The Use of ROC Analysis for the Qualitative Prediction of Human Oral Bioavailability from Animal Data

PURPOSE: To develop and evaluate a tool for the qualitative prediction of human oral bioavailability (F(human)) from animal oral bioavailability (F(animal)) data employing ROC analysis and to identify the optimal thresholds for such predictions. METHODS: A dataset of 184 compounds with known F(human) and F(animal) in at least one species (mouse, rat, dog and non-human primates (NHP)) was employed. A binary classification model for F(human) was built by setting a threshold for high/low F(human) at 50%. The thresholds for high/low F(animal) were varied from 0 to 100 to generate the ROC curves. Optimal thresholds were derived from ‘cost analysis’ and the outcomes with respect to false negative and false positive predictions were analyzed against the BDDCS class distributions. RESULTS: We successfully built ROC curves for the combined dataset and per individual species. Optimal F(animal) thresholds were found to be 67% (mouse), 22% (rat), 58% (dog), 35% (NHP) and 47% (combined dataset). No significant trends were observed when sub-categorizing the outcomes by the BDDCS. CONCLUSIONS: F(animal) can predict high/low F(human) with adequate sensitivity and specificity. This methodology and associated thresholds can be employed as part of decisions related to planning necessary studies during development of new drug candidates and lead selection. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11095-013-1193-2) contains supplementary material, which is available to authorized users

Hepatic, Intestinal, Renal, and Plasma Hydrolysis of Prodrugs in Human, Cynomolgus Monkey, Dog, and Rat: Implications for In Vitro–In Vivo Extrapolation of Clearance of Prodrugs

Hydrolysis plays an important role in metabolic activation of prodrugs. In the current study, species and in vitro system differences in hepatic and extrahepatic hydrolysis were investigated for 11 prodrugs. Ten prodrugs in the data set are predominantly hydrolyzed by carboxylesterases (CES), whereas olmesartan medoxomil is also metabolized by carboxymethylenebutenolidase (CMBL) and paraoxonase. Metabolic stabilities were assessed in cryopreserved hepatocytes, liver S9 (LS9), intestinal S9 (IS9), kidney S9 (KS9), and plasma from human, monkey, dog, and rat. Of all the preclinical species investigated, monkey intrinsic hydrolysis clearance obtained in hepatocytes (CL int,hepatocytes) were the most comparable to human hepatocyte data. Perindopril and candesartan cilexetil showed the lowest and highest CL int,hepatocytes, respectively, regardless of the species investigated. Scaled intrinsic hydrolysis clearance obtained in LS9 were generally higher than CLint,hepatocytes in all species investigated, with the exception of dog. In the case of human and dog intestinal S9, hydrolysis intrinsic clearance could not be obtained for CES1 substrates, but hydrolysis for CES2 and CMBL substrates was detected in IS9 and KS9 from all species. Pronounced species differences were observed in plasma; hydrolysis of CES substrates was only evident in rat. Predictability of human hepatic intrinsic clearance (CLint,h) was assessed for eight CES1 substrates using hepatocytes and LS9; extrahepatic hydrolysis was not considered due to high stability of these prodrugs in intestinal and kidney S9. On average, predicted oral CLint,h from hepatocyte data represented 20% of the observed value; the underprediction was pronounced for highclearance prodrugs, consistent with the predictability of cytochrome P450/conjugation clearance from this system. Prediction bias was less apparent with LS9, in particular for high-clearance prodrugs, highlighting the application of this in vitro system for investigation of prodrugs. Copyright © 2014 by The American Society for Pharmacology and Experimental Therapeutics

Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations

Development of sub-models of organs within physiologically-based pharmacokinetic (PBPK) principles and beyond simple perfusion limitations may be challenging because of underdeveloped in vitro-in vivo extrapolation approaches or lack of suitable clinical data for model refinement. However, the advantage of such models in predicting clinical observations in divergent patient groups is now commonly acknowledged. Mechanistic understanding of altered renal secretion in renal impairment is one area that may benefit from such models, despite knowledge gaps in renal pathophysiology (Rowland Yeo et al., 2011; Sayama et al., 2014). In the current study a PBPK kidney model was developed for digoxin, accounting for the roles of organic anion transporting peptide 4C1 (OATP4C1) and P-glycoprotein (P-gp) in its tubular secretion, with the aim to investigate the impact of age and renal impairment (moderate to severe) on renal drug disposition. Initial PBPK simulations based on changes in glomerular filtration rate (GFR) underestimated the observed reduction in digoxin renal excretion clearance (CLR) in subjects with moderately impaired renal function relative to healthy. Reduction in either proximal tubule cell number or the OATP4C1 abundance in the mechanistic kidney model successfully predicted 59% decrease in digoxin CLR, in particular when these changes were proportional to reduction in GFR. In contrast, predicted proximal tubule concentration of digoxin was only sensitive to changes in the transporter expression/ million proximal tubule cells. Based on the mechanistic modelling, reduced proximal tubule cellularity and OATP4C1 abundance, and inhibition of OATP4C1-mediated transport, are proposed as possible causes of reduced digoxin renal secretion in renally impaired patients