Defense Date


Document Type


Degree Name

Doctor of Philosophy



First Advisor

Venitz Jurgen


This research developed validated QSPKR and PK-AS models for predicting human systemic PK properties of three, preselected, pharmacological classes of drugs, namely opioids, β-adrenergic receptor ligands (β-ARL) and β-lactam antibiotics (β-LAs) using pertinent human and animal systemic PK properties (fu,, CLtot, Vdss, fe) and their biologically relevant unbound counterparts from the published literature, followed by an assessment of the effect of different molecular descriptors on these PK properties and on the PK-AS slopes for CLtot and Vdss from two species (rat and dog). Lipophilicity (log (D)7.4) and molecular weight (MW) were found to be the most statistically significant and biologically plausible, molecular properties affecting the biologically relevant, systemic PK properties: For compounds with log (D)7.4 > -2.0 and MW < 350 D (e.g., most opioids and β-ARL), increased log (D)7.4 resulted in decreased fu and increased Vdssu, CLtotu and CLnonrenu, indicating the prevalence of hydrophobic interactions with biological membrane/proteins. As result, the final QSPKR models using log (D)7.4 provided acceptable predictions for fu, Vdssu, CLtotu and CLnonrenu. CLnonrenu and CLtotu. For both the datasets, inclusion of drugs undergoing extrahepatic clearance worsened the QSPKR predictions. For compounds with log (D)7.4 < -2.0 and MW > 350 D (e.g., β-LA), increased MW (leading to more hydrogen bond donors/acceptors) resulted in a decrease in fu, likely indicating hydrogen bonding interactions with plasma proteins. In general, it was more difficult to predict PK parameters for β-LAs, as their Vdssu approached plasma volume and CLrenu and CLnonrenu were low - as a result of their high hydrophilicity and large MW, requiring specific drug transporters for distribution and excretion. The PK-AS analysis showed that animal body size accounted for most of the observed variability (r2> 0.80) in systemic PK variables, with single species methods, particularly those using dog, gave the best predictions. The fu correction of PK variables improved goodness of fit and predictability of human PK. There were no apparent effects of molecular properties on the predictions. CLren, CLrenu, CLnonren, and CLnonrenu were the most difficult variables to predict, possibly due to the associated interspecies differences in the metabolism, renal and hepatobiliary drug transporters.


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