Interspecies scaling of tebufelone pharmacokinetic data and application to preclinical toxicology

Interspecies scaling and prediction of human clearance: comparison of small- and macro-molecule drugs

Human clearance prediction for small- and macro-molecule drugs was evaluated and compared using various scaling methods and statistical analysis. Human clearance is generally well predicted using single or multiple species simple allometry for macro- and small-molecule drugs excreted renally. The prediction error is higher for hepatically eliminated small-molecules using single or multiple species simple allometry scaling, and it appears that the prediction error is mainly associated with drugs with low hepatic extraction ratio (Eh). The error in human clearance prediction for hepatically eliminated small-molecules was reduced using scaling methods with a correction of maximum life span (MLP) or brain weight (BRW). Human clearance of both small- and macro-molecule drugs is well predicted using the monkey liver blood flow method. Predictions using liver blood flow from other species did not work as well, especially for the small-molecule drugs.

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.

Mechanism-based concepts of size and maturity in pharmacokinetics

Growth and development can be investigated using readily observable demographic factors such as weight and age. Size is the primary covariate and can be referenced to a 70-kg person with allometry using a coefficient of 0.75 for clearance and 1 for volume. The use of these coefficients is supported by fractal geometric concepts and observations from diverse areas in biology. Fat free mass (FFM) might be expected to do better than total body weight when there are wide variations in fat affecting body composition. Clearance pathways develop in the fetus before birth. The use of postnatal age as a descriptor of maturation is unsatisfactory because birth may occur prematurely; therefore postmenstrual age is a superior predictor of elimination function. A sigmoid E(max) model (Hill equation) describes gradual maturation of clearance in early life leading to a mature adult clearance achieved at a later age.

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.

Allometric principles for interspecies extrapolation in toxicological risk assessment--empirical investigations

Four types of data (toxicokinetic data of pharmaceuticals from six species including humans, LD(50) values from eight animal species, long-term NOAEL values of pesticides from mice, rats, and dogs, and toxicity data on anti-neoplastic agents from six species including humans) were used for interspecies comparisons. Species differences with regard to kinetic parameters and toxicity were evaluated and the concordance with predictions by allometric scaling according to caloric demand (allometric exponent 0.75) or to body weight (allometric exponent 1) was checked. For LD(50) values, agreement was poor for both allometric concepts. Recently reported concordance of LD(50) species differences with body weight scaling could be traced back to biased data selection. The other three datasets are clearly in agreement with the allometric scaling according to caloric demand. Caloric demand scaling is thus proposed as a generic interspecies extrapolation method in the absence of substance-specific data. Moreover, the evaluated data make it possible to describe uncertainty associated with the process of interspecies extrapolation by allometric rules.

Prediction of volume of distribution values in humans for neutral and basic drugs using physicochemical measurements and plasma protein binding data

We present a method for the prediction of volume of distribution in humans, for neutral and basic compounds. It is based on two experimentally determined physicochemical parameters, ElogD(7.4) and f(i(7.4)), the latter being the fraction of compound ionized at pH 7.4 and on the fraction of free drug in plasma (f(u)). The fraction unbound in tissues (f(ut)), determined via a regression analysis from 64 compounds using the parameters described, is then used to predict VD(ss) via the Oie-Tozer equation. Accuracy of this method was determined using a test set of 14 compounds, and it was demonstrated that human VD(ss) values could be predicted, on average, within or very close to 2-fold of the actual value. The present method is as accurate as reported methods based on animal pharmacokinetic data, using a similar set of compounds, and ranges between 1.62 and 2.20 as mean-fold error. This method has the advantage of being amenable to automation, and therefore fast throughput, it is compound and resources sparing, and it offers a rationale for the reduction of the use of animals in pharmacokinetic studies. A discussion of the potential errors that may be encountered, including errors in the determination of f(u), is offered, and the caveats about the use of computed vs experimentally determined logD and pK(a) values are addressed.

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.

Common errors of drug administration in infants: causes and avoidance

Drug administration errors are common in infants. Although the infant population has a high exposure to drugs, there are few data concerning pharmacokinetics or pharmacodynamics, or the influence of paediatric diseases on these processes. Children remain therapeutic orphans. Formulations are often suitable only for adults; in addition, the lack of maturation of drug elimination processes, alteration of body composition and influence of size render the calculation of drug doses complex in infants. The commonest drug administration error in infants is one of dose, and the commonest hospital site for this error is the intensive care unit. Drug errors are a consequence of system error, and preventive strategies are possible through system analysis. The goal of a zero drug error rate should be aggressively sought, with systems in place that aim to eliminate the effects of inevitable human error. This involves review of the entire system from drug manufacture to drug administration. The nuclear industry, telecommunications and air traffic control services all practise error reduction policies with zero error as a clear goal, not by finding fault in the individual, but by identifying faults in the system and building into that system mechanisms for picking up faults before they occur. Such policies could be adapted to medicine using interventions both specific (the production of formulations which are for children only and clearly labelled, regular audit by pharmacists, legible prescriptions, standardised dose tables) and general (paediatric drug trials, education programmes, nonpunitive error reporting) to reduce the number of errors made in giving medication to infants.

