Scaling of antipyrine intrinsic clearance of unbound drug in 15 mammalian species

Light, Water, and Melatonin: The Synergistic Regulation of Phase Separation in Dementia

The swift rise in acceptance of molecular principles defining phase separation by a broad array of scientific disciplines is shadowed by increasing discoveries linking phase separation to pathological aggregations associated with numerous neurodegenerative disorders, including Alzheimer’s disease, that contribute to dementia. Phase separation is powered by multivalent macromolecular interactions. Importantly, the release of water molecules from protein hydration shells into bulk creates entropic gains that promote phase separation and the subsequent generation of insoluble cytotoxic aggregates that drive healthy brain cells into diseased states. Higher viscosity in interfacial waters and limited hydration in interiors of biomolecular condensates facilitate phase separation. Light, water, and melatonin constitute an ancient synergy that ensures adequate protein hydration to prevent aberrant phase separation. The 670 nm visible red wavelength found in sunlight and employed in photobiomodulation reduces interfacial and mitochondrial matrix viscosity to enhance ATP production via increasing ATP synthase motor efficiency. Melatonin is a potent antioxidant that lowers viscosity to increase ATP by scavenging excess reactive oxygen species and free radicals. Reduced viscosity by light and melatonin elevates the availability of free water molecules that allow melatonin to adopt favorable conformations that enhance intrinsic features, including binding interactions with adenosine that reinforces the adenosine moiety effect of ATP responsible for preventing water removal that causes hydrophobic collapse and aggregation in phase separation. Precise recalibration of interspecies melatonin dosages that account for differences in metabolic rates and bioavailability will ensure the efficacious reinstatement of the once-powerful ancient synergy between light, water, and melatonin in a modern world.

Meta-Assessment of Metformin Absorption and Disposition Pharmacokinetics in Nine Species

The objective of this study was to systematically assess literature datasets and quantitatively analyze metformin PK in plasma and some tissues of nine species. The pharmacokinetic (PK) parameters and profiles of metformin in nine species were collected from the literature. Based on a simple allometric scaling, the systemic clearances (CL) of metformin in these species highly correlate with body weight (BW) (R2 = 0.85) and are comparable to renal plasma flow in most species except for rabbit and cat. Reported volumes of distribution (VSS) varied appreciably (0.32 to 10.1 L/kg) among species. Using the physiological and anatomical variables for each species, a minimal physiologically based pharmacokinetic (mPBPK) model consisting of blood and two tissue compartments (Tissues 1 and 2) was used for modeling metformin PK in the nine species. Permeability-limited distribution (low fd1 and fd2) and a single tissue-to-plasma partition coefficient (Kp) value for Tissues 1 and 2 were applied in the joint mPBPK fitting. Nonlinear regression analysis for common tissue distribution parameters along with species-specific CL values reasonably captured the plasma PK profiles of metformin across most species, except for rat and horse with later time deviations. In separate fittings of the mPBPK model to each species, Tissue 2 was considered as slowly-equilibrating compartment consisting of muscle and skin based on in silico calculations of the mean transit times through tissues. The well-fitted mPBPK model parameters for absorption and disposition PK of metformin for each species were compared with in vitro/in vivo results found in the literature with regard to the physiological details and physicochemical properties of metformin. Bioavailability and absorption rates decreased with the increased BW among the species. Tissues such as muscle dominate metformin distribution with low permeability and partitioning while actual tissue concentrations found in rats and mice show likely transporter-mediated uptake in liver, kidney, and gastrointestinal tissues. Metformin has diverse pharmacologic actions, and this assessment revealed allometric relationships in its absorption and renal clearance but considerable variability in actual and modeled tissue distribution probably caused by transporter differences.

Allometric scaling of therapeutic monoclonal antibodies in preclinical and clinical settings

Constant technological advancement enabled the production of therapeutic monoclonal antibodies (mAbs) and will continue to contribute to their rapid expansion. Compared to small-molecule drugs, mAbs have favorable characteristics, but also more complex pharmacokinetics (PK), e.g., target-mediated nonlinear elimination and recycling by neonatal Fc-receptor. This review briefly discusses mAb biology, similarities and differences in PK processes across species and within human, and provides a detailed overview of allometric scaling approaches for translating mAb PK from preclinical species to human and extrapolating from adults to children. The approaches described here will remain vital in mAb drug development, although more data are needed, for example, from very young patients and mAbs with nonlinear PK, to allow for more confident conclusions and contribute to further growth of this field. Improving mAb PK predictions will facilitate better planning of (pediatric) clinical studies and enable progression toward the ultimate goal of expediting drug development.

