Interspecies pharmacokinetic scaling of metazosin, a novel alpha-adrenergic antagonist

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.

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.

A Novel Strategy for Physiologically Based Predictions of Human Pharmacokinetics

BACKGROUND

The major aim of this study was to develop a strategy for predicting human pharmacokinetics using physiologically based pharmacokinetic (PBPK) modelling. This was compared with allometry (of plasma concentration-time profiles using the Dedrick approach), in order to determine the best approaches and strategies for the prediction of human pharmacokinetics.

METHODS

PBPK and Dedrick predictions were made for 19 F. Hoffmann-La Roche compounds. A strategy for the prediction of human pharmacokinetics using PBPK modelling was proposed in this study. Predicted values (pharmacokinetic parameters, plasma concentrations) were compared with observed values obtained after intravenous and oral administration in order to assess the accuracy of the prediction methods.

RESULTS

By following the proposed strategy for PBPK, a prediction would have been made prospectively for approximately 70% of the compounds. The prediction accuracy for these compounds in terms of the percentage of compounds with an average-fold error of <2-fold was 83%, 50%, 75%, 67%, 92% and 100% for apparent oral clearance (CL/F), apparent volume of distribution during terminal phase after oral administration (V(z)/F), terminal elimination half-life (t(1/2)), peak plasma concentration (C(max)), area under the plasma concentration-time curve (AUC) and time to reach C(max) (t(max)), respectively. For the other 30% compounds, unacceptable prediction accuracy was obtained in animals; therefore, a prospective prediction of human pharmacokinetics would not have been made using PBPK. For these compounds, prediction accuracy was also poor using the Dedrick approach. In the majority of cases, PBPK gave more accurate predictions of pharmacokinetic parameters and plasma concentration-time profiles than the Dedrick approach.

CONCLUSIONS

Based on the dataset evaluated in this study, PBPK gave reasonable predictions of human pharmacokinetics using preclinical data and is the recommended approach in the majority of cases. In addition, PBPK modelling is a useful tool to gain insights into the properties of a compound. Thus, PBPK can guide experimental efforts to obtain the relevant information necessary to understand the compound's properties before entry into human, ultimately resulting in a higher level of prediction accuracy.

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.

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.

Species scaling of propafenone disposition and concentration--time relationships among eight mammalian species

Usually, smaller mammals have higher clearances per unit body mass than do larger mammalian species. When clearance and other pharmacokinetic parameters are correlated with internal physiological processes, species tend to dispose of drugs at a similar pace. The first application of this concept is pharmacokinetic time, expressed with different units: Kallynochron, Apolysichron, Dienetichron, and Syndesichron. The present work describes pharmacokinetic time in these units from data obtained with propafenone in eight animal species: mouse, rat, rabbit, dog, sheep, human, cow, and horse. Additionally, volume of distribution (Vdss = 6.5 B0.94) and clearance (CL = 0.17 B0.86) were correlated to body weight (B). Different units of pharmacokinetic time were evaluated with an Akaike Information Criterion test, and the Syndesichron was the unit that provided the best superimposition for the concentration-time plot for all animal species. It can be inferred that all mammalian species eliminated half of the dose from their bodies in 4759 Syndesichrons.