![[Feedback]](/icons/banner/feedbackACT.gif){kind=icon}
![[For Subscribers]](/icons/banner/subscriberACT.gif){kind=icon}
![[Archive]](/icons/banner/archiveACT.gif){kind=icon}
![[Search]](/icons/banner/searchACT.gif){kind=icon}
![[Contents]](/icons/banner/tocACT.gif){kind=icon}
|
|
|
|
|
||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
ABSORPTION, DISTRIBUTION, METABOLISM, AND EXCRETION
Pharmacokinetics, Dynamics, and Metabolism, Pfizer Global Research and Development, Groton, Connecticut
Received October 14, 2004; accepted February 28, 2005.
 |
Abstract |
|---|
 Top Abstract Materials and MethodsResultsDiscussionReferences |
|---|
; Golden and Pollack, 2003).
The kinetics of brain penetration consists of the extent of brain equilibrium and the time to achieve brain equilibrium. The extent of brain equilibrium is often quantified by brain-plasma partition coefficient (Kp), the ratio of total brain concentration and plasma concentration at steady state. This parameter depends upon drug binding in plasma and brain tissue, the uptake and efflux transporters at BBB, metabolism in the brain, and the bulk flow of cerebrospinal fluid (Hammarlund-Udenaes et al., 1997). If active transporters, brain metabolism and the bulk flow of cerebrospinal fluid do not contribute significantly to brain drug disposition, the free drug concentration in brain is equal to the free drug concentration in plasma, and the Kp is equal to the ratio of unbound fraction in plasma and unbound fraction in brain at equilibrium. Theoretically, the ratio of unbound brain concentration and unbound plasma concentration at steady state, Kp,free, is a better parameter to quantitate the extent of brain equilibrium (Tunblad et al., 2003). This parameter is not dependent upon plasma and brain tissue binding. In drug discovery, it is important to identify CNS-targeted compounds with Kp,free of unity by screening out substrates of efflux transporters. Extensive screening efforts have been made in the drug discovery phase to identify the substrates of known efflux transporters, such as P-glycoprotein (Adachi et al., 2001; Polli et al., 2001; Chen et al., 2003b; Lin and Yamazaki, 2003).
Although the extent of brain penetration or achievement of high free brain concentration is the most critical property, the time to reach brain equilibrium is another important perspective of the kinetics of brain penetration. In CNS drug discovery, it is often desirable to identify compounds that can quickly penetrate into brain thereby the unbound drug concentration at the targeted site in brain tissue can reach plasma unbound concentration quickly after administration. The property of quick brain penetration can be gauged by the time to reach brain equilibrium. Therefore, a short time to achieve brain equilibrium is a surrogate for a rapid achievement of active brain concentration. Rapid CNS penetration becomes essential for the compounds used for many diseases such as hypnosis (Hardman et al., 2001), status epilepsy (Li et al., 2000), and stroke (Adams and Leira, 1998). Empirical approaches to identify compounds with quick brain penetration during the discovery phase include screens to identify compounds with high BBB permeability (Di et al., 2003; Liu et al., 2004). In addition to BBB permeability, it has been implied in the literature that the time of brain equilibrium also depends upon the partition coefficient (Hammarlund-Udenaes et al., 1997). No study has been conducted to evaluate systematically the factors that determine the time to reach brain equilibrium.
The present study was designed to evaluate the effects of BBB permeability, plasma protein binding, and brain tissue binding on the time to reach brain equilibrium. The application of the results from the present study on strategies to select rapid brain penetration compounds in drug discovery is also discussed.
|
Materials and Methods |
|---|
|
TopAbstractMaterials and MethodsResultsDiscussionReferences |
|---|
Animal Experiments. Male Sprague-Dawley rats (250-280 g) were obtained from Charles River Laboratories (Raleigh, NC). They were housed at controlled temperature and humidity in an alternating 12-h light/dark cycle with free access to food and water. Rats received caffeine (10 mg/kg), CP-141938 (5 mg/kg), fluoxetine (10 mg/kg), NFPS (10 mg/kg), propranolol (5 mg/kg), theobromine (10 mg/kg), or theophylline (10 mg/kg) subcutaneously. The doses were prepared in 0.9% saline and delivered in a volume of 2 ml/kg. Blood samples were collected in heparin-treated tubes at a designated time between 10 min and 24 h postdose via cardiac puncture. After centrifugation (3000 rpm, 10 min) of the blood, plasma was isolated. Brain tissue was harvested and rinsed with saline immediately after collection. The plasma and brain samples were stored at -20°C prior to analysis.
