Physiological pharmacokinetic model for distribution and elimination of pentazocine. II. Study in rabbits and scale-up to man

[Biopharmaceutical studies on molecular mechanisms of membrane transport]

By incorporating the transporter-mediated or receptor-mediated transport process in physiologically based pharmacokinetic models, we succeeded in the quantitative prediction of plasma and tissue concentrations of beta-lactam antibiotics, insulin, pentazocine, quinolone antibacterial agents, and inaperizone and digoxin. The author's research on transporter-mediated pharmacokinetics focuses on the molecular and functional characteristics of drug transporters such as oligopeptide transporter, monocarboxylic acid transporter, anion antiporter, organic anion transporters, organic cation/carnitine transporters (OCTNs), and the ATP-binding cassette transporters P-glycoprotein and MRP2. We have successfully demonstrated that these transporters play important roles in the influxes and/or effluxes of drugs in intestinal and renal epithelial cells, hepatocytes, and brain capillary endothelial cells that form the blood-brain barrier. In the systemic carnitine deficiency (SCD) phenotype mouse model, juvenile visceral steatosis (jvs) mouse, a mutation in the OCTN2 gene was found. Furthermore, several types of mutation in human SCD patients were found, demonstrating that OCTN2 is a physiologically important carnitine transporter. Interestingly, OCTNs transport carnitine in a sodium-dependent manner and various cationic drugs transport it in a sodium-independent manner. OCTNs are thought to be multifunctional transporters for the uptake of carnitine into tissue cells and for the elimination of intracellular organic cationic drugs.

Prediction of the volume of distribution of a drug: which tissue-plasma partition coefficients are needed?

The aim of this study was to identify the tissue-plasma partition coefficients (Kp) needed for an initial prediction of the volume of distribution at steady state (Vd(ss)) of a drug in humans. Values of Kp were collected from the literature. Only Kp values plausibly representing true steady state distribution were accepted, and data had to be available for muscle, fat, skin and at least five other organs. The apparent volume of distribution of a drug in an organ/tissue (Vapp) was calculated as Kp multiplied by the volume of the organ/tissue, and the Vd(ss) as the sum of all available Vapp values. The percentage contribution of each Vapp to the Vd(ss) was estimated. In addition, linear regressions were calculated between Kp values of all drugs in a specific organ/tissue and Kp in muscle or fat. Finally, the Vd(ss) was re-calculated using (for basic drugs) the Kp in fat to calculate Vapp in fat and lungs and the Kp in muscle for the Vapp of all other organs/tissues. The two sets of estimates of Vd(ss) were compared by linear regression. The same calculations were performed for acidic drugs, except that muscle Kp was used also forthe lungs. Distribution to fat and muscle accounted for 84% (61-91%) (median and range) of the total estimated Vd(ss) of the basic drugs (n = 17). The regressions between Kp in organs/tissues and muscle Kp were statistically significant except in the case of liver. For acidic drugs (n = 18), distribution to fat and muscle accounted for 65% (42-92%) of Vd(ss), and the regressions of Kp were significant for all organs/tissues except kidney and bone. For both types of drugs, correlations between organ/tissue Kp values and Kp in fat were generally worse. There were excellent linear correlations between Vd(ss) calculated by means of only two Kp values and the originally calculated Vd(ss) (r2> or = 0.99 for both basic and acidic drugs; slopes were notsignificantly different from unity). Thus, initial estimation of the Vd(ss) of a new drug can normally be based on only two Kp values, those of muscle and fat. The muscle Kp can be used to represent all lean tissues, including the residual "carcass", with the exception that fat Kp can be used for distribution of basic drugs to lungs.

[Studies on the mechanism of subcellular distribution of basic drugs based on their lipophilicity]

This paper described the studies on the mechanism of subcellular distribution of lipophilic weak bases. Although the tissue distribution of basic drugs appeared to decrease with time simply in parallel with their plasma concentration, their subcellular distribution in various tissues exhibited a variety of patterns. Basic drugs were distributed widely in various tissues, but were concentrated in lung granule fraction, where their accumulation was dependent on their lipophilicity and lysosomal uptake. As the plasma concentration of drugs decreased after maximum level, the contribution of lysosomes to their subcellular distribution increased. The uptake of the basic drugs into lysosomes depended both on their intralysosomal pH and on the drug lipophilicity. As the lipophilicity of the basic drugs increased, they accumulated more than the values predicted from the pH-partition theory and raised the intralysosomal pH more potently, probably owing to their binding with lysosomal membranes with or without additional intralysosomal aggregation. These phenomena should be considered as a basis of drug interaction in clinical treatments.