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.

Misconceptions and issues regarding allometric scaling during the drug development process

INTRODUCTION

Allometry is the study of size and its consequences. The simple hypothesis of allometric scaling is that all physiological parameters are proportional to body size or body mass. This review examines the development of theory-based allometry or fixed exponents (0.75 and 1.0 for basal metabolic rate and volume, respectively) and the evidence for or against the theory. The main focus of this report is to show the readers that there is enough evidence from experimental data that negate the concept of theory-based allometry in biology, physiology, and pharmacokinetics. Areas covered: In this review, the history of the development of theoretical allometry and the strong evidence against theory-based allometry demonstrated by experimental data is provided. During drug development, allometry is applied to both inter-species (from animals to humans) and intra-species (adults to children) scaling. These two forms of allometric scaling in the context of theory-based allometry are discussed and provide insight on scientific progress that refute theory-based allometry. Expert opinion: Theory-based allometry is a mere theory and experimental data and real-life observations strongly negate the existence of such a theory. Pharmacostatistical and physiological models based on theory-based allometry can be misleading and incorrect because the theory-based allometric exponent 0.75 is not universal. The exponents of allometry are data dependent and are not fixed in the universe.

Across-Species Scaling of Monoclonal Antibody Pharmacokinetics Using a Minimal PBPK Model

PURPOSE

To examine the across-species scalability of monoclonal antibody (mAb) pharmacokinetics (PK) and assess similarities in tissue distribution across species using a recently developed minimal PBPK (mPBPK) model.

METHODS

Twelve sets of antibody PK data from various species were obtained from the literature, which were jointly and individually analyzed. In joint analysis, vascular reflection coefficients for tissues with either tight (σ 1 ) or leaky endothelium (σ 2 ) were assumed consistent across species with systemic clearance allometrically scaled (CL = a∙BW (b) ). Four parameters (σ 1 , σ 2 , a, and b) were estimated in the joint analysis. In addition, the PK from each species was individually analyzed to assess species similarities in tissue distribution.

RESULTS

Twelve mAb PK profiles were well-captured by the mPBPK model in the joint analysis. The estimated σ 1 ranged 0.690 to 0.999 with an average of 0.908; and σ 2 ranged 0.258 to 0.841 with an average of 0.579. Clearance was reasonably scaled and b ranged 0.695 to 1.27 averaging 0.91. Predictions of plasma concentrations for erlizumab and canakinumab in humans using parameters obtained from fitting animal data were consistent with actual measurements.

CONCLUSIONS

Therapeutic mAbs given IV usually exhibit biexponential kinetics with their distribution properties best captured using physiological concepts. The mPBPK modeling approach may facilitate efforts in translating antibody distribution and overall PK across species.

Contrasting toxicokinetic evaluations and interspecies pharmacokinetic scaling approaches for small molecules and biologics: applicability to biosimilar development

1. A 2-fold threshold typically used for prediction accuracy of interspecies scaling of clearance (CL) may be too liberal when using pharmacokinetic similarity in animals to advance biosimilar candidate selection for clinical testing. The purpose of this review is to identify interspecies scaling methods for use in de-risking biosimilar development prior to clinical testing. 2. Scaling approaches for predicting macromolecule CL were identified through literature review. Reports that evaluated predicted and observed human CLs for ≥5 individual compounds were considered. Absolute average fold-error (AAFE) was calculated for each method along with the proportion of compounds with individual fold-error values within a tighter threshold of 0.7-1.3. 3. Traditional simple allometry with a minimum of three species and the rule of exponents performed inconsistently with some groups of compounds resulting in a greater than 2-fold error (i.e. AAFE > 2). For monoclonal antibodies (mAbs), simplified allometric approaches employing a single species (monkey) with a fixed exponent of 0.85 consistently resulted in lower AAFEs and a higher proportion of compounds within the tighter range of 0.7-1.3. 4. For macromolecules, and particularly mAbs, employing single-species monkey "simplified" allometric approaches with a fixed exponent of 0.85 may be more appropriate than traditional allometric approaches.

