Integration of in vitro data into allometric scaling to predict hepatic metabolic clearance in man: application to 10 extensively metabolized drugs

Expression and characterization of functional dog flavin-containing monooxygenase 1

A full-length dog (beagle) flavin-containing monooxygenase 1 (FMO1) cDNA (dFMO1) was obtained from liver by reverse transcription-polymerase chain reaction. The amino acid sequence of dFMO1 was 89% homologous to human FMO1. Using a baculovirus expression system in Sf-9 insect cells, dFMO1 was expressed to protein levels of 0.4 nmol/mg, as determined by immunoquantitation. The flavin content of the expressed enzyme was consistent with immunodetectable dFMO1 protein levels. Expressed dFMO1 catalyzed NADPH-dependent methyl p-tolyl sulfide oxidation, with K(m) and V(max) values of 98.6 microM and 63.8 nmol of S-oxide formed/min/mg of protein, respectively. By comparison, human FMO1 showed similar values of 87.1 microM (K(m)) and 51.0 nmol/min/mg (V(max)). Activity for dFMO1 showed characteristic pH dependence, with a 4.5-fold increase in S-oxidase activity as the incubation pH increased from 7.6 to 9.0. Human FMO1 also showed an increase in reaction rate with pH but a somewhat lower optimum of 8.0 to 8.4. dFMO1 also catalyzed imipramine N-oxidation, with a K(m) of 4.7 microM and a V(max) of 82.1 nmol/min/mg of protein. This enzyme displayed other characteristics of FMO enzymes, with rapid depletion of enzyme activity upon heating in the absence of NADPH. Protein levels of 74 pmol of dFMO1/mg of microsomal protein were determined for a pooled liver microsome sample, suggesting that this enzyme is a major canine hepatic monooxygenase. In conclusion, the expression and characterization of catalytically active dFMO1 will allow the role of this enzyme in the metabolism of xenobiotics to be determined.

Prediction of clearance in humans from in vitro human liver microsomes and allometric scaling. A comparative study of the two approaches

The objective of this study was to evaluate whether the predicted clearance of a drug in humans from in vitro human liver microsomes was comparable with the predicted clearance in humans obtained by allometric scaling. Sixteen drugs were randomly selected from the literature and their hepatic clearances were predicted using human liver microsomes. For allometric scaling at least three animal species were used and three methods were utilized to generate allometric equations to predict the clearance in humans: (i) clearance vs body weight (simple allometry); (ii) product of the clearance and maximum life-span potential (MLP) vs body weight; and (iii) the product of clearance and brain weight vs body weight. The choice of one of the methods was based on the 'rule of exponents' as described by Mahmood and Balian /2,3/. The results of this study indicated that the use of human liver microsomes to predict hepatic clearance in humans may not provide reliable predictions. On the other hand, the prediction of clearance in humans using allometric scaling combined with the 'rule of exponents' can provide comparatively better prediction of clearance in humans.

The use of in vitro metabolic stability for rapid selection of compounds in early discovery based on their expected hepatic extraction ratios

PURPOSE

The in vivo hepatic extraction ratio of cynomolgus monkeys was correlated with the corresponding in vitro extraction ratios that were determined in monkey microsomal incubations.

METHOD

For compounds that are eliminated mainly through liver phase I metabolism, the extraction ratio calculated from liver microsomal stability studies should correlate with their in vivo hepatic extraction ratios and also with their oral bioavailability in monkey. We used both well-stirred and parallel tube models of intrinsic clearance for the correlation. We also calculated extraction ratios for compounds within a given therapeutic area from fraction absorbed values that were estimated from the Caco-2 absorption model.

RESULT

The present data show that in vitro extraction ratios in monkey microsomes are predictive of the in vivo hepatic extraction ratios in monkeys. All compounds with high extraction ratio (>70%) in vivo were successfully classified as high-extraction-ratio compounds based on the in vitro monkey microsomal stability data. From the results of this study, it appears that the parallel tube model provided a slightly better classification than the well-stirred model. CONCULUSIONS: The present method appears to be a valuable tool to rapidly screen and prioritize compounds with respect to liver first-pass metabolism in monkeys at an early phase of drug discovery.

