Interspecies scaling of biliary excreted drugs

Mechanistic study on the species differences in excretion pathway of HR011303 in human and rats

Excretion of [¹⁴C]HR011303-derived radioactivity showed significant species difference. Urine (81.50% of dose) was the main excretion route in healthy male subjects, whereas feces (87.16% of dose) was the main excretion route in rats. To further elucidate the underlying cause for excretion species differences of HR011303, studies were conducted to uncover its metabolism and excretion mechanism. M5, a glucuronide metabolite of HR011303, is the main metabolite in humans and rats. Results of rat microsomes incubation study suggested that HR011303 was metabolized to M5 in the rat liver. According to previous studies, M5 is produced in both human liver and kidney microsomes. We found M5 in human liver can be transported to the blood by multidrug resistance-associated protein (MRP) 3 and then the majority of M5 can be hydrolyzed to HR011303. HR011303 enters the human kidney or liver through passive diffusion, whereas M5 is taken up through organic anion transporter (OAT) 3, organic anion-transporting polypeptide (OATP) 1B1, and OATP1B3. When HR011303 alone was present, it can be metabolized to M5 in both sandwich-cultured rat hepatocytes (SCRH) and sandwich-cultured human hepatocytes (SCHH) and excreted into bile as M5 in SCRH. Using transporter inhibitors in sandwich-cultured model and membrane vesicles that expressing MRP2 or Mrp2, we found M5 was substance of MRP2/Mrp2 and the bile efflux of M5 mainly mediated by MRP2/Mrp2. Considering the significant role of MRP3/Mrp3 and MRP2/Mrp2 in the excretion of glucuronides, the competition between them for M5 was possibly the determinant for the different excretion routes in humans and rats. Significance Statement Animal experiments are necessary to predict dosage and safety of candidate drugs prior to clinical trials. However, extrapolation results often differ from actual situation. For HR011303, excretory pathways exhibited a complete reversal, through urine in humans and feces in rats. Such phenomena have been observed in several drugs, but no in-depth studies have been conducted to date. In the present study, the excretion species differences of HR011303 can be explained by the competition for M5 between MRP2/Mrp2 and MRP3/Mrp3.

Interpretation of Non-Clinical Data for Prediction of Human Pharmacokinetic Parameters: In Vitro-In Vivo Extrapolation and Allometric Scaling

Extrapolation of pharmacokinetic (PK) parameters from in vitro or in vivo animal to human is one of the main tasks in the drug development process. Translational approaches provide evidence for go or no-go decision-making during drug discovery and the development process, and the prediction of human PKs prior to the first-in-human clinical trials. In vitro-in vivo extrapolation and allometric scaling are the choice of method for projection to human situations. Although these methods are useful tools for the estimation of PK parameters, it is a challenge to apply these methods since underlying biochemical, mathematical, physiological, and background knowledge of PKs are required. In addition, it is difficult to select an appropriate methodology depending on the data available. Therefore, this review covers the principles of PK parameters pertaining to the clearance, volume of distribution, elimination half-life, absorption rate constant, and prediction method from the original idea to recently developed models in order to introduce optimal models for the prediction of PK parameters.

Human pharmacokinetics of ginkgo terpene lactones and impact of carboxylation in blood on their platelet-activating factor antagonistic activity

Terpene lactones are a class of bioactive constituents of standardized preparations of Ginkgo biloba leaf extract, extensively used as add-on therapies in patients with ischemic cardiovascular and cerebrovascular diseases. This investigation evaluated human pharmacokinetics of ginkgo terpene lactones and impact of their carboxylation in blood. Human subjects received oral YinXing-TongZhi tablet or intravenous ShuXueNing, two standardized ginkgo preparations. Their plasma protein-binding and platelet-activating factor antagonistic activity were assessed in vitro. Their carboxylation was assessed in phosphate-buffered saline (pH 7.4) and in human plasma. After dosing YinXing-TongZhi tablet, ginkgolides A and B and bilobalide exhibited significantly higher systemic exposure levels than ginkgolides C and J; after dosing ShuXueNing, ginkgolides A, B, C, and J exhibited high exposure levels. The compounds' unbound fractions in plasma were 45-92%. Apparent oral bioavailability of ginkgolides A and B was mostly >100%, while that of ginkgolides C and J was 6-15%. Bilobalide's bioavailability was probably high but lower than that of ginkgolides A/B. Terminal half-lives of ginkgolides A, B, and C (4-7 h) after dosing ShuXueNing were shorter than their respective values (6-13 h) after dosing YinXing-TongZhi tablet. Half-life of bilobalide after dosing the tablet was around 5 h. Terpene lactones were roughly evenly distributed in various body fluids and tissues; glomerular-filtration-based renal excretion was the predominant elimination route for the ginkgolides and a major route for bilobalide. Terpene lactones circulated as trilactones and monocarboxylates. Carboxylation reduced platelet-activating factor antagonistic activity of ginkgolides A, B, and C. Ginkgolide J, bilobalide, and ginkgo flavonoids exhibited no such bioactivity. Collectively, differences in terpene lactones' exposure between the two preparations and influence of their carboxylation in blood should be considered in investigating the relative contributions of terpene lactones to ginkgo preparations' therapeutic effects. The results here will inform rational clinical use of ginkgo preparations.