Applications of human pharmacokinetic prediction in first-in-human dose estimation

Quantitative estimations of first-in-human (FIH) doses are critical for phase I clinical trials in drug development. Human pharmacokinetic (PK) prediction methods have been developed to project the human clearance (CL) and bioavailability with reasonable accuracy, which facilitates estimation of a safe yet efficacious FIH dose. However, the FIH dose estimation is still very challenging and complex. The aim of this article is to review the common approaches for FIH dose estimation with an emphasis on PK-guided estimation. We discuss 5 methods for FIH dose estimation, 17 approaches for the prediction of human CL, 6 methods for the prediction of bioavailability, and 3 tools for the prediction of PK profiles. This review may serve as a practical protocol for PK- or pharmacokinetic/pharmacodynamic-guided estimation of the FIH dose.

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 pharmacokinetics—evaluation of methods for prediction of hepatic metabolic clearance

Methods for prediction of hepatic clearance (CLH) in man have been evaluated. A physiologically-based in-vitro to in-vivo (PB-IVIV) method with human unbound fraction in blood (fu,bl) and hepatocyte intrinsic clearance (CLint)-data has a good rationale and appears to give the best predictions (maximum ∼2-fold errors; < 25% errors for half of CL-predictions; appropriate ranking). Inclusion of an empirical scaling factor is, however, needed, and reasons include the use of cryopreserved hepatocytes with low activity, and inappropriate CLint- and fu,bl-estimation methods. Thus, an improvement of this methodology is possible and required. Neglect of fu,bl or incorporation of incubation binding does not seem appropriate. When microsome CLint-data are used with this approach, the CLH is underpredicted by 5- to 9-fold on average, and a 106-fold underprediction (attrition potential) has been observed. The poor performance could probably be related to permeation, binding and low metabolic activity. Inclusion of scaling factors and neglect of fu,bl for basic and neutral compounds improve microsome predictions. The performance is, however, still not satisfactory. Allometry incorrectly assumes that the determinants for CLH relate to body weight and overpredicts human liver blood flow rate. Consequently, allometric methods have poor predictability. Simple allometry has an average overprediction potential, > 2-fold errors for ∼1/3 of predictions, and 140-fold underprediction to 5800-fold overprediction (potential safety risk) range. In-silico methodologies are available, but these need further development. Acceptable prediction errors for compounds with low and high CLH should be ∼50 and ∼10%, respectively. In conclusion, it is recommended that PB-IVIV with human hepatocyte CLint and fu,bl is applied and improved, limits for acceptable errors are decreased, and that animal CLH-studies and allometry are avoided.

Pharmacokinetic allometric scaling of antibodies: application to the first-in-human dose estimation

The objectives of this study are: (i) to evaluate the predictive performance of interspecies scaling for antibodies to predict clearance, volume of distribution at steady state, and half-life in humans from animal data and (ii) to estimate first-in-human dose based on the predicted human clearance. Four 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, (3) the product of clearance and brain weight versus body weight, and (4) the application of a fixed exponent of 0.75. Based on the predicted human clearance, six methods were used to estimate the first-in-human dose. The predicted pharmacokinetic parameters and the estimated first-in-human dose of antibodies were compared with the observed human values. The results of the study indicated that the clearance of antibodies can be predicted with reasonable accuracy in humans and a good estimate of first human dose can be obtained from the predicted human clearance.