Protein Binding. The unbound fraction in plasma and brain homogenate was determined using a 96-well equilibrium dialysis method reported previously (Kalvass and Maurer, 2002). Briefly, fresh Sprague-Dawley rat plasma and brain tissue was obtained on the day of the study. Brain tissue was homogenized in 2 volumes (w/v) of 100 mM sodium phosphate buffer. Plasma, brain homogenate, and phosphate buffer (for equilibrium controls) were spiked with a compound (500 ng/ml), and 150 µl of these matrices were added to the dialysis apparatus. The receiver side contained 150 µl of phosphate buffer. The 96-well equilibrium dialysis apparatus was maintained on a shaking device in an incubator at 37°C for 5 h. Ten microliters of plasma or brain homogenate and 50 µl of buffer were taken from the apparatus and added to high-performance liquid chromatography (HPLC) vials containing 100 µl of acetonitrile. The samples were then vortexed, centrifuged, and the supernatant was stored at -20°C prior to analysis. The unbound fractions determined from diluted brain tissue homogenates were corrected to yield an estimate of unbound fraction in the intact brain tissue using a previously published method (Kalvass and Maurer, 2002).
Sample Analysis. The brain tissues were homogenized in 3 volumes (w/v) of water. Twenty microliters of plasma or brain homogenate, 20 µl of dimethyl sulfoxide, and 200 µl of acetonitrile were mixed in silanized 96-well glass tubes. For the protein binding samples, 10 µl of plasma or brain homogenate samples were mixed with 50 µl of control buffer, and 50 µl of buffer samples were mixed with 10 µl of control brain homogenate or control plasma to yield an identical matrix between buffer and nonbuffer samples. The samples were then mixed with 100 µl of acetonitrile and 50 µl of methanol water mixture (50:50, v/v) in 96-well glass tubes. After centrifugation at 3000 rpm for 5 min, the supernatant was analyzed by HPLC-tandem mass spectrometry methods.
The HPLC-tandem mass spectrometry system consisted of either a Shimadzu ternary pump (Shimadzu LC-10A; Shimadzu, Kyoto, Japan) or an Agilent quaternary pump HPLC system (Hewlett Packard, Palo Alto, CA), an autosampler, and a PE Sciex API 3000 or 4000 (PerkinElmer Sciex Instruments, Foster City, CA) mass spectrometer with a turbo ion spray interface (PerkinElmer Sciex Instruments, Thornhill, ON, Canada). A 10-µl aliquot of each sample was injected onto a HPLC column. CP-141938 was run on a Phenomenex Synergi Polar column (50 x 4.6 mm, 4 µm; Phenomenex, Torrance, CA) isocratically at 75% acetonitrile and 25% 5 mM ammonium acetate containing 0.01% formic acid and 0.1% isopropranol with a flow rate of 1 ml/min for 4 min. Propranolol, fluoxetine, and NFPS were run on a Phenomenex Primesphere C18 HC column (30 x 2.0 mm, 5 µm; Phenomenex) using a gradient pump program beginning at 5 to 10% acetonitrile and 90 to 95% aqueous 5 to 20 mM ammonium acetate containing 0.1% isopropranol with a flow rate of 0.4 ml/min. The acetonitrile increased linearly from 10 to 90% from 1.0 to 1.2 min and then maintained at 90% from 1.2 to 4.0 min. The system returned to the initial conditions in a single step and was allowed to equilibrate for 1 min. Caffeine, theobromine, and theophylline were run on a Phenomenex Luna Phenyl Hexyl column (50 x 4.6 mm, 5 µm; Phenomenex) isocratically at 20% acetonitrile and 80% 5 mM ammonium acetate containing 0.1% formic acid and 0.1% isopropranol for 5 min at a flow rate of 1 ml/min. All analytes were eluted between 1 and 4 min.