Role of enterohepatic recirculation in drug disposition: cooperation and complications

Enterohepatic recirculation (EHC) concerns many physiological processes and notably affects pharmacokinetic parameters such as plasma half-life and AUC as well as estimates of bioavailability of drugs. Also, EHC plays a detrimental role as the compounds/drugs are allowed to recycle. An in-depth comprehension of this phenomenon and its consequences on the pharmacological effects of affected drugs is important and decisive in the design and development of new candidate drugs. EHC of a compound/drug occurs by biliary excretion and intestinal reabsorption, sometimes with hepatic conjugation and intestinal deconjugation. EHC leads to prolonged elimination half-life of the drugs, altered pharmacokinetics and pharmacodynamics. Study of the EHC of any drug is complicated due to unavailability of the apposite model, sophisticated procedures and ethical concerns. Different in vitro and in vivo methods for studies in experimental animals and humans have been devised, each having its own merits and demerits. Involvement of the different transporters in biliary excretion, intra- and inter-species, pathological and biochemical variabilities obscure the study of the phenomenon. Modeling of drugs undergoing EHC has always been intricate and exigent models have been exploited to interpret the pharmacokinetic profiles of drugs witnessing multiple peaks due to EHC. Here, we critically appraise the mechanisms of bile formation, factors affecting biliary drug elimination, methods to estimate biliary excretion of drugs, EHC, multiple peak phenomenon and its modeling.

Systematic Evaluation of Wajima Superposition (Steady-State Concentration to Mean Residence Time) in the Estimation of Human Intravenous Pharmacokinetic Profile

We present a systematic evaluation of the Wajima superpositioning method to estimate the human intravenous (i.v.) pharmacokinetic (PK) profile based on a set of 54 marketed drugs with diverse structure and range of physicochemical properties. We illustrate the use of average of "best methods" for the prediction of clearance (CL) and volume of distribution at steady state (VDss) as described in our earlier work (Lombardo F, Waters NJ, Argikar UA, et al. J Clin Pharmacol. 2013;53(2):178-191; Lombardo F, Waters NJ, Argikar UA, et al. J Clin Pharmacol. 2013;53(2):167-177). These methods provided much more accurate prediction of human PK parameters, yielding 88% and 70% of the prediction within 2-fold error for VDss and CL, respectively. The prediction of human i.v. profile using Wajima superpositioning of rat, dog, and monkey time-concentration profiles was tested against the observed human i.v. PK using fold error statistics. The results showed that 63% of the compounds yielded a geometric mean of fold error below 2-fold, and an additional 19% yielded a geometric mean of fold error between 2- and 3-fold, leaving only 18% of the compounds with a relatively poor prediction. Our results showed that good superposition was observed in any case, demonstrating the predictive value of the Wajima approach, and that the cause of poor prediction of human i.v. profile was mainly due to the poorly predicted CL value, while VDss prediction had a minor impact on the accuracy of human i.v. profile prediction.

Characterization of preclinical in vitro and in vivo pharmacokinetics properties for KBP-7018, a new tyrosine kinase inhibitor candidate for treatment of idiopathic pulmonary fibrosis

KBP-7018 is a novel selective tyrosine kinase inhibitor with potential for the treatment of idiopathic pulmonary fibrosis. The objective of this study was to characterize the preclinical pharmacokinetics of KBP-7018 in vitro and in vivo, and then to assess the likelihood of developing KBP-7018 as a clinical candidate. The systemic clearance (CL) of KBP-7018 was relatively low in rodents and monkeys with a value of less than 30% of hepatic blood flow, while it was high in dogs. The steady-state volume of distribution (V_ss) ranged from 1.51 L/kg to 4.65 L/kg across the species tested. The maximum concentration (C_max) of KBP-7018 occurred at 0.25–6 hours after oral dosing, and the bioavailability was moderate (21%–68%). The human CL (~20% of hepatic blood flow) and V_ss (1.6–5.3 L/kg) were predicted by allometric scaling method and together with the other modeling methods indicated low metabolism and acceptable half-time (4.8–19.3 hours) in vivo. Overall, the preclinical data make it amenable to further oral solid dosage from design for the upcoming Phase I trials in human.