Interspecies allometric scaling

Lack of approved pharmaceutical agents and very limited pharmacokinetic data in the scientific literature for exotic, wildlife, and zoo species are a major issue for veterinarians treating these species. There are fewer than 15 compounds approved in the United States for zoo and wildlife species compared to nearly 300 drugs licensed for cattle. Zoo veterinarians are therefore required to extrapolate the use of approved agents (veterinary or human) to nonapproved species, often with little or no scientific basis to support drug or dose schedule selection. In general, species differences in drug absorption, metabolism, distribution, and excretion have been well documented for domestic species. However, there has been limited research to provide similar data for nondomestic species. Consequently, with the possible exception of pet bird species, there is little published information on the pharmacokinetic parameters of drugs in nondomestic species. Additionally, because of the commercial value of many zoo species, the traditional method of "trial and error" for drug and dose selection and related compliance issues is often inappropriate. There is an understandable concern, whereby the zoo veterinarian does not wish to be the first to administer an agent or formulation in an untested species. "One medicine" is a central concept in treating zoo species, in that vertebrate species are generally more similar than dissimilar. However, drug absorption can vary within as well as between species. Considering the anatomical differences between true monogastrics (canine and feline species), hind-gut fermentors (rodents, rabbits, horses, and elephants), fore-gut fermentors (Colobus monkeys and kangaroos), and ruminants (cattle, goats, sheep, and antelope), the potential for differences in pharmacokinetic profiles are marked. Moreover, there are potential differences between organisms in a single class. An example is the ability of several snake species to up- and down-regulate their digestive systems. This renders the time course of oral drug absorption dependent on both body temperature and time after feeding. Plasma protein binding may vary considerably between species and may also be temperature dependent. This is very significant when treating poikilothermic (reptiles, amphibians, and fish) species and when conducting pharmacokinetic studies with highly protein-bound drugs. The large body sizes of some zoo species create additional considerations for treatment with drugs and can place significant limitations on delivery of an effective drug dose.

Interspecies scaling of therapeutic monoclonal antibodies: initial look

The authors evaluated interspecies scaling for the prediction of human clearance of 18 therapeutic monoclonal antibodies (mAbs). Human and monkey/chimpanzee data of 14 mAbs were classified based on the targeted antigens (soluble or membrane bound). Simple allometry and/or a time-invariant method (elementary Dedrick plot) were performed. Results indicate that human clearance might be accurately predicted from monkey data for mAbs targeting soluble receptors or membrane-bound receptors with limited tissue distribution using simplified allometry. The optimal exponents were estimated to be 0.85 or 0.90. If nonlinearity is anticipated at the human efficacious dose, pharmacokinetic parameters obtained at high doses in animals might not be sufficient for full pharmacokinetic characterization and prediction. Using prespecified criteria, including predicted human clearance (< or = or > 10 mL/d/kg), simplified allometric scaling might be helpful in predicting the effect of receptor-mediated clearance for mAbs targeting membrane-bound antigens. Furthermore, simplified allometry and an elementary Dedrick plot provide similar results in predicted clearance. Given the significant advantages offered by simplified allometry, it should be used when data are available from only 1 species. When reasonable data from > or =3 species are available, traditional allometry should be explored. Overall, clearance prediction is useful for human dose prediction in drug discovery and development.

Predicting oral clearance in humans: how close can we get with allometry?

BACKGROUND

Oral clearance (CL/F) is an important pharmacokinetic parameter and plays an important role in the selection of a safe and tolerable dose for first-in-human studies. Throughout the pharmaceutical industry, many drugs are administered via the oral route; however, there are only a handful of published scaling studies for the prediction of oral pharmacokinetic parameters.

METHODS

We evaluated the predictive performances of four different allometric approaches -- simple allometry (SA), the rule of exponents, the unbound CL/F approach, and the unbound fraction corrected intercept method (FCIM) -- for the prediction of human CL/F and the oral area under the plasma concentration-time curve (AUC). Twenty-four compounds developed at Johnson and Johnson Pharmaceutical Research and Development, covering a wide range of physicochemical and pharmacokinetic properties, were selected. The CL/F was predicted using these approaches, and the oral AUC was then estimated using the predicted CL/F.

RESULTS

The results of this study indicated that the most successful predictions of CL/F and the oral AUC were obtained using the unbound CL/F approach in combination with the maximum lifespan potential or the brain weight as correction factors based on the rule of exponents. We also observed that the unbound CL/F approach gave better predictions when the exponent of SA was between 0.5 and 1.2. However, the FCIM seemed to be the method of choice when the exponent of SA was <0.50 or >1.2.

CONCLUSIONS

Overall, we were able to predict CL/F and the oral AUC within 2-fold of the observed value for 79% and 83% of the compounds, respectively, by selecting the allometric approaches based on the exponents of SA.