Probabilistic approach to the establishment of maximal content limits of impurities in drug formulations: the case of parenteral diphenylhydantoic acid

Diphenylhydantoic acid (DPHA) is a degradation product in parenteral formulations of the anticonvulsant phenytoin and the prodrug fosphenytoin. DPHA has also been reported to be a minor metabolite of phenytoin. Levels found in the urine of various species, including humans, after oral or intravenous (iv) phenytoin ranged from undetected to a few percent of administered dose. In the present analysis, the toxicologic profile of DPHA was integrated with exposure data in order to characterize its safety under recommended clinical regimens of fosphenytoin administration. In preclinical safety studies, DPHA was without effect in the Ames assay and at concentrations up to 3000 microg/plate in the presence or absence of metabolic activation, and in the in vitro micronucleus test with acute and 2-week repeated dose studies in Wistar rats at iv doses up to 15 mg/kg. In 4-week studies conducted in rats and dogs receiving fosphenytoin containing DPHA levels up to 1.1%, and in an in vitro structural chromosome aberration test with DPHA levels up to 2.0%, all findings were consistent with known effects of phenytoin (such as CNS signs and increased liver weight), and none were attributed to DPHA. Reports in the literature indicate that in murine in vivo and in vitro models, DPHA has much lower potential for reproductive toxicity than phenytoin. A no-observed-effect level (NOEL) of 15 mg/kg established from the 2-week study in rats was used with probabilistic techniques to estimate tolerable daily doses (TDDs) of DPHA. In this approach, interspecies correction was performed by allometrically scaling the NOEL based on a distributional power of body weight while intraindividual variability was accounted for by selecting the lower percentiles of the population-based distribution of TDDs. The results indicate that a DPHA content limit of 3.0% in an administered dose of fosphenytoin is unlikely to cause adverse effects in patients.

Mixed effect modeling of sumatriptan pharmacokinetics during drug development. I: Interspecies allometric scaling

Allometric scaling is an empirical examination of the relationships between the pharmacokinetic parameters and size (usually body weight), but it can also involve brain weight for metabolized drug. Through all species, the protein binding of sumatriptan is similar (14-16%), and its metabolic pathway undergoes extensive oxidative deamination involving the monoamine oxidase A isoenzyme. These similarities across species suggested the possible relevance of an allometric analysis. Toxicokinetic data were collected from rats, pregnant rabbits, and dogs in animal pharmacokinetic studies where sumatriptan was administered intravenously to the animals at doses of 5 mg/kg. 0.25 mg/kg, and 1 mg/kg, respectively. Animal data were pooled and analyzed in one step using a mixed effect modeling (population) approach. The kinetic parameters predicted in any species were close to the observed values by species: 77 L/hr vs. 80 L/hr in man for total clearance, 137 L vs. 119 L for distribution volume at steady state. The value of the mixed effect modeling approach compared to the two-step method was demonstrated especially with the possibility of including covariates to describe the status of animal (e.g., pregnancy) in the model. Knowledge of the animal kinetics, dynamics, and metabolism of a drug contributes to optimal and expeditious development. Valuable information for the design of the first-dose-in-man study may emerge from more creative data analysis based on all the information collected during the preclinical and ongoing nonclinical evaluation of a new drug.

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.

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.

Interspecies scaling: predicting pharmacokinetic parameters of antiepileptic drugs in humans from animals with special emphasis on clearance

The objective of this study was to test the interspecies-scaling approach in a series of antiepileptic drugs. Clearance, volume of distribution, and elimination half-life were scaled up from animal data obtained from literature. Four different methods were utilized to generate plots to scale up the clearance values: (i) clearance vs body weight (simple allometric equation); (ii) the product of clearance and maximum life-span potential (MLP) vs body weight (an approach recommended in literature); (iii) the two-term power equation which incorporates both body weight and brain weight suggested by Boxenbaum; and (iv) the product of clearance and brain weight vs body weight (a new approach being introduced in this study). When the predicted values for clearance were qualitatively compared with the observed values in humans, it was found that our proposed method predicted the clearance better than the other three methods. Using the simple allometric equation, the prediction of volume of distribution as a function of body weight was found to be satisfactory. The elimination half-life could not be predicted from simple allometric equations for any of the drugs studied; however, utilizing the equation CL = VK, prediction for half-life was feasible. The results of this study indicate that it is possible to predict reliably the pharmacokinetic parameters of these antiepileptic drugs in humans from animal data using an allometric approach.