The application of allometric scaling principles to predict pharmacokinetic parameters across species

INTRODUCTION

Interspecies allometric scaling provides a simple and fast option to interpolate or extrapolate drug dose or pharmacokinetic parameters to a species of interest. Over the years, new scaling methods have been developed in order to improve the performance of these predictions. It is critical to choose appropriate allometric scaling approach(es) to analyze the available pharmacokinetic data.

AREAS COVERED

This review provides updated information on the latest allometric scaling methods developed for the most frequently interpolated or extrapolated pharmacokinetic parameters. The different degrees of success and advantages/disadvantages of different methods are compared and contrasted. The pitfalls that affect the accuracy of prediction and the solutions to avoid the risk of prediction errors are discussed. The application of allometric scaling in veterinary medicine is presented.

EXPERT OPINION

Although interspecies allometric scaling needs further refinements and has limitations, it is still a potential tool and rational option for the estimate of pharmacokinetic parameters in species for which there are no data available or to better interpret preclinical efficacy and safety trials. Allometric scaling can offer insight into possible mechanisms of species-dependent drug disposition.

Dose selection based on physiologically based pharmacokinetic (PBPK) approaches

Physiologically based pharmacokinetic (PBPK) models are built using differential equations to describe the physiology/anatomy of different biological systems. Readily available in vitro and in vivo preclinical data can be incorporated into these models to not only estimate pharmacokinetic (PK) parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. They provide a mechanistic framework to understand and extrapolate PK and dose across in vitro and in vivo systems and across different species, populations and disease states. Using small molecule and large molecule examples from the literature and our own company, we have shown how PBPK techniques can be utilised for human PK and dose prediction. Such approaches have the potential to increase efficiency, reduce the need for animal studies, replace clinical trials and increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however some limitations need to be addressed to realise its application and utility more broadly.

Comparative assessment of In Vitro-In Vivo extrapolation methods used for predicting hepatic metabolic clearance of drugs

The purpose of this study was to perform a comparative analysis of various in vitro--in vivo extrapolation (IVIVE) methods used for predicting hepatic metabolic clearance (CL) of drugs on the basis of intrinsic CL data determined in microsomes. Five IVIVE methods were evaluated: the "conventional and conventional bias-corrected methods" using the unbound fraction in plasma (fu(p) ), the "Berezhkovskiy method" in which the fu(p) is adjusted for drug ionization, the "Poulin et al. method" using the unbound fraction in liver (fu(liver) ), and the "direct scaling method," which does not consider any binding corrections. We investigated the effects of the following scenarios on the prediction of CL: the use of preclinical or human datasets, the extent of plasma protein binding, the magnitude of CL in vivo, and the extent of drug disposition based on biopharmaceutics drug disposition classification system (BDDCS) categorization. A large and diverse dataset of 139 compounds was collected, including those from the literature and in house from Genentech. The results of this study confirm that the Poulin et al. method is robust and showed the greatest accuracy as compared with the other IVIVE methods in the majority of prediction scenarios studied here. The difference across the prediction methods is most pronounced for (a) albumin-bound drugs, (b) highly bound drugs, and (c) low CL drugs. Predictions of CL showed relevant interspecies differences for BDDCS class 2 compounds; the direct scaling method showed the greatest predictivity for these compounds, particularly for a reduced dataset in rat that have unexpectedly high CL in vivo. This result is a reflection of the direct scaling method's natural tendency to overpredict the true metabolic CL. Overall, this study should facilitate the use of IVIVE correlation methods in physiologically based pharmacokinetics (PBPK) model.

Approaches for predicting human pharmacokinetics using interspecies pharmacokinetic scaling

Reliably predicting pharmacokinetic behavior in humans from preclinical data is an important aspect of drug development. The most widely used technique in this regard is allometric scaling. In this review, various approaches developed for predicting pharmacokinetic parameters in humans using interspecies scaling are introduced and discussed. Methods to predict plasma concentration-time profiles in humans after intravenous and oral administration are also reviewed. The reliable prediction of human pharmacokinetics with regard to investigational drugs is aimed, ultimately, at selecting the first in-human dose with which to begin clinical studies. Approaches for the selection of the first in-human dose are also reviewed. Although there have been many trials to compare and optimize interspecies scaling methods, no firm conclusions have been reached. Because interspecies scaling methods are still highly empirical, further effort is needed to improve the reliability of predicting human pharmacokinetics by interspecies scaling.