Interspecies allometric scaling. Part I: prediction of clearance in large animals

Interspecies scaling is a useful tool for the prediction of pharmacokinetic parameters from animals to humans, and it is often used for estimating a first-time in human dose. The knowledge of pharmacokinetics in veterinary species is important for dosage selection, particularly in the treatment of large zoo animal species, such as elephants, giant cats and camels, for which pharmacokinetic data are scant. Therefore, the accuracy in clearance predictions in large animal species, with and without the use of correction factors (rule of exponents), and the impact of species selection in the prediction of clearance in large animal species was examined. Based upon this analysis, it was determined that there is a much larger risk of inaccuracies in the clearance estimates in large animal species when compared with that observed for humans. Unlike in humans, for large animal species, correction factors could not be applied because there was no trend between the exponents of simple allometry and the appropriate correction factor for improving our predictions. Nevertheless, we did see an indication that the exponents of simple allometry may alert us as to when the predicted clearance in the large animal may be underestimated or overpredicted. For example, if a large animal is included in the scaling, the predicted clearance in a large animal should be considered overestimated if the exponent of simple allometry is >1.3. Despite the potential for extrapolation error, the reality is that allometric scaling is needed across many veterinary practice situations, and therefore will be used. For this reason, it is important to consider mechanisms for reducing the risk of extrapolation errors that can seriously affect target animal safety, therapeutic response, or the accuracy of withdrawal time predictions.

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.

Prediction of human drug clearance from animal data: Application of the rule of exponents and ‘fu corrected intercept method’ (FCIM)

The objective of this study is to evaluate the predictive performance of the rule of exponents (ROE) and 'fu Corrected Intercept Method' (FCIM) for the human drug clearance. Different classes of drugs such as extensively metabolized, renally excreted, renally secreted, and biliary excreted drugs were used in this analysis. The results of the study indicated that both these methods under given conditions are extremely useful for the prediction of human drug clearance. There are certain situations under which one of these methods is more suited than the other method. Overall, it appears that a rational use of FCIM and the ROE can help a great deal in obtaining a better estimate of the human drug clearance for a wide variety of drugs. The advantages and disadvantages of these two methods are also discussed.

A novel model for prediction of human drug clearance by allometric scaling

Sixty-one sets of clearance (CL) values in animal species were allometrically scaled for predicting human clearance. Unbound fractions (f(u)) of drug in plasma in rats and humans were obtained from the literature. A model was developed to predict human CL: CL=33.35 ml/min x (a/Rf(u))(0.770), where Rf(u) is the f(u) ratio between rats and humans and a is the coefficient obtained from allometric scaling. The new model was compared with simple allometric scaling and the "rule of exponents" (ROE). Results indicated that the new model provided better predictability for human values of CL than did ROE. It is especially significant that for the first time the proposed model improves the prediction of CL for drugs illustrating 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.

A mathematical description of the functionality of correction factors used in allometry for predicting human drug clearance

The functionality of the correction factors, maximum life-span potential (MLP), and brain weight (BrW) used in allometry is mathematically described. Correction by MLP or BrW is equivalent to a multiplication of some constants by the predicted values in humans from simple allometry, but they have no relationship to measured pharmacokinetic parameters in the animal species. The values of these constants (F(MLP) or F(BrW)) were calculated for some commonly used combinations of animal species. For all combinations of animal species, the value of F(BrW) is always greater than that of F(MLP) with a fold-increase of about 1.3 to 1.9. Different combinations of species give different values of F(BrW) and F(MLP). In addition, the role of correction factors (MLP and BrW) or the "rule of exponents" (ROE) was evaluated. An intrinsic defect in using correction factors or ROE was revealed; different study designs will produce significantly different prediction results. However, ROE may still serve as a useful practical approach in predicting human CL since it was derived from real observations and has been applied to many examples.