A priori prediction of tissue:plasma partition coefficients of drugs to facilitate the use of physiologically-based pharmacokinetic models in drug discovery

The tissue:plasma (P(t:p)) partition coefficients (PCs) are important drug-specific input parameters in physiologically based pharmacokinetic (PBPK) models used to estimate the disposition of drugs in biota. Until now the use of PBPK models in early stages of the drug discovery process was not possible, since the estimation of P(t:p) of new drug candidates by using conventional in vitro and/or in vivo methods is too time and cost intensive. The objectives of the study were (i) to develop and validate two mechanistic equations for predicting a priori the rabbit, rat and mouse P(t:p) of non-adipose and non-excretory tissues (bone, brain, heart, intestine, lung, muscle, skin, spleen) for 65 structurally unrelated drugs and (ii) to evaluate the adequacy of using P(t:p) of muscle as predictors for P(t:p) of other tissues. The first equation predicts P(t:p) at steady state, assuming a homogenous distribution and passive diffusion of drugs in tissues, from a ratio of solubility and macromolecular binding between tissues and plasma. The ratio of solubility was estimated from log vegetable oil:water PCs (K(vo:w)) of drugs and lipid and water levels in tissues and plasma, whereas the ratio of macromolecular binding for drugs was estimated from tissue interstitial fluid-to-plasma concentration ratios of albumin, globulins and lipoproteins. The second equation predicts P(t:p) of drugs residing predominantly in the interstitial space of tissues. Therefore, the fractional volume content of interstitial space in each tissue replaced drug solubilities in the first equation. Following the development of these equations, regression analyses between P(t:p) of muscle and those of the other tissues were examined. The average ratio of predicted-to-experimental P(t:p) values was 1.26 (SD = 1.40, r = 0.90, n = 269), and 85% of the 269 predicted values were within a factor of three of the corresponding literature values obtained under in vivo and in vitro conditions. For predicted and experimental P(t:p), linear relationships (r > 0.9 in most cases) were observed between muscle and other tissues, suggesting that P(t:p) of muscle is a good predictor for the P(t:p) of other tissues. The two previous equations could explain the mechanistic basis of these linear relationships. The practical aim of this study is a worthwhile goal for pharmacokinetic screening of new drug candidates.

Effects of methoxyflurane anesthesia on the pharmacokinetics of 125I-IAZA in Sprague-Dawley rats

Effects of methoxyflurane anesthesia on the pharmacokinetics of intravenous 125I-IAZA in rats are reported. No significant differences in t(1/2alpha), t(1/2beta), V(SS), and ClTB for total radioactivity (125I-IAZA and metabolites) were observed between the anesthetized (Group 1, n = 4) and nonanesthetized (Group 2, n = 3) animals. For 125I-IAZA, ClTB increased from 646 +/- 52 mL/h/kg to 2250 +/- 351 mL/h/kg and t(1/2beta) decreased from 97.7 +/- 17.5 min to 35.6 +/- 5.4 min, for Groups 1 and 2, respectively. There were no differences in V(SS) or t(1/2alpha) between the two groups. These findings support literature reports of anesthetic effects on xenobiotic pharmacokinetics, and indicate a need for caution in the evaluation of preclinical imaging studies in which animals are immobilized with anesthetics.

Relationships between the hepatic intrinsic clearance or blood cell-plasma partition coefficient in the rabbit and the lipophilicity of basic drugs

The relationships between drug lipophilicity and hepatic intrinsic clearance (CLint,h) or red blood cell-plasma partition coefficients (D) have been elucidated for ten highly lipophilic basic drugs with apparent octanol-water partition coefficients at pH 7.4 (Papp,oct) or 150 or above. The true octanol-water partition coefficients of the non-ionized drugs (Poct) were used to determine CLint,h and D for the unbound drugs (CLint,h,f and Df, respectively), and CLint,h,f and Df for the non-ionized and unbound drugs (CLint,h fu and Dfu, respectively). The total clearance values were determined at steady state by infusion studies of individual drugs in rabbits. There was better correlation between log Poct and log CLint,h,fu (r = 0.974) than between log Poct and log CLint,h,f (r = 0.864). The D values were calculated from the blood-plasma concentration ratio. There was a better correlation between log Poct and log Dfu (r = 0.944) than between log Poct and log Df (r = 0.612). The regression equations obtained were CLint,h,fu = 0.0875 x Poct1.338 and Dfu = 0.0108 x Poct0.970, respectively. These results show that the CLint,h and D of highly lipophilic basic drugs can be predicted from Poct by taking fu into consideration. By applying these parameters to a physiologically based pharmacokinetic model it might be possible to predict the pharmacokinetics of unknown basic drugs.