The compounds were monitored using the following mass transitions: CP-141938, 404.3
160.0 (declustering potential 51 V; collision energy 29 V); propranolol, 260.2116.3 (36 V; 27 V); fluoxetine, 310.1148.1 (26 V; 13 V); NFPS, 394.2102.2 (26 V; 21 V); caffeine, 195.2138.1 (41 V; 27 V); theobromine, 181.1138.1 (46 V; 25 V); and theophylline, 181.1123.1 (46 V; 23 V). The low limit of quantitation for the plasma samples of caffeine, CP-141938, fluoxetine, NFPS, propranolol, theobromine, and theophylline was 10, 1, 2.5, 1, 2, 50, and 50 ng/ml, respectively. The low limit of quantitation for the brain samples was 40, 4, 10, 4, 5, 200, and 200 ng/ml, respectively. The relative accuracy was between 80 and 120%. The contribution of residual blood in the brain tissue to the brain concentration was corrected by subtracting 3.7% of the plasma concentration from the corresponding brain concentration (Khor et al., 1991).
Brain PBPK Model. A hybrid brain PBPK model was constructed based upon a previously published whole-body PBPK model (Peng et al., 2001). The brain consists of two compartments, i.e., brain intravascular and extravascular compartments (Fig. 1A). This model was based upon the following assumptions: 1) only the unbound drug in vascular space is available to cross the BBB, and the unbound and bound compound equilibrates instantaneously within each compartment; 2) no transporter contributes significantly to the brain disposition, consequently, the uptake and efflux clearance is equal to PS, the product of BBB permeability-surface area product representing the distribution clearance across BBB via passive diffusion; and 3) cerebrospinal fluid does not significantly impact on the brain drug disposition (Wang et al., 1997).
|
For caffeine, CP-141938, NFPS, theobromine, and theophylline their mass balance rate equation for the central compartment consisting of rapid perfusion organs is:
 | (1) |
 | (2) |
 | (3) |
 | (4) |
Its mass balance rate equation for the peripheral compartment consisting of slow perfusion organs is:
 | (5) |
The mass balance rate equation for brain intravascular compartment is:
 | (6) |
The mass balance rate equation for brain extravascular compartment is:
 | (7) |
The Q, Vev, and Viv was assumed to be 312 ml/h/kg, 6.56 ml/kg, and 0.24 ml/kg, respectively (Peng et al., 2001). The pharmacokinetic parameters for the plasma (ka, Vp, Vsp, Clp, and Cld) were estimated by fitting eqs. 1, 2, 3, 4, 5 to the observed plasma concentrations in Fig. 2, and the pharmacokinetic parameters for the brain (PS, Kp, and fu,brain) were estimated by fitting eqs. 6 and 7 to brain concentrations using the nonlinear least-squares regression program WinNonlin (version 3.2; Pharsight Corporation, Mountain View, CA). The goodness-of-fit were assessed based on Akaike's Information Criterion (Akaike, 1976), the degree of colinearity of parameters, the degree of bias in residual error, the standard error of parameter estimates, and visual inspection of the generated curves relative to the data. A weighting scheme of 1/YPredicted was used for all fitting procedures (Liu et al., 1999).
|
|
 | (8) |
). By definition, k12 = Cld/Vp, k21 = Cld/Vsp, and k10 = Clp/Vp.
Relationship between Brain and Plasma Concentrations. To obtain an explicit expression to describe the brain-to-plasma concentration ratio (BP) time course, the brain PBPK model was simplified by removing the cerebral blood flow from the model under the assumption that BBB permeability is the rate-limiting step for brain penetration (Fig. 1B) (Hammarlund-Udenaes et al., 1997). Since brain tissue weight is less than 1% of body weight in rats (Brown et al., 1997), the amount of drug in brain tissue is much less than that in the rest of the body. Therefore, the impact of efflux of drug from brain on plasma concentration can be considered negligible. After a compound is administrated by an intravenous bolus injection, the mass balance rate equation for plasma can be described as:
 | (9) |
 | (10) |
Integration of the rate equations yield plasma and brain concentration-time equations:
 | (11) |
 | (12) |
BP can be obtained from eqs. 11 and 12:
 | (13) |
 | (14) |
). The following equation can be obtained from eq. 10:
 | (15) |
 | (16) |
|
Results |
|---|
|
TopAbstractMaterials and MethodsResultsDiscussionReferences |
|---|
). The unbound fractions in rat plasma (fu,plasma) and brain homogenate (fu,brain) measured by an equilibrium dialysis method are also presented in Table 1. The determined unbound fraction in rat plasma is consistent with the values reported in the literature (Bonati et al., 1984; Chauvelot-Moachon et al., 1988; Yasuhara and Levy, 1988; Shum and Jusko, 1989; Caccia et al., 1990). We observed an inverse relationship between permeability and the nonspecific binding in brain homogenate for some of the model compounds. Fluoxetine and propranolol have high PS and low fu,brain. CP-141948, theobromine, and theophylline have low PS and high fu,brain.