Prediction of human pharmacokinetics from animal data and molecular structural parameters using multivariate regression analysis: oral clearance

The aim of the study reported here was to develop a regression equation for predicting oral clearance of various kinds of drugs in humans using experimental data from rats and dogs and molecular structural parameters. The data concerning the oral clearance of 87 drugs from rats, dogs, and humans were obtained from literature. The compounds have various structures, pharmacological activities, and pharmacokinetic characteristics. In addition, the molecular weight, calculated partition coefficient (c log P), and the number of hydrogen bond acceptors were used as possible descriptors related to oral clearance in human. Multivariate regression analyses, multiple linear regression analysis, and the partial least squares (PLS) method were used to predict oral clearance in human, and the predictive performances of these techniques were compared by allometric approaches, which have been used in interspecies scaling. Interaction terms were also introduced into the regression analysis to evaluate the nonlinear relationship. For the data set used in this study, the PLS model with the tertiary term descriptors gave the best predictive performance, and the value of the squared cross-validated correlation coefficient (q(2)) was 0.694. This PLS model, using animal oral clearance data for only two species and easily calculated molecular structural parameters, can generally predict oral clearance in human better than the allometric approaches. In addition, the molecular structural parameters and the interaction term descriptors were useful for predicting oral clearance in human by PLS. Another advantage of this PLS model is that it can be applied to drugs with various characteristics.

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.

Pharmacokinetics and allometric scaling of levormeloxifene, a selective oestrogen receptor modulator

The pharmacokinetics of a new selective oestrogen receptor modulator levormeloxifene was investigated in mice, rats, cynomolgus monkeys and humans by compartmental pharmacokinetics. Levormeloxifene was administered as an oral solution in all studies. Allometric scaling was used to predict human pharmacokinetic parameters and the performance of the approach was evaluated. Mean values of clearance confounded by F(CL/F) were 0.073, 0.29, 3.18 and 2.4 l/h in mice, rats, monkeys and humans, respectively. Values of distribution volume at steady state confounded by F(V(ss)/F) were 0.073 and 7.5 l in mice and rats. In monkeys, values of the central volume F(V(c)/F) and volume at steady state F(V(ss)/F) were 28.9 and 57.9 l, respectively. In humans, values of V(c)/F and V(ss)/F were 106 and 587 l, respectively. Predicted CL/F and V(ss)/F showed a linear relationship when plotted vs BW on a log-log scale; for CL/F, r was 0.95-0.98 and for V(ss)/F, r was 0.99. Using allometric scaling the predicted human V(ss)/F deviated 3-fold from the experimentally determined values. Observed values of CL/F deviated 21-25 fold from the predicted, the latter depending on the scaling method. Confidence intervals for the predicted parameters showed major lack of precision for all the allometric scaling methods.

Prediction of human clearance from animal data and molecular structural parameters using multivariate regression analysis

The aim of the study reported here was to develop a method for predicting human clearance that can be applied to various kinds of drugs using clearance values for rats and dogs and some molecular structural parameters. The clearance data for rats, dogs, and humans of 68 drugs were obtained from literature. The compounds have various structures, pharmacological activities, and pharmacokinetic characteristics. In addition, molecular weight, c log P, and the number of hydrogen bond acceptors were used as possible descriptors related to the human clearance value for each drug. Three types of regression methods, multiple linear regression (MLR) analysis, partial least squares (PLS) method, and artificial neural network (ANN), were used to predict human clearance, and their predictive performances were compared with allometric approaches, which have been widely used in interspecies scaling. In MLR and PLS analyses, interaction terms were introduced to evaluate the nonlinear relationships. For the data sets used in the present study, MLR and PLS with quadratic terms gave the same equation and the best predictive performance. The value of the squared cross-validated correlation coefficient (q(2)) was 0.682. In conclusion, the MLR method using animal clearance data from only two species and using easily calculated structural parameters can generally predict human clearance better than allometric methods. This approach can be applied to drugs with various characteristics.

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.

