Abstract

QUANTITATIVE STRUCTURE – PHARMACOKINETICS RELATIONSHIP FOR THE STEADY STATE VOLUME OF DISTRIBUTION OF BASIC AND NEUTRAL DRUGS

*Zvetanka Zhivkova

ABSTRACT

Objective: The success of new drug candidates is critically dependent on its pharmacokinetic (PK) behavior. Therefore the early prediction of PK parameters of new drug candidates became a vital step of drug development process. The study presents a new quantitative structure – pharmacokinetics relationship (QSPkR) for prediction of Vss for neutral and basic drugs. Methods: The dataset consisted of 407 drugs, separated into training set (n = 339) and external test set (n = 68). Chemical structures were encoded by 130 theoretical descriptors. Genetic algorithm and step wise multiple linear regression were applied for model generation. The models were evaluated by internal and external validation. Results: Significant, predictive and interpretable QSPkR model was developed with explained variance r2 = 0.547, cross-validated correlation coefficients q2LOO-CV = 0.505 and q2LGO-CV=0.519, external test set predictive coefficient r2pred = 0.556 and geometric mean fold error of prediction GMFEP = 1.89. The model was able to predict the Vss for 69% of the drugs in the external test set within the 2-fold error of experimental values. Conclusions: The model reveals the main molecular features governing Vss. Lipophilicity, basicity and the presence of aromatic rings contribute positively to Vss, while polarity, molecular size and hydrogen bonding ability disfavor Vss. The model shows fairly good predictivity for moderate and high-Vss drugs (with Vss in the range 0.7 – 10 L/kg) and poor performance for extremely high-Vss drugs which follow unique distribution patterns.

Keywords: QSPkR, steady state volume of distribution, ADME prediction.