Drug development is a very laborious, expensive and time consuming process. Inadequate pharmacokinetic knowledge on the drug candidate is one of the reasons for failure during drug development. The in-vivo absorbability of drugs categorized as BCS Class II is very difficult to predict because of the large variability in the absorption or dissolution kinetics. Urapidil comes under the category of BCS Class II. Thus, present study was aimed to assess the influence of covariates on pharmacokinetics of Urapidil from typical pharmacokinetics studies using population pharmacokinetic model. In this study one compartment model incorporating subject specific parameters was developed and evaluated. Results demonstrated that the one compartment absorption model without lag time under first order estimation method best describes the pharmacokinetics of Urapidil. The final model described the body weight influence on apparent oral clearance of Urapidil and 27.60% of the inter-individual variability was explained by the covariate body weight. Thus, it can be concluded that body weight was found to be the most important covariate for clearance of Urapidil. The projected model shall further developed in patients treated for Urapidil and results from this study should interpret cautiously while any dose adjustment for Urapidil treatment in patient population.

The identification and quantification of covariates, particularly using population pharmacokinetics is now seen as an integral part of drug development. This present study was aimed to assess the influence of subject specific parameters (covariates) on pharmacokinetics of Eupressyl (Urapidil) from typical pharmacokinetics studies. The influence of covariates (age, height, body weight, body mass index) on the pharmacokinetics of Urapidil was evaluated analyzing the data pooled from three different pharmacokinetic studies. The influence of covariates on Urapidil pharmacokinetics was evaluated using linear mixed effect model. Covariate analysis was carried out following a two-stage approach. Results from the first stage analyses showed that there is no significant effect (P > 0.05) on Urapidil pharmacokinetic parameters against evaluated covariates. However, at second stage following linear mixed effect models, subject specific parameters were correlated with obtained pharmacokinetic parameters. The results evidencing that the reasonable influence of covariates on Urapidil pharmacokinetics parameters were observed for different lot of innovator products. Thus, characterizing effect of few of the covariates on pharmacokinetics outcome will definitely reduce the number of pharmacokinetic studies using healthy human subjects and also development time and cost in generic drug developments. However, further pharmacokinetic models for Urapidil to be developed and validated using non-linear mixed effectmodels, as it is considered one of the standard method for evaluating drug variability.