Interspecies scaling of biliary excreted drugs

The objective of this study is to predict clearance of drugs in humans from animals which are excreted in the bile. Clearance (CL) of eight drugs known to be excreted in the bile were randomly selected from the literature. Scaling of CL was performed using at least three animal species. Using simple allometry, CL x mean life-span potential (MLP) or CL x brain weight, CLs of studied drugs were predicted in humans. The choice of one of the methods depended on the 'rule of exponents' as described by Mahmood and Balian. A 'correction factor' was calculated by adjusting bile flow rate based on the species body weight (bile flow = mL/day/kg body weight) or liver weight (bile flow = mL/day/kg liver weight). Using the 'rule of exponents' and combining it with the 'correction factor', the CLs of biliary excreted drugs were predicted in humans. Predicted CLs in humans from animals using simple allometry were several times higher for all eight drugs (% error [range] = 46-1703). Using the 'rule of exponents' and combining it with a 'correction factor' as described in this report provided a substantial improvement (% error [range] = 5-91) in the prediction of CL for biliary excreted drugs. The results of this study indicate that the CL of a biliary excreted drug may be overpredicted in humans and by applying the 'correction factor' employed here, the predictability of drug CL in humans from animal data may be significantly improved.

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.

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.

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.

Prediction of clearance, volume of distribution and half-life by allometric scaling and by use of plasma concentrations predicted from pharmacokinetic constants: a comparative study

Pharmacokinetic parameters (clearance, CL, volume of distribution in the central compartment, VdC, and elimination half-life, t1/2beta) predicted by an empirical allometric approach have been compared with parameters predicted from plasma concentrations calculated by use of the pharmacokinetic constants A, B, alpha and beta, where A and B are the intercepts on the Y axis of the plot of plasma concentration against time and alpha and beta are the rate constants, both pairs of constants being for the distribution and elimination phases, respectively. The pharmacokinetic parameters of cefpiramide, actisomide, troglitazone, procaterol, moxalactam and ciprofloxacin were scaled from animal data obtained from the literature. Three methods were used to generate plots for the prediction of clearance in man: dependence of clearance on body weight (simple allometric equation); dependence of the product of clearance and maximum life-span potential (MLP) on body weight; and dependence of the product of clearance and brain weight on body weight. Plasma concentrations of the drugs were predicted in man by use of A, B, alpha and beta obtained from animal data. The predicted plasma concentrations were then used to calculate CL, VdC and t1/2beta. The pharmacokinetic parameters predicted by use of both approaches were compared with measured values. The results indicate that simple allometry did not predict clearance satisfactorily for actisomide, troglitazone, procaterol and ciprofloxacin. Use of MLP or the product of clearance and brain weight improved the prediction of clearance for these four drugs. Except for troglitazone, VdC and t1/2beta predicted for man by use of the allometric approach were comparable with measured values for the drugs studied. CL, VdC and t1/2beta predicted by use of pharmacokinetic constants were comparable with values predicted by simple allometry. Thus, if simple allometry failed to predict clearance of a drug, so did the pharmacokinetic constant approach (except for actisomide). The results of this study indicate that caution should be employed in interpreting plasma concentrations predicted for a drug in man by use of pharmacokinetic constants obtained in animals.

Interspecies scaling of renally secreted drugs

The objective of this study is to predict pharmacokinetic parameters (clearance, volume of distribution at steady state, and elimination half-life) in humans from animal data for drugs which are renally secreted in humans. Pharmacokinetic parameters of ten drugs were scaled-up from animal data obtained from the literature. Using simple allometry (pharmacokinetic parameter of interest vs body weight), total, renal and nonrenal clearances, volume of distribution and half-life were predicted in humans. The predicted parameters were compared with the observed parameters. The results of the study indicated that it is likely that the predicted total and renal clearances from animal data will be underestimated in humans for renally secreted drugs. The prediction of renal clearance was improved by normalizing the renal clearance by a 'correction factor' for animals who exhibited renal secretion. The predicted volume and half-life were comparable with the observed values in man. Overall, the results of this study indicate that caution should be employed in interpreting the total and renal clearance of renally secreted drugs predicted by the allometric approach.

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.

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

In this study, we investigated rational and reliable methods of using animal data to predict in humans the clearance of drugs which are mainly eliminated through hepatic metabolism. For 10 extensively metabolized compounds, adjusting the in vivo clearance in the different animal species for the relative rates of metabolism in vitro dramatically improved the predictions of human clearance compared to the approach in which clearance is directly extrapolated using body weight. Using hepatocyte data to normalize the in vivo clearances led to lower median deviations between the observed and predicted clearances in man compared to the approach normalizing data with brain weight (30-40% vs 60-80%, respectively). In addition, the approach integrating in vitro data appeared to be superior with respect to the range of deviations: approximately 2-fold underestimation, in the worst case, was observed by using in vitro data, whereas normalizing data by brain weight led to up to 10-fold underestimation of clearance in man. In addition, the integration of in vitro data provides a more rational basis to predict the metabolic clearance in man and may be applicable to compounds undergoing phase I and phase II metabolism as well.

