Prediction of the Corneal Permeability of Drug-Like Compounds

ABSTRACT

Purpose

To develop a computational model for optimisation of low corneal permeability, which is a key feature in ocular drug development.

Methods

We have used multivariate analysis to build corneal permeability models based on a structurally diverse set of 58 drug-like compounds.

Results

According to the models, the most important parameters for permeability are logD at physiologically relevant pH and the number of hydrogen bonds that can be formed. Combining these descriptors resulted in models with Q 2 and R 2 values ranging from 0.77 to 0.79. The predictive capability of the models was verified by estimating the corneal permeability of an external data set of 11 compounds and by using predicted permeability values to calculate the aqueous humour concentrations in the steady-state of seven compounds. The predicted values correlated well with experimental values.

Conclusion

The developed models are useful in early drug development to predict the corneal permeability and steady-state drug concentration in aqueous humor without experimental data.

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Abbreviations

Css :

steady-state concentration

HBA:

number of hydrogen bond acceptors

HBD:

number of hydrogen bond donors

HBtot :

total number of putative hydrogen bonds, i.e. HBD + HBA

logP:

the logarithm of the octanol-water partition coefficient of the neutral form

logperm :

the logarithm of the corneal permeability

logD7.0, logD7.4 and logD8.0 :

the logarithm of the octanol-water partition coefficient at pH 7.0, 7.4 and 8.0, respectively

MV:

molecular volume

MW:

molecular weight

PCA:

principal component analysis

PLS:

partial least squares

PSA:

polar surface area

QSPR:

quantitative structure-property relationship

RMSE:

root mean squared error

RMSEP:

root mean squared error of prediction

VIP:

variable importance in the projection

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ACKNOWLEDGEMENTS

This work was supported by the Academy of Finland. Heikki Käsnänen is thanked for valuable comments on the manuscript.

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Correspondence to Arto Urtti.

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Kidron, H., Vellonen, KS., del Amo, E.M. et al. Prediction of the Corneal Permeability of Drug-Like Compounds. Pharm Res 27, 1398–1407 (2010). https://doi.org/10.1007/s11095-010-0132-8

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KEY WORDS

  • computational model
  • multivariate analysis
  • ocular absorption
  • ophthalmic drugs
  • QSPR