|
Determination of PBPK Parameters. The dose-normalized plasma and brain concentrations and the corresponding BP time course of the seven compounds are presented in Fig. 2. The absorption of caffeine, CP-141938, NFPS, theobromine, and theophylline was best described by a first-order kinetics process. Fluoxetine and propranolol were treated as an intravenous bolus administration due to their rapid absorption. The heterogeneous way of treating the absorption process was only used to describe the plasma concentration-time profiles and should have no impact on the calculation of parameters related to brain drug disposition. The in vivo fu,brain was calculated from fu,plasma/Kp. Brain elimination rate constant (kout) was determined from PS · fu,brain/Vb, where the PS and fu,brain were calculated from the PBPK model and Vb is the physiological volume of rat brain, 6.56 ml/kg b.wt. (Peng et al., 2001). Plasma elimination rate constants (kel) for all compounds except fluoxetine were determined from Clp/Vp, where the Clp and Vp were calculated from the PBPK model. The terminal kel of fluoxetine was estimated from Clp, Cld, Vp, and Vsp using eq. 8. All the pharmacokinetic parameters are shown in Tables 2 and 3. Large variability of the estimated PS values for caffeine and theobromine was observed. This is likely due to the lack of data points before plasma and brain reached equilibrium (Fig. 2). The PBPK model was able to describe the BP values for all the data except the last time point (7 h) for CP-141938 (Fig. 2).
|
Determination of Brain Equilibrium Half-Life. The observed brain equilibrium half-life (Obs. t1/2eq) was visually estimated from Fig. 2 as the time for BP to reach 50% of the BP at the plateau between 4 and 6 h (Table 3). The plasma and brain concentrations of caffeine, propranolol, theobromine, and theophylline had a similar terminal t1/2, and their BP reached a plateau in less than 0.2 h. Their Obs. t1/2eq was assigned as 0.1 h. For CP-141938 and fluoxetine, the plasma and brain concentrations showed a similar terminal t1/2, and the BP reached a plateau in approximately 2 h. Their Obs. t1/2eq was assigned as 1 h. The brain concentration of NFPS exhibited a longer t1/2, and their BP did not reach a plateau at 24 h. Its t1/2eq was assigned as greater than 24 h. The t1/2eq and t1/2eq,in values were obtained using eqs. 14 and 16, respectively (Table 3).
Correlation of Pharmacokinetic Parameters. The relationship of in vivo log PS and the in situ log PS is presented in Fig. 3A (correlation coefficient R2 = 0.83). The regression equation is in vivo log PS = 1.16(in situ log PS) - 0.15. The relationship of in vivo log fu,brain and in vitro log fu,brain determined from brain homogenate is presented in Fig. 3B (R2 = 0.69). The data points appear to be clustered on the extremes of the range; therefore, more data are needed to evaluate the correlation. The relationship of log fu,plasma and log fu,brain determined from brain homogenate is presented in Fig. 3C (R2 = 0.91). The relationship of log t1/2eq,in and log(PS · fu,brain) is shown in Fig. 4A (R2 = 0.85). The relationship of log t1/2eq,in and in situ log PS is presented in Fig. 4B (R2 < 0.01).
|
|
|
|
Discussion |
|---|
|
TopAbstractMaterials and MethodsResultsDiscussionReferences |
|---|
). However, the exact contribution of BBB permeability, plasma binding, and brain tissue binding on the time to equilibrium has not been assessed systemically. Caffeine, CP-141938, fluoxetine, NFPS, propranolol, theobromine, and theophylline were selected as the model compounds because they displayed a marked difference in their BBB permeability (160-fold), unbound fraction in plasma (14-fold), and brain tissue (560-fold).