Prediction of human oral plasma concentration-time profiles using preclinical data: comparative evaluation of prediction approaches in early pharmaceutical discovery

BACKGROUND AND OBJECTIVES

Empirically based methods remain one of our tools in human pharmacokinetic predictions. The Dedrick approach and the steady-state plasma drug concentration (C(ss))-mean residence time (MRT) approach are based on the assumption that concentration-time profiles are similar among species, including man, and that curves derived from a variety of animal species can be superimposed after mathematical transformation. In the Dedrick approach the transformation is based on the slope and intercept of the allometric relationship. The C(ss)-MRT approach is based on the implementation of measured animal and predicted human MRT and dose/volume of distribution at steady state (V(ss)). The aims of the present study were to compare the predictive performance of concentration-time profiles obtained by these approaches, to evaluate the prediction of individual pharmacokinetic parameters by these approaches and to further refine these approaches incorporating the experience from our previous work.

METHODS

A retrospective analysis using 35 proprietary compounds developed at Johnson & Johnson Pharmaceutical Research and Development was conducted to compare the accuracies of the Dedrick and C(ss)-MRT approaches for predicting oral concentration-time profiles and pharmacokinetic parameters in man. In the first step, input for the transformation was based on simple allometry. Then we assessed whether both methods could be fine-tuned by systematically incorporating correction factors (maximum life span potential, brain weight and plasma protein binding), depending on the interspecies relationship. In addition, for the C(ss)-MRT approach, we used formulas based on multivariate regression analysis as input for the transformation.

RESULTS

Inclusion of correction factors significantly improved the profile predictability for the Dedrick and C(ss)-MRT approaches. This was mainly linked to an improved prediction of terminal elimination half-life (t(½)), MRT and the ratio between the maximum plasma concentration and the concentration at the last observed time point (C(max)/C(last)). No significant differences were observed between the Dedrick approach with correction factors, the C(ss)-MRT approach with correction factors and the C(ss)-MRT approach, based on the regression equations.

CONCLUSIONS

Based on the dataset evaluated in this study, we demonstrated that human plasma concentration-time profiles and pharmacokinetic parameters could be predicted with the Dedrick and C(ss)-MRT approaches and that if correction factors were implemented, the predictions improved significantly. With the requirement of only a limited preclinical in vivo pharmacokinetic dataset, these empirical methods could offer potential in the early stages of drug discovery.

Intravenous prediction of human pharmacokinetic parameters for ketorolac, a non-steroidal anti-inflammatory agent, using allometry approach

The intravenous pharmacokinetics data of ketorolac in mice, rats, rabbits, dogs and monkeys were assembled from literature. The relationship between the main pharmacokinetic parameters [viz., volume of distribution (V (d)) and clearance (CL)] and body weight was studied across five mammalian species, using double-logarithmic plots to predict the human pharmacokinetic parameters of CL and V (d) using simple allometry or with correction factors [maximum life span potential (MLP), brain weight, CF1 (bile flow/liver weight) and CF2 (bile flow/body weight)]. The metabolism pattern, biotransformation pathways and the predominant urinary excretion of parent and the formed metabolites of ketorolac were found to be similar amongst mice, rats, rabbits, dogs, monkeys and humans, facilitating the scaling process. The human parameter value for V (d) was predicted by simple allometric equation: 0.2481W(1.0549) (r (2) = 0.9217). The predicted V (d) value (21.92 L) is close to the reported value (17.5 L), whereas the CL was predicted by simple allometric approach or with standard correction factors viz., MLP, brain weight, CF1 and CF2. Best proximity CL value was obtained with MLP having allometric equation: 0.7126W(1.3264) (r (2) = 0.9640). The outcome of this exercise suggests that allometric scaling with suitable correction factors could potentially be used to predict the human pharmacokinetic parameters of drugs belonging to non-steroidal anti-inflammatory drugs retrospectively.

