ESTIMATING INTESTINAL PERMEABILITY BY SURFACE ACTIVITY PROFILING

Kevin Kiehm1, Marcus Brewster2, Jef Peeters2, Jennifer B. Dressman1
1 Department of Pharmaceutical Technology, Johann Wolfgang Goethe University, Frankfurt, Germany
2 Johnson & Johnson, Pharmaceutical Research and development, Beerse, Belgium

1 Department of Pharmaceutical Technology, Johann Wolfgang Goethe University, Frankfurt, Germany2 Johnson & Johnson, Pharmaceutical Research and development, Beerse, Belgium

 

INTRODUCTION

Estimating intestinal permeability of new drug entities is an important biopharmaceutical parameter in drug discovery. Due to the increase in lead substances in drug discovery, fast and effective methods are required to predict oral absorption.

An in vitro assay based on surface activity profiling was developed to evaluate passive transcellular gastrointestinal permeability. The amphiphilic properties of a drug, as reflected by its surface activity, can then be correlated to their interactions with the lipid bilayer in biological membranes1.

A training set of structurally diverse, well characterized drugs with known absorption properties was selected. The ability of drugs to interact with the air/water interface was investigated by surface tension measurements. These measurements were carried out on a novel multichannel microtensiometer. This instrument allows rapid determination of the thermodynamic properties of compounds at the air/water interface. The surface activity (air/water partitioning) of the drugs was then quantified using the Gibbs adsorption isotherm and correlated with oral absorption data for the drugs.

Since the hydrophobic effect is responsible for the adsorption at the air/water interface the data received was then compared with log P values, which are commonly used as a predictor of transmembrane permeability2.


MATERIALS AND METHODS 

Materials

The drug substances acyclovir, amitriptyline, atenolol, captopril, cimetidine, diphenydramine, diltiazem, furosemide, ibuprofen, metoclopramide, miconazole, paracetamol, propranolol, ranitidine, sulfasalazine, sulpiride were purchased from Sigma-Aldrich, Germany.

All other chemicals were analytical grade and purchased commercially.


Selection of Model Drugs

The drugs were chosen to cover a wide range of absorption after oral administration as well as a wide range of physicochemical properties such as lipophilicity, charge and molecular size.

Only drugs with reliable data on the absorbed fraction in humans and clear indications that the drugs were predominantly absorbed by passive processes were selected.


Solubility Studies

Thermodynamical solubility was determined for all substances in Simulated Intestinal Fluid (phosphate buffer pH 6.8 50mM). A saturated solution of the drug was formed by shake flask method at 20°C.

After 12h and 24h the pH of the solution was checked and readjusted again to pH 6.8. After equilibrium the samples were filtered and the concentration of the compounds were quantified by UV spectroscopy.


Surface Activity Measurements

Surface tension measurements were carried out on a multichannel microtensiometer (Delta-8, Kibron Inc.) This instrument is designed for high throughput screening and enables the measurement of 98 samples in 2 minutes.

The measurement is based on the Du Nuoy maximum pull principle, using instead of a ring, fine needles to record the maximum pull force exerted by the surface tension. A dilution series of 11 concentrations of each compound was prepared in Simulated Intestinal Fluid. The highest concentration was chosen according to the solubility measurements. Dilution ratio was 1:1. All measurements were done at 20±0.5°C and for each solute concentration 3 samples were measured. Sample volume was 50μl per well. Equilibrium time was 15 minutes to achieve a sufficient partitioning of the compounds between bulk and surface.


Analysis of the Adsorption Isotherm

The maximum surface excess Γmax is determined from the Gibbs adsorption isotherm.

 

Surface excess is the concentration of a surfactant at the surface in excess of the bulk concentration and can be determined by measuring the surface tension for different bulk concentrations.


Γ : surface excess
C: concentration of the drug compound
RT: is the thermal energy per molecule
: surface tension subject to bulk concentration


RESULTS AND DISCUSSION



Table 1. Compound ADME properties


a human fraction absorbed data, taken from the literature
b log P data, taken from the literature
c for drugs which have reached the CMC, bulk concentration is equal to the critical micelle          concentration

The compounds investigated are summarized in Table 1. The fraction absorbed and log P data was taken from the literature. The maximum surface concentration log Γmax was calculated according to the Gibbs equation by using the highest concentration and the corresponding maximum surface pressure of the compound.

For compounds which formed micelles, the critical micelle concentration and the maximum surface pressure was used instead.


Figure 2 shows the lack of correlation of intestinal absorption with log P. In contrast, a linear relationship of human intestinal absorption and log Γmax was found (Figure 1).

Figure 1. Relationship between fraction absorbed of the drug compounds and their maximum surface concentration

Figure 2. Relationship between fraction absorbed of the drug compounds and their log P value.

 

CONCLUSIONS

The results indicate that surface activity profiling can be used to distinguish between poorly and well absorbed drugs. The use of the novel multichannel microtensiometer provides a suitable screening technique in terms of both accuracy and throughput. The results suggest that the proposed assay may be an alternative tool for permeability screening of new drug candidates.


REFERENCES

[1] Surface Activity Profiling of Drugs Applied to Predict of Blood-Brain Barrier Permeabilty, Suomalainen P, Johans C, Soderlund T, Kinnunen PK., J Med Chem. 2004 Mar 25;47(7):1783-8

[2] Correlation of human jejunal permeability (in vivo) of drugs with experimentally and theoretically derived parameters. A multivariate data analysis approach.„ Winiwarter, S., N. M. Bonham, et al. (1998). " J Med Chem 41(25): 4939-49

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