The present study demonstrates the utility of using a hybrid brain PBPK model to calculate kinetic parameters that are directly related to physiological processes (Gibaldi and Perrier, 1982). The hybrid brain PBPK model instead of a whole-body PBPK model was used in the present study because the objective of this work was to examine the effects of plasma binding, brain tissue binding, and BBB permeability on the brain equilibrium time. The brain PBPK model describes the observed brain and plasma concentration time course and BP time course data well, except the last data point for CP-141938 (Fig. 2). This may be due to an experimental variability or slow equilibrium compartments within brain tissue as suggested previously for another P-glycoprotein substrate (Chen and Pollack, 1998). The calculated in vivo log PS from the PBPK model correlates with the determined log PS using an in situ brain perfusion method (R2 = 0.83, Fig. 3A). This study is consistent with a previous study in which Takasato et al. (1984) showed that in vivo PS values of eight solvent-like compounds using pharmacokinetic analysis were consistent with the in situ PS values (Rapoport et al., 1979). In addition, the calculated in vivo log fu,brain from the PBPK model also correlates with the determined log fu,brain determined in brain homogenate (Fig. 3B, R2 = 0.69). However, the data points are clustered at the extremes of the range, and more studies are needed to evaluate the correlation.
The present study demonstrates theoretically and experimentally that the time to equilibrium is governed by the product of PS and fu,brain. The time to equilibrium can be assessed by the time to reach the plateau of BP-time profiles (Fig. 2) (Rapoport et al., 1982). According to eq. 13, compounds can be separated into two classes. For class I compounds, their kout is less than kel. Their BP increases over time after a single dose and cannot reach a plateau. Their brain terminal t1/2 is longer than the plasma t1/2. In this study, NFPS exhibited this profile (Fig. 2). Its kout (0.14 h-1) is less than its kel (0.21 h-1). Its BP kept increasing up to 24 h postdose, and its brain terminal t1/2 was longer than its plasma t1/2 (Fig. 2). For the class II compounds, their kout is greater than kel. Their BP increases initially and then reaches a plateau, and the terminal t1/2 of the brain concentration is equal to the plasma t1/2. The BP-time profile after a single dose is similar to the plasma concentration-time profile after an intravenous infusion (eq. 13) (Gibaldi and Perrier, 1982). Six of the seven compounds belong to the class II compounds. Their kout is greater than kel, and their BP increased after administration then reached a plateau approximately between 10 min and 2 h. Their brain and plasma t1/2 values were similar (Table 2; Fig. 2).
For class II compounds, the time to reach equilibrium can be quantified with brain equilibration half-life (t1/2eq), which is defined as the time for BP to reach 50% of its plateau level after single intravenous bolus dose. A similar approach has been used in literature to describe the rate of penetration into cerebrospinal fluid (Brodie et al., 1960). The t1/2eq calculated using eq. 14 is consistent with the visually observed t1/2eq (Obs. t1/2eq) from the BP-time profiles (Table 3). Because t1/2eq is only applicable to class II compounds, we propose using the intrinsic brain equilibrium half-life (t1/2eq,in) to describe the time to equilibrium. The t1/2eq,in is defined as the time for BP to reach 50% of its plateau level under the condition of constant plasma concentration (Patlak and Pettigrew, 1976). According to eq. 16, t1/2eq,in is inversely proportional to the product of PS and fu,brain. Compounds having the same PS · fu,brain should exhibit the same time to reach brain equilibrium. These predictions were in agreement with the simulated data.
The experimental results from this study also support that t1/2eq,in is determined by the product of PS and fu,brain. Log t1/2eq,in does not correlate with in situ log PS (R2 < 0.01), however, a correlation was observed between the in vivo log t1/2eq,in and log(PS · fu,brain) (R2 = 0.85, Fig. 4A). In our theoretical analyses, it was assumed that a transporter does not contribute significantly to brain drug disposition, nevertheless, it can be demonstrated that the effect will be the same if transporters do contribute to the disposition, in which case, the efflux clearance from brain to plasma instead of PS should be used.
There is an apparent inverse relationship of PS and fu,brain for some of the model compounds. CP-141938 and theobromine have a low PS but high fu,brain, fluoxetine and propranolol have a high PS but low fu,brain (Tables 1 and 2). This inverse relationship is expected because highly lipophilic compounds tend to have a high permeability to cross the BBB and high binding with brain tissue. In contrast, less lipophilic compounds tend to have a low permeability across the BBB and less binding to brain tissue. The inverse relationship between PS and fu,brain may provide a mechanistic explanation for the observation made by Hammarlund-Udenaes (1997) that compounds having much different BBB permeability are able to reach brain equilibrium quickly.