Prediction of pharmacokinetic profile of valsartan in humans based on in vitro uptake-transport data

The aim of this study was to evaluate a physiologically based pharmacokinetic (PBPK) model for predicting PK profiles in humans based on a model refined in rats and humans in vitro uptake-transport data using valsartan as a probe substrate. Valsartan is eliminated unchanged, mostly through biliary excretion, both in humans and rats. It was, therefore, chosen as model compound to predict in vivo elimination based on in vitro hepatic uptake-transport data using a fully mechanistic PBPK model. Plated rat and human hepatocytes, and cell lines overexpressing human OATP1B1 and OATP1B3 were used for in vitro uptake experiments. A mechanistic two-compartment model was used to derive the active and passive transport parameters, namely uptake Michaelis-Menten parameters (V(max) and K(m,u)) together with passive diffusion (P(dif)). These transport parameters were then used as input in a whole body physiologically based pharmacokinetic (PBPK) model. The uptake rate of valsartan was higher for rat hepatocytes (K(m,u)=28.4+/-3.7 microM, V(max)=1320+/-180 pmol/mg/min, and P(dif) =1.21+/-0.42 microl/mg/min) compared to human hepatocytes (K(m,u)=44.4+/-14.6 microM, V(max)=304+/-85 pmol/mg/min, and P(dif)=0.724+/-0.271 microl/mg/min). OATP1B1 and -1B3 parameters were correlated to human hepatocyte data, using experimentally established relative activity factors (RAF). Resulting PBPK simulations were compared for plasma- (humans and rats) and bile- (rats) concentration-time profiles following iv bolus administration of valsartan. Plasma clearances (CL(P)) for rats and humans were predicted within twofold relative to predictions based on respective in vitro data. The simulations were extended to simulate the impact of either OATP1B1 or -1B3 inhibition on plasma profile. The limited data set indicates that the mechanistic model allowed for accurate evaluation of in vitro transport data; and the resulting hepatic uptake transport kinetic parameters enabled the prediction of in vivo PK profiles and plasma clearances, using PBPK modelling. Moreover, the interspecies difference in elimination rate observed in vivo was correctly reflected in the transport parameters determined in vitro.

Physiologically based pharmacokinetics (PBPK)

Allometric scaling is widely used to predict human pharmacokinetic parameters from preclinical species, and many different approaches have been proposed over the years to improve its predictive performance. Nevertheless, prediction errors are commonly observed in the practical application of simple allometry, for example, in cases where the hepatic metabolic clearance is mainly determined by enzyme activities, which do not scale allometrically across species. Therefore, if good correlation was noted for some drugs, poor correlation was observed for others, highlighting the need for other conceptual approaches. Physiologically based pharmacokinetic (PBPK) models are now a well-established approach to conduct extrapolations across species and to generate simulations of pharmacokinetic profiles under various physiological conditions. While conventional pharmacokinetic models are defined by drug-related data themselves, PBPK models have richer information content and integrate information from various sources, including drug-dependent, physiological, and biological parameters as they vary in between species, subjects, or with age and disease state. Therefore, the biological and mechanistic bases of PBPK models allow the extrapolation of the kinetic behavior of drugs with regard to dose, route, and species. In addition, by providing a link between tissue concentrations and toxicological or pharmacological effects, PBPK modeling represents a framework for mechanistic pharmacokinetic-pharmacodynamic models.

Prediction of human pharmacokinetics-biliary and intestinal clearance and enterohepatic circulation

The main objective was to evaluate and propose methods for predicting biliary clearance (CL(bile)) and enterohepatic circulation (EHC) of intact drugs in man. Another aim was to evaluate to role of intestinal drug secretion and propose a method for prediction of intestinal secretion CL (CL(i)). Animal data poorly predict the CL and CL(bile) of biliary excreted drugs, and the suggested molecular weight threshold for bile excretion as the dominant elimination route does not seem to hold. Active transport, low metabolic intrinsic CL (CL(int)) and, as an approximation, permeability (P(e)) less than that of metoprolol is required for substantial CL(bile) to occur. The typical EHC plasma concentration vs time profile (multiple peaks) is demonstrated for many low metabolic CL(int)-compounds with efflux and moderate to high intestinal P(e) and fraction absorbed. Physiologically-based in-vitro to in-vivo (PB-IVIV) methodology with in-vitro intrinsic CL(bile)-data obtained with sandwich-cultured human hepatocytes has generated 2- and 5-fold underpredictions for two compounds with intermediate to high CL(bile). This is despite not considering the unbound fraction. Possible explanations include low transporter activity and diffusion limitations in the in-vitro experiments. Intestinal reabsorption and EHC were also neglected in these predictions and in-vivo CL(bile) estimations. The sandwich model and these reference data are still very useful. Consideration of an empirical scaling factor and a newly developed approach that accounts for intestinal reabsorption and EHC could potentially lead to improved PB-IVIV predictions of CL(bile). Apparently, no attempts have been made to predict CL(i). Elimination via the intestinal route does not appear to be of great importance for the few compounds with available data, but could be equally as important as bile excretion. Net secretion in-vitro P(e) and newly estimated in-vivo intrinsic CL(i) data for digoxin and rosuvastatin could be useful for approximation of CL(i) of other compounds.