Prediction of the pharmacokinetic parameters of reduced-dolasetron in man using in vitro-in vivo and interspecies allometric scaling

1. Dolasetron (Anzemet) is a potent and selective 5-HT3 receptor antagonist which is rapidly and extensively reduced to yield its major pharmacologically active metabolite, reduced dolasetron (RD). RD is further metabolized by CYP450 enzymes as well as undergoing renal excretion. As both in vitro and in vivo data on RD were available from animals and man, two approaches to predict the human pharmacokinetic parameters of RD were assessed. 2. First, in vitro studies, using liver microsomes from animal species and man, were undertaken to measure Vmax and K(m) and to assess the intrinsic clearance (CLint). With appropriate liver weight and liver blood flow scaling factors the predicted in vivo metabolic clearance (CLm-pred) was calculated. Human CLm-pred was underestimated by a factor of 5 when it was calculated using the above scaling factors. As, in a prospective study, the observed human in vivo metabolic clearance (CLm-obs) is unknown, CLm-pred was substituted into the least-squares correlation equation obtained from a plot of CLm-pred against CLm-obs' using animal data. The estimate of human CLm-obs was improved as it was only underestimated by a factor of 1.5. 3. Second, allometric scaling of in vivo animal pharmacokinetic data, using body weight, was performed to predict pharmacokinetic parameters in man. Good predictions of human pharmacokinetic parameters of RD were obtained for plasma clearance (1.7 l/min predicted versus 1.61/min observed), half-life (6.0 h predicted versus 5.6 h observed), and volume of distribution (860.91 predicted versus 770.41 observed). 4. The integration of in vitro metabolic data from microsomes gave similar results to conventional allometric scaling, whereas the normalization of clearance by brain weight resulted in an approximately three-fold underestimation of human clearance. 5. For RD, a drug that is eliminated by both renal and metabolic clearance, retrospective conventional allometric scaling allowed accurate prediction of pharmacokinetic parameters in man, whereas in vitro-in vivo scaling resulted in an underestimation of in vivo CLm. Although these results are somewhat at variance, ideally both scaling methods should be applied to improve the prediction of human pharmacokinetic parameters.

Extrapolation from animals to man. The integration of pharmacokinetics and pharmacodynamics

This paper has focused on the difficulties of extrapolating toxicological or pharmacological data obtained from animals to those expected in man. For some drugs, under certain conditions, there may be no problem, but for many, this is clearly not the case. Differences in apparent activity are impossible to reconcile without "normalizing" the dose for differences in pharmacokinetics and metabolism. The increasing use of artificial intelligence and expert systems in drug investigations may provide a greater insight into why these differences may occur and allow prediction but, in the end, they must be tested in the experiments undertaken. The use of kinetic dynamic relationships in different species will certainly help in this regard and, wherever possible, should be included in experimental design to build up a database of experience since such information is sadly lacking. But we must interpret with caution the data produced by those that continue to extrapolate animal data to humans without some attempt to discuss in detail the validity of their assumptions.

Interspecies scaling: predicting clearance of drugs in humans. Three different approaches

1. The interspecies scaling approach to predict clearance in humans from animal data was tested for a wide variety of drugs. 2. Three different methods were utilized to generate plots to scale-up the clearance values: (i) method I, clearance versus body weight (simple allometric equation); (ii) method II, product of clearance and maximum life-span potential; (iii) method III, product of clearance and brain weight versus body weight. 3. The circumstances under which the three methods can be applied to predict clearance in humans were evaluated. 4. If the exponent lies between 0.55 to 0.7 then method I predicts clearance reasonably well. 5. If the exponent lies between 0.71 to 1.0 clearance can be predicted reasonably well by method II. 6. If the exponent is > 1.0 clearance can be predicted using method III.