Flavin-containing monooxygenase activity in hepatocytes and microsomes: in vitro characterization and in vivo scaling of benzydamine clearance

Liver microsomes, and more recently cryopreserved hepatocytes, are commonly used in the in vitro characterization of the metabolism of new xenobiotics. The flavin-containing monooxygenases (FMO) are a major non p450 oxidase present in liver microsomes and hepatocytes. Since FMO is known to be thermally labile, and this enzyme may be involved in the metabolic clearance of some drugs, we sought to more completely characterize the metabolic competency of this enzyme in cryopreserved hepatocytes and in liver microsomes preincubated under various conditions using benzydamine as an in vitro and in vivo probe. The metabolism of benzydamine to its major metabolite, the N-oxide, is mediated by FMO3 in humans. We found that the in vitro microsomal t(1/2) was 70% longer when incubations were prewarmed at 37 degrees C in the absence of NADPH compared with prewarming in the presence of an NADPH-regenerating system, and N-oxide formation was inhibited >99%. Interestingly, the in vivo clearance predicted from these incubations and from human hepatocytes overpredicted the observed clearance of benzydamine in humans (>10.5 versus 2.4 ml/min/kg). In contrast, rat hepatocytes successfully predicted rat in vivo benzydamine clearance to within approximately 30% (>68 versus 48 ml/min/kg). Benzydamine N-oxidation in liver microsomes from all common preclinical species demonstrated heat sensitivity. This information should be considered when extrapolating metabolism data of xenobiotics from these in vitro systems.

Comparison of SPE and fast LC to eliminate mass spectrometric matrix effects from microsomal incubation products

Twenty-seven highly diversified pharmaceutical compounds were used as a test set to evaluate matrix effects from microsomal media on LC/MS analyses. The individual effects of Tris buffer, NADPH and microsomes on ESI response were investigated. Direct flow injection MS/MS analysis, using no sample preparation or HPLC separation, gave an average of 2.2-5-fold matrix suppression in MS response from Tris buffer and NADPH. More polar analytes were affected the greatest. To reduce the loss in response, an automated solid phase extraction (SPE) procedure was developed. A much smaller average matrix effect was observed when samples were prepared using a Waters Oasis HLB 96-well SPE. As little as 1 ml of methanol (MeOH) was sufficient to elute most compounds with more than 80% recovery. Comparable results were obtained by directly injecting a protein-precipitated incubation onto a fast gradient LC separation prior to MS/MS detection. No advantage was seen by using both SPE and a fast LC separation prior to MS/MS analysis.

Prediction of hepatic metabolic clearance: comparison and assessment of prediction models

OBJECTIVE

To perform a comparative quantitative evaluation of the prediction accuracy for human hepatic metabolic clearance of 5 different mathematical models: allometric scaling (multiple species and rat only), physiologically based direct scaling, empirical in vitro-in vivo correlation, and supervised artificial neural networks.

METHODS

The mathematical prediction models were implemented with a publicly available dataset of 22 extensively metabolised compounds and compared for their prediction accuracy using 3 quality indicators: prediction error sum of squares (PRESS), r2 and the fold-error.

RESULTS

Approaches such as physiologically based direct scaling, empirical in vitro-in vivo correlation and artificial neural networks, which are based on in vitro data only, yielded an average fold-error ranging from 1.64 to 2.03 and r2 values greater than 0.77, as opposed to r2 values smaller than 0.44 when using allometric scaling combining in vivo and in vitro preclinical data. The percentage of successful predictions (less than 2-fold error) ranged from 55% (rat allometric scaling) to between 64 and 68% with the other approaches.

CONCLUSIONS

On the basis of a diverse set of 22 metabolised drug molecules, these studies showed that the most cost-effective and accurate approaches, such as physiologically based direct scaling and empirical in vitro-in vivo correlation, are based on in vitro data alone. Inclusion of in vivo preclinical data did not significantly improve prediction accuracy; the prediction accuracy of the allometric approaches was at the lower end of all methods compared.