Identification of interspecies difference in efflux transporters of hepatocytes from dog, rat, monkey and human

The large interspecies differences of hepatobiliary transport present a challenge for the allometric prediction of human biliary excretion for drug candidates primarily cleared via hepatobiliary secretion. In the present study, we determined the metabolic stabilities of common fluorescent substrates of hepatobiliary efflux transporters and developed a rapid efflux assay to determine the functional activities of MRP/Mrp, BCRP/Bcrp and P-gp in hepatocytes of four species. The specificities of transporter-mediated dye efflux were confirmed by selective transporter inhibitors. Among tested species, transporter-specific dye efflux kinetics was consistent between freshly isolated and cryopreserved hepatocytes. Hepatocyte elimination half-lives of MRP/Mrp substrates GS-MF and calcein were observed in the rank order of human>monkey>dog>rat. The fourfold higher MRP/Mrp substrate efflux rate of rat hepatocytes compared to human is likely due to the species-specific functional differences of MRP2/Mrp2 expressed on the canalicular membrane. We also observed efficient BCRP-mediated pheophorbide A (PhA) efflux by human and dog hepatocytes, while PhA extrusion in monkey and rat hepatocytes appeared limited. P-gp function measured by DiOC2(3) efflux was minimal in hepatocytes of all origins and no significant species differences were detected. Our results demonstrated marked differences in hepatocyte MRP/Mrp and BCRP/Bcrp activities across species, indicating that they may contribute to the species differences of in vivo hepatobiliary excretion. These results also suggest the potential utility of primary hepatocytes, either fresh or cryopreserved, as an in vitro model to predict interspecies differences in the biliary transport of MRP/Mrp and BCRP/Bcrp substrates.

Preclinical pharmacokinetics and interspecies scaling of ragaglitazar, a novel biliary excreted PPAR dual activator

Allometric scaling has been used as an effective tool for the prediction of human pharmacokinetic parameters. Allometry has been a useful approach for the analysis of compounds that are eliminated unchanged in the urine and/or exhibit similar metabolic patterns across species. However, it has been a challenging issue to correctly predict human pharmacokinetic parameters for drugs that are eliminated intact and/or as conjugates in the bile. Ragaglitazar is a novel, non-thiazolidinedione peroxisome proliferator-activated receptor (PPAR) alpha- and gamma-agonist. In our investigation, preclinical pharmacokinetic data on ragaglitazar were gathered for several animal species (mice, rats, rabbits and dogs). Ragaglitazar when administered orally has shown a low clearance rate (Cl/F; < 5% of hepatic blood flow) in mice, rats and rabbits and a moderately high Cl/F in dogs (> 15% of hepatic blood flow). A qualitative estimation of rat bile has unequivocally confirmed the elimination of ragaglitazar in the bile. The human pharmacokinetic data are also indicative of the involvement of enterohepatic biliary recycling. In order to predict key parameters such as Cl/F and volume of distribution (V/F), simple allometry was the approach adopted at the onset. Although V/F scaled adequately, it failed to accurately predict human Cl/F. Therefore, standard correction factors such as maximum life span potential (MLP) and brain weight were also included. Although such modifications improved the linearity (r2 > 0.9), they failed to predict the investigated values. Further incorporation of correction factors particularly relevant to biliary excreted drugs improved the prediction of these values. Interestingly, the exclusion of dog data from the interspecies scaling considerably improved the prediction of both Cl/F and V/F.

Issues in the pharmacokinetics of trichloroethylene and its metabolites

Much progress has been made in understanding the complex pharmacokinetics of trichloroethylene (TCE) . Qualitatively, it is clear that TCE is metabolized to multiple metabolites either locally or into systemic circulation. Many of these metabolites are thought to have toxicologic importance. In addition, efforts to develop physiologically based pharmacokinetic (PBPK) models have led to a better quantitative assessment of the dosimetry of TCE and several of its metabolites. As part of a mini-monograph on key issues in the health risk assessment of TCE, this article is a review of a number of the current scientific issues in TCE pharmacokinetics and recent PBPK modeling efforts with a focus on literature published since 2000. Particular attention is paid to factors affecting PBPK modeling for application to risk assessment. Recent TCE PBPK modeling efforts, coupled with methodologic advances in characterizing uncertainty and variability, suggest that rigorous application of PBPK modeling to TCE risk assessment appears feasible at least for TCE and its major oxidative metabolites trichloroacetic acid and trichloroethanol. However, a number of basic structural hypotheses such as enterohepatic recirculation, plasma binding, and flow- or diffusion-limited treatment of tissue distribution require additional evaluation and analysis. Moreover, there are a number of metabolites of potential toxicologic interest, such as chloral, dichloroacetic acid, and those derived from glutathione conjugation, for which reliable pharmacokinetic data is sparse because of analytical difficulties or low concentrations in systemic circulation. It will be a challenge to develop reliable dosimetry for such cases.