Prediction of changes in the clinical pharmacokinetics of basic drugs on the basis of octanol-water partition coefficients

A physiologically based pharmacokinetic model for basic drugs has been established on the basis of octanol-water partition coefficients of the non-ionized, unbound drugs (Poct). The parameters for the physiological model in man were estimated from a regression equation obtained for the relationships between the Poct and the tissue-plasma partition coefficient, the hepatic intrinsic clearance (CLint,h) and the blood-to-plasma concentration ratio in rabbits. The plasma concentrations observed after intravenous administration of ten basic drugs (3.2 mg kg-1) to rabbits agreed with the levels predicted using the physiological model (r = 0.710-0.980). In man, the predicted plasma concentrations of basic drugs were in good agreement with reported values (r = 0.729-0.973), except for diazepam and pentazocine. Variations in plasma and brain-concentration profiles of clomipramine and nitrazepam in various disease states were simulated using the model. We assumed that the changes in unbound fraction of drug in serum (fp), CLint,h and the hepatic blood flow rate were from 0.25- to 4-fold that of the control and that fat volume changed by 0.2- to 5-fold. With regard to changes in fp, we predicted that the brain-plasma concentration ratio of clomipramine was 1.5- to 25-fold that of the control 24 h after intravenous administration, although the variations in the plasma concentration-time profiles were less marked. Plasma concentrations predicted for several basic drugs were in good agreement with reported values and this physiological model could be useful for predicting drug-disposition kinetics in man.

Physiologically based pharmacokinetic study on a cyclosporin derivative, SDZ IMM 125

The immunosuppressant, SDZ IMM 125 (IMM), is a derivative of cyclosporin A (CyA). The disposition kinetics of IMM in plasma, blood cells, and various tissues of the rat was characterized by a physiologically based pharmacokinetic (PBPK) model; the model was then applied to predict the disposition kinetics in dog and human. Accumulation of IMM in blood cell is high (equilibrium blood cell/plasma ratio = 8), although the kinetics of drug transference between plasma and blood cell is moderately slow, taking approximately 10 min to reach equilibrium, implying a membrane-limited distribution into blood cells. A local PBPK model, assuming blood-flow limited distribution and tissue/blood partition coefficient (KP) data, failed to adequately describe the observed kinetics of distribution, which were slower than predicted. A membrane transport limitation is therefore needed to model dynamic tissue distribution data. Moreover, a slowly interacting intracellular pool was also necessary to adequately describe the kinetics of distribution in some organs. Three elimination pathways (metabolism, biliary secretion, and glomerular filtration) of IMM were assessed at steady state in vivo and characterized independently by the corresponding clearance terms. A whole-body PBPK model was developed according to these findings, which described closely the IMM concentration-time profiles in arterial blood as well as 14 organs/tissues of the rat after intravenous administration. The model was then scaled up to larger mammals by modifying physiological parameters, tissue distribution and elimination clearances; in vivo enzymatic activity was considered in the scale-up of metabolic clearance. The simulations agreed well with the experimental measurements in dog and human, despite the large interspecies difference in the metabolic clearance, which does not follow the usual allometric relationship. In addition, the nonlinear increase in maximum blood concentration and AUC with increasing dose, observed in healthy volunteers after intravenous administration, was accommodated quantitatively by incorporating the known saturation of specific binding of IMM to blood cells. Overall, the PBPK model provides a promising tool to quantitatively link preclinical and clinical data.

Physiologic pharmacokinetic modeling

Although physiologic modeling has not gained the widespread acceptance that was originally projected, it may serve as the basis for future PK/PD modeling approaches. In addition, with more effort applied to developing in vitro and animal-to-human predictions, physiologic modeling may assume a higher position in the pharmacokinetic modeling hierarchy.

Man versus beast: pharmacokinetic scaling in mammals

Land mammals range in size from the 3-g shrew to the 3000-kg elephant. Despite this 10(6) range in weight, most land mammals have similar anatomy, physiology, biochemistry, and cellular structure. This similarity has allowed interspecies scaling of physiologic properties such as heart rate, blood flow, blood volume, organ size, and longevity. The equation that is the basis for scaling physiologic properties among mammals is the power equation Y = aWb, where Y is the physiologic variable of interest, W is body weight, and log a is the y-intercept and b is the slope obtained from the plot of log Y versus log W. Animals commonly used in preclinical drug studies (i.e., mice, rats, rabbits, monkeys, and dogs) do not eliminate drugs at the same rate that humans eliminate drugs; small mammals usually eliminate drugs faster than large mammals. Since drug elimination is intimately associated with physiologic properties that are well described among species, it seems reasonable to surmise that drug elimination can be scaled among mammals. Analysis of drug pharmacokinetics in numerous species demonstrates that drug elimination among species is predictable and, in general, obeys the power equation Y = aWb. Early papers on interspecies pharmacokinetic scaling normalized the x- and y-axes to illustrate the superimpossibility of pharmacokinetic curves from different species. More recently, the x- and y-axes have been left in the common units of concentration and time, and individual pharmacokinetic variables have been adjusted to predict pharmacokinetic profiles in an untested species, usually humans.