Ghafourian, Taravat and Khavari-Khorasani, Tina and Dastmalchi, Siavoush and Barzegar-Jalali, Mohammad and Nokhodchi, Ali (2006) QSPR models for the prediction of apparent volume of distribution. International Journal of Pharmaceutics, 319 (1-2). pp. 82-97. ISSN 0378-5173. (doi:https://doi.org/10.1016/j.ijpharm.2006.03.043) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)
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An estimate of volume of distribution (Vd) is of paramount importance both in drug choice as well as maintenance and loading dose calculations in therapeutics. It can also be used in the prediction of drug biological half life. This study employs quantitative structure–pharmacokinetic relationship (QSPR) techniques for the prediction of volume of distribution. Values of Vd for 129 drugs were collated from the literature. Structural descriptors consisted of partitioning, quantum mechanical, molecular mechanical, and connectivity parameters calculated by specialized software and pKa values obtained from ACD labs/logD database. Genetic algorithm and stepwise regression analyses were used for variable selection and model development. Models were validated using a leave-many-out procedure. QSPR analyses resulted in a number of significant models for acidic and basic drugs separately, and for all the drugs. Validation studies showed that mean fold error of predictions for the selected models were between 1.79 and 2.17. Although separate QSPR models for acids and bases resulted in lower prediction errors than models for all the drugs, the external validation study showed a limited applicability for the equation obtained for acids. Therefore, the universal model that requires only calculated structural descriptors was recommended. The QSPR model is able to predict the volume of distribution of drugs belonging to different chemical classes with a prediction error similar to that of the other more complicated prediction methods including the commonly practiced interspecies scaling. The structural descriptors in the model can be interpreted based on the known mechanisms of distribution and the molecular structures of the drugs.
|Divisions:||Faculties > Sciences > Medway School of Pharmacy|
|Depositing User:||Ali Nokhodchi|
|Date Deposited:||05 Sep 2008 19:55 UTC|
|Last Modified:||28 Apr 2014 10:27 UTC|
|Resource URI:||https://kar.kent.ac.uk/id/eprint/11296 (The current URI for this page, for reference purposes)|