A global examination of allometric scaling for predicting human drug clearance and the prediction of large vertical allometry**This work was presented at the American Association of Pharmaceutical Scientists Annual meeting, Salt Lake City, USA, Oct. 26, 2003

Allometrically scaled data sets (138 compounds) used for predicting human clearance were obtained from the literature. Our analyses of these data have led to four observations. (1) The current data do not provide strong evidence that systemic clearance (CL(s); n = 102) is more predictable than apparent oral clearance (CL(po); n = 24), but caution needs to be applied because of potential CL(po) prediction error caused by differences in bioavailability across species. (2) CL(s) of proteins (n = 10) can be more accurately predicted than that of non-protein chemicals (n = 102). (3) CL(s) is more predictable for compounds eliminated by renal or biliary excretion (n = 33) than by metabolism (n = 57). (4) CL(s) predictability for hepatically eliminated compounds followed the order: high CL (n = 11) > intermediate CL (n = 17) > low CL (n = 29). All examples of large vertical allometry (% error of prediction greater than 1000%) occurred only when predicting human CL(s) of drugs having very low CL(s). A qualitative analysis revealed the application of two potential rules for predicting the occurrence of large vertical allometry: (1) ratio of unbound fraction of drug in plasma (f(u)) between rats and humans greater than 5; (2) C logP greater than 2. Metabolic elimination could also serve as an additional indicator for expecting large vertical allometry.

ACCURACY OF ALLOMETRICALLY PREDICTED PHARMACOKINETIC PARAMETERS IN HUMANS: ROLE OF SPECIES SELECTION

A general equation was derived, which directly describes the mathematical relationship between the allometrically predicted pharmacokinetic (PK) parameters in humans and the body weights of animal species (along with their corresponding measured PK parameters). It was shown, with use of the derived equation, that the predicted values in humans, based on combinations of animal species commonly used in allometry, are heavily dependent on certain species, for example, the dog. In contrast, parameter values from the rat made no contribution to the predicted human values, as long as the rat was not the smallest species used. Monte Carlo simulations were further performed to examine the species or weight dependence. The cost-effective combinations of animal species, in terms of number and species type, were theoretically examined through simulations. Finally, literature data demonstrated the species or weight dependence predicted from the equation and as illustrated through the Monte Carlo simulations. Appreciation of this species or weight dependence should guide researchers in selecting animal species and designing optimal experiments in the application of allometric scaling.

Interspecies Scaling of Biliary Excreted Drugs: A Comparison of Several Methods**The views expressed in this article are those of the author and do not reflect the official policy of the FDA. No official support or endorsement by the FDA is intended or should be inferred

The objective of this study was to evaluate the predictive performance of several methods of interspecies scaling for the prediction of human clearance of drugs which are excreted in the bile. Ten methods of allometric scaling were used to predict human clearance of biliary excreted drugs from animal data. The methods included the simple allometric approach; the rule of exponents; the rule of exponents with a correction factor; the ratio of human and monkey liver blood flow x monkey clearance; product of clearance and bile flow; product of clearance and UDGPT; product of clearance, bile flow, and UDGPT; and a modified version of the last three approaches in association with the rule of exponents. The results of the study indicate that among these ten approaches, the rule of exponents with the correction factor is the best approach for the prediction of human clearance for drugs which are excreted in the bile. The worst approach is the product of clearance, bile flow, and UDGPT. The simple allometry and the monkey liver blood flow (MLBF) approaches gave almost similar results. For some drugs the simple allometry predicted clearance better than the MLBF approach and vice versa.

A comprehensive analysis of the role of correction factors in the allometric predictivity of clearance from rat, dog, and monkey to humans

This study was conducted to comprehensively evaluate the performance of various allometric scaling methods for the prediction of human clearance. Allometric scaling was used to predict clearance for 103 compounds, for which clearance data in the rat, dog, monkey, and humans were available. Allometry was performed using all three preclinical species and with combinations of any two species. The methods employed included standard allometry and various correction factors, including brain weight, maximum lifespan potential, and glomerular filtration. Scaling was performed on all compounds universally and on segregated subsets based on allometric exponent, clearance, physicochemical property, or route of elimination. 776 allometric combinations with 27,313 individual outcomes were performed. A predicted-to-observed clearance ratio of 0.5 to twofold was preselected as the criterion for predictive success. The success rate of allometric scaling ranged from 18 to 53%; none of the correction factors resulted in substantially improved predictivity. Furthermore, none of the methods attempted in this study achieved a success rate greater than that observed by simply estimating human clearance based on monkey hepatic extraction. Prospective allometric scaling, with or without correction factors, represents a suboptimal technique for estimating human clearance based on in vivo preclinical data.