The inverse relationship between PS and fu,brain suggests that to search for rapid brain penetration compounds in drug discovery, both PS and fu,brain or the product of PS and fu,brain should be considered. A lead compound should not be eliminated as a candidate compound with quick onset of action only because it shows low permeability. For example, theobromine is a low PS (23 ml/h/kg) and high fu,brain (0.61) compound, resulting in PS · fu,brain of 14 ml/h/kg. In contrast, fluoxetine is a high PS (619 ml/h/kg) and low fu,brain (0.00094) compound, resulting in PS · fu,brain of 0.6 ml/h/kg. As expected from the PS · fu,brain, but not from the PS, the observed t1/2eq,in for theobromine (
0.1 h) was shorter than that of fluoxetine (1 h).
The theoretical analysis and PBPK simulation in this study demonstrate that plasma protein binding only determines the total brain drug concentration, not the equilibration time (eq. 16). Interestingly, log fu,plasma correlates with log fu,brain for the seven model compounds (R2 = 0.91, Fig. 3C). This apparent correlation is also supported by literature data. For a set of 18 compounds (Kalvass and Maurer, 2002), log fu,plasma correlates with log fu,brain after two outliers (compounds 4 and 8) were removed (R2 = 0.60). In addition, a good correlation was also observed for 32 compounds (R2 = 0.85) (Maurer et al., 2005). Hence, in theory, plasma protein binding per se is not related to the time to equilibrium and should not be considered as a criterion to select rapid brain equilibrium compounds in drug discovery. However, due to the empirical correlation between plasma binding and brain tissue binding, low plasma protein binding may be used as a surrogate.
Two approaches, namely a hybrid brain PBPK model and a two-compartmental brain model, have been employed in this study. The hybrid brain PBPK model approach was used to calculate in vivo fu,brain and PS values and to simulate brain and plasma data. The two-compartmental brain model is a simplified form of the hybrid brain PBPK model and was used to derive the explicit expression of the theoretical relationship. These two approaches are consistent with each other. For example, NFPS did not reach equilibrium up to 24 h postadministration. The PBPK model showed that its kel is greater than its kout. This observation is consistent with the prediction from the analyses of the two-compartmental model that equilibrium cannot be achieved if its kel is greater than kout. For the other six compounds, the PBPK model showed that the kel values are less than their kout. This observation is also consistent with the prediction from the analyses of the two-compartmental model that the equilibrium can be achieved if its kel is less than kout.
In summary, the present study demonstrates the utility of the PBPK model to calculate physiologically relevant pharmacokinetic parameters. We demonstrated that rapid brain equilibration requires a combination of high BBB permeability and low brain tissue binding. Importantly, high BBB permeability alone cannot guarantee a quick equilibration time. The strategy to select compounds with rapid brain penetration in drug discovery should identify those compounds with high PS and low nonspecific binding in brain tissue and plasma.
|
Footnotes |
|---|
ABBREVIATIONS: BBB, blood-brain barrier; CNS, central nervous system; NFPS, N[3-(4'-fluorophenyl)-3-(4'-phenylphenoxy)propyl]sarcosine; CP-141938, methoxy-3-[(2-phenyl-piperadinyl-3-amino)-methyl]-phenyl-N-methyl-methane-sulfonamide; HPLC, high-performance liquid chromatography; PBPK, physiologically based pharmacokinetics; PS, permeability-surface area product; BP, brain-to-plasma concentration ratio.
Address correspondence to: Dr. Xingrong Liu, Pfizer Global Research and Development, MS 8220-4167, Eastern Point Road, Groton, CT 06340. E-mail: xingrong.liu{at}pfizer.com
|
References |
|---|
|
TopAbstractMaterials and MethodsResultsDiscussionReferences |
|---|
Adachi Y, Suzuki H, and Sugiyama Y (2001) Comparative studies on in vitro methods for evaluating in vivo function of MDR1 P-glycoprotein. Pharm Res (NY) 18: 1660-1668.
Adams H and Leira E (1998) Treatment of acute ischemic stroke. Drugs Today 34: 655-660.
Akaike H (1976) An information criterion (AIC). Math Sci 14: 5-9.
Bonati M, Latini R, Sadurska B, Riva E, Galletti F, Borzelleca JF, Tarka SM, Arnaud MJ, and Garattini S (1984) Kinetics and metabolism of theobromine in male rats. Toxicology 30: 327-341.[CrossRef][Medline]
Brodie BB, Kurz H, and Schanker LS (1960) The importance of dissociation constant and lipid-solubility in influencing the passage of drugs into the cerebrospinal fluid. J Pharmacol Exp Ther 130: 20-25.