Interspecies scaling: predicting oral clearance in humans

The objective of this study was to test the interspecies scaling approach for a wide variety of drugs to predict oral clearance in humans from animal data. This study is an attempt to evaluate whether the rule of exponents of Mahmood and Balian for the prediction of systemic clearance can also be applied for the prediction of oral clearance in humans. Three different methods were used to generate log-log plots to scale up the clearance values: (1) clearance versus body weight (simple allometric equation), (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 32 drugs were analyzed, and it was concluded that the oral clearance of drugs could be best predicted using one of the allometric equations.

Allometric scaling of xenobiotic clearance: uncertainty versus universality

Statistical analysis and Monte Carlo simulation were used to characterize uncertainty in the allometric exponent (b) of xenobiotic clearance (CL). CL values for 115 xenobiotics were from published studies in which at least 3 species were used for the purpose of interspecies comparison of pharmacokinetics. The b value for each xenobiotic was calculated along with its confidence interval (CI). For 24 xenobiotics (21%), there was no correlation between log CL and log body weight. For the other 91 cases, the mean +/- standard deviation of the b values was 0.74 +/- 0.16; range: 0.29 to 1.2. Most (81%) of these individual b values did not differ from either 0.67 or 0.75 at P = 0.05. When CL values for the subset of 91 substances were normalized to a common body weight coefficient (a), the b value for the 460 adjusted CL values was 0.74; the 99% CI was 0.71 to 0.76, which excluded 0.67. Monte Carlo simulation indicated that the wide range of observed b values could have resulted from random variability in CL values determined in a limited number of species, even though the underlying b value was 0.75. From the normalized CL values, four xenobiotic subgroups were examined: those that were (i) protein, and those that were (ii) eliminated mainly by renal excretion, (iii) by metabolism, or (iv) by renal excretion and metabolism combined. All subgroups except (ii) showed a b value not different from 0.75. The b value for the renal excretion subgroup (21 xenobiotics, 105 CL values) was 0.65, which differed from 0.75 but not from 0.67.

Prediction of drug clearance in humans from laboratory animals based on body surface area

The object of the study was to develop a new allometric equation for clearance from laboratory animals to humans based on body surface area (BSA allometric method). Human clearances for 30 drugs were predicted from animal data obtained from the literature. The results predicted with the method were compared with those observed. The results were also compared with values predicted with clearance versus body weight (BW simple allometric method), the product of brain weight and clearance versus body weight (Cl x BRW method) and the product of maximum life span potential and clearance versus body weight (Cl x MLP method), respectively. Good predictions were found in 21 out of 30 with the BAS allometric method. Both BSA allometric method and BW simple allometric method can give good predictions of clearance in humans for many drugs. Similarly to BW simple allometric method, Cl x BRW method and Cl x MLP method, BSA allometric method may be used to accurately predict human clearance from laboratory animal data.

Prediction of the disposition of midazolam in surgical patients by a physiologically based pharmacokinetic model

The aim of this study was to predict the disposition of midazolam in individual surgical patients by physiologically based pharmacokinetic (PBPK) modeling and explore the causes of interindividual variability. Tissue-plasma partition coefficients (k(p)) were scaled from rat to human values by a physiologically realistic four-compartment model for each tissue, incorporating the measured unbound fraction (f(u)) of midazolam in the plasma of each patient. Body composition (lean body mass versus adipose tissue) was then estimated in each patient, and the volume of distribution at steady state (V(dss)) of midazolam was calculated. Total clearance (CL) was calculated from unbound intrinsic CL, f(u), and estimated hepatic blood flow. Curves of midazolam plasma concentration versus time were finally predicted by means of a perfusion-limited PBPK model and compared with measured data. In a first study on 14 young patients undergoing surgery with modest blood loss, V(dss) was predicted with an only 3.4% mean error (range -24-+39%) and a correlation between predicted and measured values of 0.818 (p < 0.001). Scaling of k(p) values by the four-compartment model gave better predictions of V(dss) than scaling using unbound k(p). In the PBPK modeling, the mean +/- standard deviation (SD) prediction error for all data was 9.7 +/- 33%. In a second study with 10 elderly patients undergoing orthopedic surgery, hemodilution and blood loss led to a higher f(u) of midazolam. The PBPK modeling correctly predicted a marked increase in V(dss), a smaller increase in CL, and a prolonged terminal half-life of midazolam, as compared with findings in the first study. Interindividual variation in the disposition of midazolam could thus in part be related to the physiological characteristics of the patients and the f(u) of the drug in their plasma.

