability

Explain the benefits of using liver microsomes for drug metabolism studies?

The liver is the main organ of drug metabolism in the body. Subcellular fractions such as liver microsomes are useful in vitro models of hepatic clearance as they contain many of the drug metabolizing enzymes found in the liver. Microsomes are easy to prepare and can be stored for long periods of time. They are easily adaptable to high throughput screens which enable large numbers of compounds to be screened rapidly and inexpensively.

Please provide an overview of Cyprotex's microsomal stability assay.

Liver microsomes are incubated with the test compound at 37°C in the presence of the co-factor, NADPH, which initiates the reaction. Samples are removed at the appropriate time points and the reaction is terminated by the addition of acetonitrile. Following centrifugation, internal standard is added to the supernatant which is analysed by LC-MS/MS. The disappearance of test compound is monitored over a 45 minute time period. An example of a typical depletion profile is shown in Figure 3.

Figure 3
Graph shows test compound disappearance with time in the presence of liver microsomes.

The ln peak area ratio (compound peak area/internal standard peak area) is plotted against time and the gradient of the line determined, where percent remaining is the compound ratio (compound peak area divided by internal standard peak area) as a percentage of the 0 minute time point. The following equations are used when analysing data from this assay:

How do I interpret the data from the microsomal stability assay?

The data can be used in several ways:

1. The compounds can be ranked in terms of their intrinsic clearance values. Unless the compound is a pro-drug, very highly cleared compounds are generally considered to be unfavourable as they are likely to be rapidly cleared in vivo resulting in a short duration of action. Classification bands can be used to categorise compounds into low, medium or high clearance. The CL_int classification bands for each species in Table 1 are calculated from a rearrangement of the well stirred model⁶ detailed in the following equation assuming an extraction ratio (E) of 0.3 and 0.7 for the low and high boundaries, respectively. This can then be scaled to intrinsic clearance (mL/min/kg) using the relevant liver weights³ and microsomal protein concentration^7,8 obtained from the literature. Due to lack of literature information, monkey and mouse microsomal protein concentration values of 32 and 45 mg microsomal protein/g liver were assumed, to match human and rat respectively. For simplicity, fu has been assumed to be 1, this represents the worst case scenario and where compounds are more highly plasma protein bound less stringent criteria would apply.

2. The data can be used in conjunction with other in vitro parameters to predict the pharmacokinetics of a compound in vivo (available through Cyprotex’s PK prediction service).

3. Species specific differences in drug metabolism can be investigated. This may be useful in identifying an appropriate species for pre-clinical development.

Why might microsomal CL_int data under predict in vivo clearance?

There are several reasons why hepatic microsomal CL_int data may under predict in vivo clearance:

1. The important metabolic fates for the compound are not present or activated in microsomes supplemented with NADPH e.g. UGT conjugation or cytosolic aldehyde oxidation.

2. Other tissues may also contribute to test compound metabolism e.g. intestine or kidney.

3. Other clearance routes, e.g. renal excretion of test compound, are important in the total drug clearance.

In addition, several laboratories have noted there is a systematic under-prediction of in vivo clearance from human liver microsome stability data even for drugs cleared predominantly by CYP mediated hepatic metabolism. Causes of the under-prediction have not been defined and are potentially multifactorial, in light of this several laboratories have proposed empirical approaches to correct the observed bias and improve the accuracy of clearance predictions ^{9, 10}.

Why would I screen my compounds in the microsomal stability assay rather than the hepatocyte stability assay?

Microsomes are adaptable to high throughput screening and enable large numbers of compounds to be screened inexpensively. Our clients tend to use this assay as an initial screen to rank order compounds of interest in terms of their metabolic stability, and then perform a secondary screen on a smaller number of selected compounds using hepatocytes.

What controls are used in the assay?

• A minimum of two positive control compounds are included for each species and is dependent on the type of protein and cofactor used.

• A control incubation is performed in the absence of cofactor to reveal any chemical instability or non-NADPH dependent enzymatic degradation.

• A control is included that contains all reaction components with the exception of the test compound. This control identifies any potential interfering component which may affect the analysis.

Can I investigate Phase II metabolism in liver microsomes?

The microsomal stability assay is primarily used to investigate Phase I metabolism using NADPH as the enzyme co-factor. However liver microsomes can also be used to study Phase II metabolism if the correct incubation conditions are used. We have recently validated this using the pore forming agent alamethicin in conjunction with appropriate Phase II cofactors for example UDPGA. This allows you to gain an understanding as to the contribution Phase II metabolism has on the overall metabolism of a test compound. It is also possible to study coupled Phase I and Phase II metabolism by using all of the relevant co-factors in the incubation.

¹ LeCluyse EL and Alexandre E (2010) Isolation and culture of primary hepatocytes from resected human liver tissue Methods Mol Biol 640; 57-82
² Obach RS. (1999) Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: an examination of in vitro half-life approach and nonspecific binding to microsomes Drug Metab Dispos 27(11); 1350-1359
³ Davies B. and Morris T. (1993) Physiological parameters in laboratory animals and humans Pharma Res 10(7); 1093-1095
⁴ Riley RJ et al. (2005) A unified model for predicting human hepatic, metabolic clearance from in vitro intrinsic clearance data in hepatocytes and microsomes Drug Metab Dispos 33; 1304-1311
⁵ Wood FL et al. (2005) Clearance prediction methodology needs fundamental improvement: trends common to rat and human hepatocytes/microsomes and implications for experimental methodology Drug Metab Dispos 45(11); 1178-1188
⁶ Houston JB (1994) Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance Biochem Pharmacol 47(9); 1469-1479
⁷ Barter ZE et al. (2007) Curr Drug Metab 8(1); 33-45
⁸ Sohlenius-Sternbeck AK et al. (2010) Evaluation of the human prediction of clearance from hepatocyte and microsome intrinsic clearance for 52 drug compounds Xenobiotica 40(9); 637-649
⁹ Iwatsubo T et al. (1997) Prediction of species differences (rats, dogs, humans) in the in vivo metabolic clearance of YM796 by the liver from in vitro data JPET 283(2); 462-469
¹⁰ Poulin P et al. (2012) In vitro–in vivo extrapolation of clearance: modeling hepatic metabolic clearance of highly bound drugs and comparative assessment with existing calculation methods J Pharm Sci 101(2); 838-851