Brown RP, Delp MD, Lindstedt SL, Rhomberg LR, and Beliles RP (1997) Physiological parameter values for physiologically based pharmacokinetic models. Toxicol Ind Health 13: 407-484.[Medline]
Caccia S, Cappi M, Fracasso C, and Garattini S (1990) Influence of dose and route of administration on the kinetics of fluoxetine and its metabolite norfluoxetine in the rat. Psychopharmacology 100: 509-514.[CrossRef][Medline]
Chauvelot-Moachon L, Delers F, Pous C, Engler R, Tallet F, and Giroud JP (1988) Alpha-1-acid glycoprotein concentrations and protein binding of propranolol in Sprague-Dawley and Dark Agouti rat strains treated by phenobarbital. J Pharmacol Exp Ther 244: 1103-1108.
Chen C, Hanson E, Watson J, and Lee JS (2003a) P-glycoprotein limits the brain penetration of nonsedating but not sedating H1-antagonists. Drug Metab Dispos 31: 312-318.
Chen C, Liu X, and Smith BJ (2003b) Utility of mdr1-gene deficient mice in assessing the impact of P-glycoprotein on pharmacokinetics and pharmacodynamics in drug discovery and development. Curr Drug Metab 4: 272-291.[CrossRef][Medline]
Chen C and Pollack GM (1998) Altered disposition and antinociception of [D-penicillamine(2,5)] enkephalin in mdr1a-gene-deficient mice. J Pharmacol Exp Ther 287: 545-552.
Di L, Kerns EH, Fan K, McConnell OJ, and Carter GT (2003) High throughput artificial membrane permeability assay for blood-brain barrier. Eur J Med Chem 38: 223-232.[CrossRef][Medline]
Doran A, Obach RS, Smith BJ, Hosea NA, Becker S, Callegari E, Chen C, Chen X, Choo E, Cianfrogna J, et al. (2005) The impact of P-glycoprotein on the disposition of drugs targeted for indications of the central nervous system: evaluation using the mdr1a/1b knockout mouse model. Drug Metab Dispos 33: 165-174.
Gibaldi M and Perrier D (1982) Pharmacokinetics. Marcel Dekker, Inc., New York.
Golden PL and Pollack GM (2003) Blood-brain barrier efflux transport. J Pharm Sci 92: 1739-1753.[CrossRef][Medline]
Hammarlund-Udenaes M, Paalzow LK, and de Lange EC (1997) Drug equilibration across the blood-brain barrier—pharmacokinetic considerations based on the microdialysis method. Pharm Res (NY) 14: 128-134.
Hardman JG, Limbird LE, and Gilman AG (2001) Goodman and Gilman's The Pharmacological Basis of Therapeutics, 10th ed, McGraw-Hill, New York.
Kalvass JC and Maurer TS (2002) Influence of nonspecific brain and plasma binding on CNS exposure: implications for rational drug discovery. Biopharm Drug Dispos 23: 327-338.[CrossRef][Medline]
Khor SP, Bozigian H, and Mayersohn M (1991) Potential error in the measurement of tissue to blood distribution coefficients in physiological pharmacokinetic modeling. Residual tissue blood. II. Distribution of phencyclidine in the rat. Drug Metab Dispos 19: 486-490.[Abstract]
Li L, Gorukanti S, Choi YM, and Kim KH (2000) Rapid-onset intranasal delivery of anticonvulsants: pharmacokinetic and pharmacodynamic evaluation in rabbits. Int J Pharm 199: 65-76.[CrossRef][Medline]
Lin JH and Yamazaki M (2003) Clinical relevance of P-glycoprotein in drug therapy. Drug Metab Rev 35: 417-454.[CrossRef][Medline]
Liu X, LeCluyse EL, Brouwer KR, Lightfoot RM, Lee JI, and Brouwer KL (1999) Use of Ca2+ modulation to evaluate biliary excretion in sandwich-cultured rat hepatocytes. J Pharmacol Exp Ther 289: 1592-1599.
Liu X, Tu M, Kelly RS, Chen C, and Smith BJ (2004) Development of a computational approach to predict blood-brain barrier permeability. Drug Metab Dispos 32: 132-139.
Maurer TS, DeBartolo DB, Tess DA, and Scott DO (2005) Relationship between exposure and nonspecific binding of thirty-three central nervous system drugs in mice. Drug Metab Dispos 33: 175-181.
Patlak CS and Pettigrew KD (1976) A method to obtain infusion schedules for prescribed blood concentration time courses. J Appl Physiol 40: 458-463.