Interspecies scaling: is a priori knowledge of cytochrome p450 isozymes involved in drug metabolism helpful in prediction of clearance in humans from animal data?

The objective of this study was to evaluate whether a priori knowledge of cytochrome P450 isozymes involved in drug metabolism coupled with Mahmood' and Balian's 'rule of exponents' can be helpful for the prediction of clearance in humans using animal data. The clearance of 27 randomly selected drugs metabolized by different isozymes were scaled up from the animal data (at least three animal species) obtained from the literature. Three methods were utilized to generate allometric equations to scale up the clearance values: (i) clearance vs body weight (simple allometry); (ii) product of the clearance and maximum life-span potential (MLP) vs body weight; and (iii) the product of clearance and brain weight vs body weight. The choice of one of the methods was based on the 'rule of exponents' as described by Mahmood and Balian. The results of this study indicate that the knowledge of a particular isozyme does not provide a guide for the failure or success of allometry for the prediction of clearance. There is no trend which indicates that the chances of accurate prediction of clearance for a given drug are comparatively higher or lower when they are metabolized by a particular isozyme.

Implications and consequences of enzyme induction on preclinical and clinical drug development

1. Enzyme induction has traditionally been studied during drug development to assess the potential of drug entities to interact with concomitant medications and alter their pharmacological effects, and clearly it is an unwanted phenomenon. However, another hurdle caused by induction occurs during preclinical development via the attainment of safety data, obtained by dosing high quantities of compound to species used in toxicology assessment. This review considers the techniques that can now be utilized in drug discovery, their relevance, the pharmacokinetic aspects of this phenomenon, and it discusses the consequences and implications of induction during preclinical and clinical development. 2. It is becoming increasingly routine to employ hepatocyte cultures and novel techniques such as quantitative real-time reverse transcriptase PCR to identify enzyme inducers in vitro. The major challenge is to utilize these in vitro data to predict the consequences of induction in vivo. From an understanding of pharmacokinetic principles and low clinical doses relative to preclinical studies, there is limited potential for induction by a development candidate to significantly alter the pharmacological efficacy of a co-administered drug. 3. The most comprehensive approach when considering induction involves integrating quantitative in vitro data, information on the pharmacokinetic behaviour of the compound and the PK/PD) relationship in order to predict its consequences. The generation of this holistic strategy would enable more detailed and informed decision-making about both the suitability of molecules for development and the development strategy itself.

Progress in predicting human ADME parameters in silico

Understanding the development of a scientific approach is a valuable exercise in gauging the potential directions the process could take in the future. The relatively short history of applying computational methods to absorption, distribution, metabolism and excretion (ADME) can be split into defined periods. The first began in the 1960s and continued through the 1970s with the work of Corwin Hansch et al. Their models utilized small sets of in vivo ADME data. The second era from the 1980s through 1990s witnessed the widespread incorporation of in vitro approaches as surrogates of in vivo ADME studies. These approaches fostered the initiation and increase in interpretable computational ADME models available in the literature. The third era is the present were there are many literature data sets derived from in vitro data for absorption, drug-drug interactions (DDI), drug transporters and efflux pumps [P-glycoprotein (P-gp), MRP], intrinsic clearance and brain penetration, which can theoretically be used to predict the situation in vivo in humans. Combinatorial synthesis, high throughput screening and computational approaches have emerged as a result of continual pressure on pharmaceutical companies to accelerate drug discovery while decreasing drug development costs. The goal has become to reduce the drop-out rate of drug candidates in the latter, most expensive stages of drug development. This is accomplished by increasing the failure rate of candidate compounds in the preclinical stages and increasing the speed of nomination of likely clinical candidates. The industry now understands the reasons for clinical failure other than efficacy are mainly related to pharmacokinetics and toxicity. The late 1990s saw significant company investment in ADME and drug safety departments to assess properties such as metabolic stability, cytochrome P-450 inhibition, absorption and genotoxicity earlier in the drug discovery paradigm. The next logical step in this process is the evaluation of higher throughput data to determine if computational (in silico) models can be constructed and validated from it. Such models would allow an exponential increase in the number of compounds screened virtually for ADME parameters. A number of researchers have started to utilize in silico, in vitro and in vivo approaches in parallel to address intestinal permeability and cytochrome P-450-mediated DDI. This review will assess how computational approaches for ADME parameters have evolved and how they are likely to progress.

