IOSR Journal of Pharmacy and Biological Sciences (IOSR-JPBS) e-ISSN: 2278-3008, p-ISSN:2319-7676. Volume 9, Issue 4 Ver. V (Jul -Aug. 2014), PP 22-29 www.iosrjournals.org www.iosrjournals.org 22 | Page Evaluation of Covariates Influence on Urapidil Pharmacokinetics using Non-Linear Mixed Effect Model M. Sundara Moorthi Nainar 1, 2 , K. Ravisekhar 1 , D.Prabakaran 3 , V. Saji 1 , T. Vijay 1 , S. Ashish 1 , V.Praveen Kumar 1 and R.Sikandar Ali Khan 1 1 (Lupin Bioresearch Center, Pune 411021, Maharashtra, India) 2 (PhD Research Scholar, Department of Pharmaceutical Sciences, Jawaharlal Nehru Technological University, Hyderabad - 500085, Andhra Pradesh, India) 3 (Ethics Biolabs, Chennai, Tamilnadu, India) Abstract: 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. Keywords: Covariates, Eupressyl, NLME, Urapidil, Variability I. Introduction Drug development is a very laborious and expensive process. One of the major reasons for failure during the clinical phases of drug development is inadequate pharmacokinetic data on the drug candidate [1]. Pharmacokinetic variability is most commonly responsible for adverse drug reactions and therapy failure due to low drug exposures [2, 3]. A number of factors can contribute to high variability in pharmacokinetic parameters [4]. The formulation factors that may impact on bioavailability and bioequivalence can be classified into two categories: (a) the first group belongs to factors that can affect drug dissolution or release which is considered as a prerequisite to the drug absorption process. (b) The second category comprises factors related to excipients or inactive ingredients which can influence drug stability, absorption and metabolism [5]. Population pharmacokinetics can be used to define the variability in plasma drug concentrations between individuals when standard dosage regimens are administered [6] and the identification and quantification of covariates, particularly using population pharmacokinetics is now seen as an integral part of drug development. However, many pharmaceutical companies go through unnecessary cycles of clinical studies involving formulation optimization without attention to the feasibility of reducing inter-individual variability and the source of such variation [7]. Many studies performed during drug development are aimed at identifying and quantifying between subject variability exhibit in drug exposure and response to improve the safety and efficacy of a drug agent. Variability is usually characterized in terms of fixed and random effects. The fixed effects are the population average values of pharmacokinetic parameters. The random effects quantify the amount of pharmacokinetic variability that is not explained by the fixed effects [8]. Knowledge of the variability of the biological systems is necessary to develop useful models. Thus, it is of crucial importance to identify the variables that contribute significantly in the process of drug absorption which will allow reliable predictions of drug absorption. Therefore integrated pharmacokinetic models take into account variables pertinent to pharmaceutical and physiological issues [5,9]. The advantages of population modeling include: a direct estimate of the population characteristics of pharmacokinetic parameters is obtained; studies can be modeled and optimized based on current knowledge; a smaller number of samples per individual, which is ethically desirable, can be used; combined analyses can be performed at the level of the raw data; complex models can be evaluated when data from many subjects are analyzed together [10]. 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 [11]. Urapidil comes under the category of BCS