Peng B, Andrews J, Nestorov I, Brennan B, Nicklin P, and Rowland M (2001) Tissue distribution and physiologically based pharmacokinetics of antisense phosphorothioate oligonucleotide ISIS 1082 in rat. Antisense Nucleic Acid Drug Dev 11: 15-27.[CrossRef][Medline]
Polli JW, Wring SA, Humphreys JE, Huang L, Morgan JB, Webster LO, and Serabjit-Singh CS (2001) Rational use of in vitro P-glycoprotein assays in drug discovery. J Pharmacol Exp Ther 299: 620-628.
Rapoport SI, Fitzhugh R, Pettigrew KD, Sundaram U, and Ohno K (1982) Drug entry into and distribution within brain and cerebrospinal fluid: [14C]urea pharmacokinetics. Am J Physiol 242: R339-R348.
Rapoport SI, Ohno K, and Pettigrew KD (1979) Drug entry into the brain. Brain Res 172: 354-359.[CrossRef][Medline]
Shum L and Jusko WJ (1989) Effects of obesity and ancillary variables (dialysis time, drug, albumin and fatty acid concentrations) on theophylline serum protein binding. Biopharm Drug Dispos 10: 549-562.[CrossRef][Medline]
Smith BJ, Doran AC, McLean S, Tingley FD 3rd, O'Neil BT, and Kajiji SM (2001) P-glycoprotein efflux at the blood-brain barrier mediates differences in brain disposition and pharmacodynamics between two structurally related neurokinin-1 receptor antagonists. J Pharmacol Exp Ther 298: 1252-1259.
Takasato Y, Rapoport SI, and Smith QR (1984) An in situ brain perfusion technique to study cerebrovascular transport in the rat. Am J Physiol 247: H484-H493.
Tunblad K, Jonsson EN, and Hammarlund-Udenaes M (2003) Morphine blood-brain barrier transport is influenced by probenecid co-administration. Pharm Res (NY) 20: 618-623.
Wang Y, Wei Y, and Sawchuk RJ (1997) Zidovudine transport within the rabbit brain during intracerebroventricular administration and the effect of probenecid. J Pharm Sci 86: 1484-1490.[CrossRef][Medline]
Yasuhara M and Levy G (1988) Rapid development of functional tolerance to caffeine-induced seizures in rats. Proc Soc Exp Biol Med 188: 185-190.[Abstract]
This article has been cited by other articles:
|
|
 |
|
  X. Liu, C. Chen, and B. J. Smith Progress in Brain Penetration Evaluation in Drug Discovery and Development J. Pharmacol. Exp. Ther., May 1, 2008; 325(2): 349 - 356. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Fornaro, D. Li, J. Pan, and J. Belik Prenatal Exposure to Fluoxetine Induces Fetal Pulmonary Hypertension in the Rat Am. J. Respir. Crit. Care Med., November 15, 2007; 176(10): 1035 - 1040. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. G. Summerfield, K. Read, D. J. Begley, T. Obradovic, I. J. Hidalgo, S. Coggon, A. V. Lewis, R. A. Porter, and P. Jeffrey Central Nervous System Drug Disposition: The Relationship between in Situ Brain Permeability and Brain Free Fraction J. Pharmacol. Exp. Ther., July 1, 2007; 322(1): 205 - 213. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 X. Liu, B. J. Smith, C. Chen, E. Callegari, S. L. Becker, X. Chen, J. Cianfrogna, A. C. Doran, S. D. Doran, J. P. Gibbs, et al. Evaluation of Cerebrospinal Fluid Concentration and Plasma Free Concentration As a Surrogate Measurement for Brain Free Concentration Drug Metab. Dispos., September 1, 2006; 34(9): 1443 - 1447. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Becker and X. Liu EVALUATION OF THE UTILITY OF BRAIN SLICE METHODS TO STUDY BRAIN PENETRATION Drug Metab. Dispos., May 1, 2006; 34(5): 855 - 861. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. G. Summerfield, A. J. Stevens, L. Cutler, M. del Carmen Osuna, B. Hammond, S.-P. Tang, A. Hersey, D. J. Spalding, and P. Jeffrey Improving the in Vitro Prediction of in Vivo Central Nervous System Penetration: Integrating Permeability, P-glycoprotein Efflux, and Free Fractions in Blood and Brain J. Pharmacol. Exp. Ther., March 1, 2006; 316(3): 1282 - 1290. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 |