Allometric pharmacokinetic scaling: towards the prediction of human oral pharmacokinetics

PURPOSE

To evaluate (1) allometric scaling of systemic clearance (CL) using unbound drug concentration, (2) the potential usage of brain weight (BRW) correction in allometric scaling of both CL and oral clearance (CL/F).

METHODS

Human clearance was predicted allometrically (CLu = a x W(biv)) using unbound plasma concentration for eight Parke-Davis compounds and 29 drugs from literature sources. When the exponent b(iv) was higher than 0.85, BRW was incorporated into the allometric relationship (CLu*BRW = a x W(biv)). This approach was also applied to the prediction of CLu/F for 10 Parke-Davis compounds. Human oral t1/2, Cmax, AUC, and bioavailability were estimated based on allometrically predicted pharmacokinetic (PK) parameters.

RESULTS

Human CL and CL/F were more accurately estimated using unbound drug concentration and the prediction was further improved when BRW was incorporated into the allometric relationship. For Parke-Davis compounds, the predicted human CL and CL/F were within 50-200% and 50-220% of the actual values, respectively. The estimated human oral t1/2, Cmax, and AUC were within 82-220%, 56-240%, and 73-190% of the actual values for all 7 compounds, suggesting that human oral PK parameters of those drugs could be reasonably predicted from animal data.

CONCLUSIONS

Results from the retrospective analysis indicate that allometric scaling of free concentration could be applied to orally administered drugs to gain knowledge of drug disposition in man, and to help decision-making at early stages of drug development.

Combining in vitro and in vivo pharmacokinetic data for prediction of hepatic drug clearance in humans by artificial neural networks and multivariate statistical techniques

Several statistical regression models and artificial neural networks were used to predict the hepatic drug clearance in humans from in vitro (hepatocyte) and in vivo pharmacokinetic data and to identify the most predictive models for this purpose. Cross-validation was performed to assess prediction accuracy. It turned out that human hepatocyte data was the best predictor, followed by rat hepatocyte data. Dog hepatocyte data and dog and rat in vivo data appear to be uncorrelated with human in vivo clearance and did not significantly contribute to the prediction models. Considering the present evaluation, the most cost-effective and most accurate approach to achieve satisfactory predictions in human is a combination of in vitro clearances on human and rat hepatocytes. Such information is of considerable value to speed up drug discovery. This study also showed some of the limitations of the approach related to the size of the database used in the present evaluation.

Allometric issues in drug development

The concept of correlating pharmacokinetic parameters with body weight from different animal species has become a useful tool in drug development. The allometric approach is based on the power function, where the body weight of the species is plotted against the pharmacokinetic parameter(s) of interest. Clearance, volume of distribution, and elimination half-life are the three most frequently extrapolated pharmacokinetic parameters. Over the years, many approaches have been suggested to improve the prediction of these pharmacokinetic parameters in humans from animal data. A literature review indicates that there are different degrees of success with different methods for different drugs. Overall, though interspecies scaling requires refinement and better understanding, the approach has lot of potential during the drug development process.