Physiologically based pharmacokinetic (PBPK) modeling of disposition of epiroprim in humans

The objective of this study was to use in synergy physiologically based and empirical approaches to estimate the drug-specific input parameters of PBPK models of disposition to simulate the plasma concentration-time profile of epiroprim in human. The estimated input parameters were the tissue:plasma partition coefficients (Pt:p) for distribution and the blood clearance (CL) for the in vivo conditions. Epiroprim represents a challenge for such methods, because it shows large interspecies differences in its pharmacokinetic properties. Two approaches were used to predict the human Pt:p values: the tissue composition model (TCM) and the "Arundel approach" based on the volume of distribution at steady state (Vdss) determined in vivo in the rat. CL in human was predicted by (1) conventional allometric scaling of in vivo animal clearances (CAS), (2) physiologically based direct scaling up of in vitro hepatocyte data (DSU), and (3) allometric scaling of animal intrinsic in vivo blood CL normalized by the ratios of animal:human intrinsic clearances determined in vitro with hepatocytes (NAS). The performance of prediction was assessed by comparing separately the above pharmacokinetic parameters (Vdss estimated from the Pt:p values and blood CL) with the corresponding in vivo data obtained from the plasma kinetic profiles. These input parameters were used in PBPK models, and the resulting plasma concentration-time profiles of epiroprim were compared with those observed in rat and human. Previously to the construction of the human PBPK model, a model for the rat was also developed to gain more confidence on the model structure and assumptions. Overall, using the TCM and the NAS for the parameterization of the distribution and clearance, respectively, the PBPK model gave the more accurate predictions of epiroprim's disposition in human. This study represents therefore an attractive approach, which may potentially help the clinical candidate selection.

A COMPREHENSIVE QUANTITATIVE AND QUALITATIVE EVALUATION OF EXTRAPOLATION OF INTRAVENOUS PHARMACOKINETIC PARAMETERS FROM RAT, DOG, AND MONKEY TO HUMANS. I. CLEARANCE

This study was conducted to comprehensively survey the available literature on intravenous pharmacokinetic parameters in the rat, dog, monkey, and human, and to compare common methods for extrapolation of clearance, to identify the most appropriate species to use in pharmacokinetic lead optimization, and to ascertain whether adequate prospective measures of predictive success are currently available. One hundred three nonpeptide xenobiotics were identified with intravenous pharmacokinetic data in rat, dog, monkey, and human; both body weight- and hepatic blood flow-based methods were used for scaling of clearance. Allometric scaling approaches, particularly those using data from only two of the preclinical species, were less successful at predicting human clearance than methods based on clearance as a set fraction of liver blood flow from an individual species. Furthermore, commonly used prospective measures of allometric scaling success, including correlation coefficient and allometric exponent, failed to discriminate between successful and failed allometric predictions. In all instances, the monkey tended to provide the most qualitatively and quantitatively accurate predictions of human clearance and also afforded the least biased predictions compared with other species. Additionally, the availability of data from both common nonrodent species (dog and monkey) did not ensure enhanced predictive quality compared with having only monkey data. The observations in this investigation have major implications for pharmacokinetic lead optimization and for prediction of human clearance from in vivo preclinical data and support the continued use of nonhuman primates in preclinical pharmacokinetics.

Interspecies Scaling of Protein Drugs: Prediction of Clearance from Animals to Humans

The objective of this study was to evaluate the interspecies scaling for therapeutic protein drugs to predict the systemic clearance in humans from animal data. This study was undertaken to examine whether the rule of exponents of Mahmood and Balian for the prediction of clearance of nonprotein drugs can also be extended to macromolecules. Three different methods were used to predict clearance in humans: (1). clearance versus body weight (simple allometry), (2). the product of clearance and maximum life-span potential (MLP) versus body weight, and (3). the product of clearance and brain weight versus body weight. Data from 15 therapeutic proteins were analyzed, and the results indicated that the clearance of protein drugs can be predicted accurately using simple allometry or brain weight depending on the exponents of the simple allometry. Furthermore, these 15 drugs were scaled up using two species and the predicted clearance was compared with the predicted clearance obtained from more than two species. It was found that more than two species are needed for a reliable prediction of clearance.