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Prediction of Vitreal Half-Life Based on Drug Physicochemical Properties: Quantitative Structure–Pharmacokinetic Relationships (QSPKR)

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Abstract

Purpose

The aim of this study was to develop quantitative structure pharmacokinetic relationships (QSPKR) to correlate drug physicochemical properties (molecular weight, lipophilicity, and drug solubility), dose, salt form factor, and eye pigmentation factor to intravitreal half-life in the rabbit model.

Methods

Dataset derived from prior literature reports, which included molecules with complete structural diversity, was used to develop the QSPKR models. Entire dataset as well as subsets limited to albino rabbit data, pigmented rabbit data, acids, bases, zwitterions, neutral compounds, suspensions, and macromolecules were analyzed. Multiple linear regression analysis was carried out with noncollinear independent variables and the best-fit models were selected based on correlation coefficients and goodness of fit statistics.

Results

The analysis indicated that logarithm of MW (Log MW), lipophilicity (Log P or Log D) and dose number (dose/solubility at pH 7.4), are the most critical determinants of intravitreal half-life of the compounds analyzed. The best-fit models obtained from the entire dataset (Log t 1/2 = −0.178 + 0.267 Log MW − 0.093 Log D + 0.003 dose/solubility at pH 7.4 + 0.153 Pigmentation Factor and Log t 1/2 = −0.32 + 0.432 Log MW − 0.157 Log P + 0.003 dose/solubility at pH 7.4) predicted the various subsets well. Pigmented dataset and zwitterions were better predicted by Log P rather than Log D.

Conclusions

The present study confirmed that intravitreal half-life could be better predicted by a group of variables (Log MW, Log P or Log D, dose number) rather than a single variable. In general, increasing Log MW and dose number, while reducing Log D or Log P would be beneficial for prolonging intravitreal half-life of drugs.

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Acknowledgements

This work was supported by a grant from Pfizer Global Research and Development, Groton, CT, USA. The authors acknowledge Dr. Jane Meza (Biostatistics department of UNMC) for her critical review of the manuscript.

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  1. Department of Pharmaceutical Sciences, University of Colorado Denver, 4200 East 9th Avenue, C-238, Denver, CO, 80262, USA

    Chandrasekar Durairaj & Uday B. Kompella

  2. Department of Ophthalmology, University of Colorado Denver, Denver, CO, 80262, USA

    Uday B. Kompella

  3. Pfizer Global Research and Development, Groton, CT, 06340, USA

    Jaymin C. Shah

  4. Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA

    Shruti Senapati

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Durairaj, C., Shah, J.C., Senapati, S. et al. Prediction of Vitreal Half-Life Based on Drug Physicochemical Properties: Quantitative Structure–Pharmacokinetic Relationships (QSPKR). Pharm Res 26, 1236–1260 (2009). https://doi.org/10.1007/s11095-008-9728-7

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