Interspecies pharmacokinetic comparisons and allometric scaling of napsagatran, a low molecular weight thrombin inhibitor

The objective of this work was to assess the pharmacokinetics of napsagatran, a low molecular weight thrombin inhibitor, after intravenous administration in a variety of laboratory animals, and prospectively to help design the first pharmacokinetic studies in man. Napsagatran is actively excreted into the bile and urine of various species and pronounced species-differences in its pharmacokinetics are observed. It is, therefore, an interesting compound to use in tests of the limitations of presently available inter-species scaling methods. The present data suggest that allometric exponent values which are consistent with the values expected for physiological processes and small organic molecules are not necessarily associated with successful predictions in man when active transport processes are involved in the disposition of the compounds. For example, compared with the values observed in man, the clearance (CL), non-renal clearance (CL(nr)) and the volume of distribution at steady state (Vd(ss)) were over-predicted by 3-, 7- and 2-fold, respectively, by use of allometry. Of the species tested, the cynomolgus monkey seemed to be the most useful for predicting kinetics in man when the approach based on concentration-time transformations was used. Thus, for half-life (t(1/2)), CL and Vd(ss), the observed mean values of 1.7 h, 459 mL min(-1) and 24 L kg(-1) in man were very close to the values predicted from the cynomolgus monkey (1.7 h, 652 mL min(-1) and 22 L kg(-1), respectively). The results show that there are large inter-species differences for kidney and liver excretion of napsagatran. This is probably because of the involvement of active transport processes, which compromised the kinetic extrapolation from animal to man, although a more thorough investigation of the transporters involved in the disposition of napsagatran is necessary to enable better understanding of the species differences observed.

Correlation of plasma clearance of 54 extensively metabolized drugs between humans and rats: mean allometric coefficient of 0.66

PURPOSE

To evaluate the distribution of allometric exponents for relationship of total plasma clearance of 54 extensively metabolized drugs, with wide-ranging linear clearance values, between humans and rats, to provide a rationale for the observed data, and to discuss potential significance of the findings.

METHODS

Human and rat plasma clearance values of 54 drugs with markedly different physicochemical properties were obtained from the literature. Standard allometric analysis was performed for each drug using both rat and human data. Unbound vs. total plasma clearances were obtained for 15 out of 54 drugs and their correlations between humans and rats were compared.

RESULTS

The mean+/-SD of the allometric exponent for the 54 drugs studied is 0.660+/-0.190. The median clearance ratio based on unit body weight is 7.41 and the median exponent is 0.645. Excluding two outliers the correlation coefficient of plasma clearance between humans and rats was 0.745 (p < 0.0001). For the 15 drugs, use of unbound plasma clearance approach seems to significantly improve the correlation coefficient compared to total plasma clearance (0.940 vs. 0.841).

CONCLUSIONS

The present study indicates that on average, humans and rats may eliminate extensively metabolized drugs at a rate similar to that expected from the allometric or body surface area relationship of basal metabolic rate between the two species. A simple statistical distribution hypothesis is used to rationalize the species difference in plasma drug clearance. Rat may serve as an useful animal model to predict (unbound) plasma clearance of drugs in humans.

Interspecies scaling: predicting volumes, mean residence time and elimination half-life. Some suggestions

Extrapolation of animal data to assess pharmacokinetic parameters in man is an important tool in drug development. Clearance, volume of distribution and elimination half-life are the three most frequently extrapolated pharmacokinetic parameters. Extensive work has been done to improve the predictive performance of allometric scaling for clearance. In general there is good correlation between body weight and volume, hence volume in man can be predicted with reasonable accuracy from animal data. Besides the volume of distribution in the central compartment (Vc), two other volume terms, the volume of distribution by area (Vbeta) and the volume of distribution at steady state (VdSS), are also extrapolated from animals to man. This report compares the predictive performance of allometric scaling for Vc, Vbeta and VdSS in man from animal data. The relationship between elimination half-life (t(1/2)) and body weight across species results in poor correlation, most probably because of the hybrid nature of this parameter. To predict half-life in man from animal data, an indirect method (CL=VK, where CL=clearance, V is volume and K is elimination rate constant) has been proposed. This report proposes another indirect method which uses the mean residence time (MRT). After establishing that MRT can be predicted across species, it was used to predict half-life using the equation MRT=1.44 x t(1/2). The results of the study indicate that Vc is predicted more accurately than Vbeta and VdSS in man. It should be emphasized that for first-time dosing in man, Vc is a more important pharmacokinetic parameter than Vbeta or VdSS. Furthermore, MRT can be predicted reasonably well for man and can be used for prediction of half-life.