Special Report Regression modeling strategy for prediction of AUC of evogliptin, a novel dipeptidyl peptidase IV inhibitor in humans, using single dose PK data Poonam Giri 1 , Shuchi Joshi 1 & Nuggehally R Srinivas* ,1 1 Department of Drug Metabolism & Pharmacokinetics, Zydus Research Centre, Cadila Healthcare Ltd, Ahmedabad 382 210, India * Author for correspondence: nuggehally.srinivas@zyduscadila.com Aim: To develop a limited regression model of evogliptin for prediction of AUC data for internal (within study) and external studies. Method: Regression analyses (linear/power/polynomial) were performed in multitiered approach using paired peak plasma concentration (C max ) versus AUC data of evogliptin. For all models, correlation co-effcient (r) and root mean square error (%RMSE) were used in predicting internal/external data. Bland–Altman analysis was performed for all the models. Results: Limited power model showed highest predictability (r = >0.98 and ≤15.5% RMSE), followed by linear model (r = >0.98 and ≤20.5% RMSE) and polynomial (r = >0.96 and ≤27.0% RMSE). Bland–Altman plots confrmed accept- able bias and precision. Conclusion: Limited regression models were successfully developed for prediction of AUC of evogliptin. First draft submitted: 20 July 2017; Accepted for publication: 1 December 2017; Published online: 7 March 2018 Keywords: Bland–Altman • correlation co-effcient • healthy subjects • limited regression model • prediction of AUC • root mean square error Despite the availability of scores of medicines, Type 2 diabetes mellitus continues to be a dreaded disease because of a progressive deterioration of functional pancreas accompanied by various degrees of insulin desen- sitization which impede effective glucose metabolism [1–3]. In this context, following the first introduction of gliptins (i.e., sitagliptin), many other gliptins have followed suit with each providing some degree of potency and pharmacokinetic differentiation although mechanism of action has remained the same (Table 1) [4–12]. Evogliptin, a new entrant to the field of gliptins, has demonstrated superior in vitro potency associated with high selectivity for the inhibition of DPP-4 enzyme and excellent in vivo efficacy in various animal models of Type 2 diabetes mellitus [13–17]. Following oral administration in humans, evogliptin attains peak plasma concentrations (C max ) within 3.5–5.5 h suggesting relatively rapid absorption of the drug [18]. Moreover, both C max and area under the plasma concentration versus time curve (AUC) were reported to be dose proportional in humans between 1.25 and 60 mg, representing a 50-fold dose range [18]. Upon repeated oral administration, a minor accumulation of evogliptin was observed (1.35–1.5-fold) and steady state was achieved within three days of oral dosing [19]. The elimination half-life of 32.9 h adequately supported once daily dosing of evogliptin and with a urinary excretion of 34% of evogliptin; it suggested that nonrenal elimination pathways were important for the disposition of evogliptin [19]. The pharmacokinetics of evogliptin was reported to be less influenced by concomitant food ingestion and therefore, oral dosing of evogliptin can occur in fasted or fed state [18]. Since, evogliptin exhibited ideal pharmacokinetic behaviour in terms of dose proportional increase in peak plasma concentration (C max ) and AUC values; consistent attainment of C max within a narrow range of 3.5–5.5 h; minor accumulation after daily dosing, we thought that evogliptin would represent an ideal substrate that may be amenable for AUC prediction using a limited time point strategy such as C max . Previously, limited time point strategy has been successfully applied for other drugs such as pravastatin, simvastatin, linezolid, fexofenadine, itraconazole, losartan, micafungin, among others [23–32]. Int. J. Pharmacokinet. (2018) 3(1), 23–38 ISSN 2053-0846 23 10.4155/ipk-2017-0015 C  2018 Future Science Ltd For reprint orders, please contact reprints@future-science.com