ABSTRACT:Thirty-two structurally diverse drugs used for the treatment of various conditions of the central nervous system (CNS), along with two active metabolites, and eight non-CNS drugs were measured in brain, plasma, and cerebrospinal fluid in the P-glycoprotein (P-gp) knockout mouse model after subcutaneous administration, and the data were compared with corresponding data obtained in wild-type mice. Total brain-to-plasma (B/P) ratios for the CNS agents ranged from 0.060 to 24. Of the 34 CNS-active agents, only 7 demonstrated B/P area under the plasma concentration curve ratios between P-gp knockout and wild-type mice that did not differ significantly from unity. Most of the remaining drugs demonstrated 1.1-to 2.6-fold greater B/P ratios in P-gp knockout mice versus wild-type mice. Three, risperidone, its active metabolite 9-hydroxyrisperidone, and metoclopramide, showed marked differences in B/P ratios between knockout and wild-type mice (6.6-to 17-fold). Differences in B/P ratios and cerebrospinal fluid/ plasma ratios between wild-type and knockout animals were correlated. Through the use of this model, it appears that most CNSactive agents demonstrate at least some P-gp-mediated transport that can affect brain concentrations. However, the impact for the majority of agents is probably minor. The example of risperidone illustrates that even good P-gp substrates can still be clinically useful CNS-active agents. However, for such agents, unbound plasma concentrations may need to be greater than values projected using receptor affinity data to achieve adequate receptor occupancy for effect.Active transport mechanisms as determinants of drug absorption, distribution, and clearance have been the focus of considerable research effort over the past decade. Of the numerous transporter proteins recently investigated, the one for which the greatest amount of knowledge exists is P-glycoprotein (MDR1). Originally described as a transporter involved in imparting drug resistance to tumor cells, P-glycoprotein has been demonstrated to be important in reducing absorption of drugs from the intestinal lumen, in active secretion of drugs into urine and bile, and in extrusion of drugs from vital organs such as the brain and reproductive tissues (Troutman et al., 2002). As such, P-glycoprotein-mediated transport has become an important issue in the discovery and development of new drugs. For example, new compounds that are promising with regard to target receptor/ enzyme activity can be severely hampered in their ability to elicit pharmacological effects in vivo should they be good substrates for P-glycoprotein, especially if the route of administration is intended to be oral or the target tissues is one rich in P-glycoprotein activity. Furthermore, the potential for drug-drug interactions arises in the event that the P-glycoprotein substrate is coadministered with another agent that can inhibit P-glycoprotein.Several models have been developed to assess drugs as P-glycoprotein substrates. In vitro models have included the Caco...

Quantitative prediction of human pharmacokinetics is critical in assessing the viability of drug candidates and in determining first-in-human dosing. Numerous prediction methodologies, incorporating both in vitro and preclinical in vivo data, have been developed in recent years, each with advantages and disadvantages. However, the lack of a comprehensive data set, both preclinical and clinical, has limited efforts to evaluate the optimal strategy (or strategies) that results in quantitative predictions of human pharmacokinetics. To address this issue, the authors conducted a retrospective analysis using 50 proprietary compounds for which in vitro, preclinical pharmacokinetic data and oral single-dose human pharmacokinetic data were available. Five predictive strategies, involving either allometry or use of unbound intrinsic clearance from microsomes or hepatocytes, were then compared for their ability to predict human oral clearance, half-life through predictions of systemic clearance, volume of distribution, and bioavailability. Use of a single-species scaling approach with rat, dog, or monkey was as accurate as or more accurate than using multiple-species allometry. For those compounds cleared almost exclusively by P450-mediated pathways, scaling from human liver microsomes was as predictive as single-species scaling of clearance based on data from rat, dog, or monkey. These data suggest that use of predictive methods involving either single-species in vivo data or in vitro human liver microsomes can quantitatively predict human in vivo pharmacokinetics and suggest the possibility of streamlining the predictive methodology through use of a single species or use only of human in vitro microsomal preparations.

This article is available online at http://dmd.aspetjournals.org ABSTRACT:The objectives of this study were to generate a data set of bloodbrain barrier (BBB) permeability values for drug-like compounds and to develop a computational model to predict BBB permeability from structure. The BBB permeability, expressed as permeabilitysurface area product (PS, quantified as logPS), was determined for 28 structurally diverse drug-like compounds using the in situ rat brain perfusion technique. A linear model containing three descriptors, logD, van der Waals surface area of basic atoms, and polar surface area, was developed based on 23 compounds in our data set, where the penetration across the BBB was assumed to occur primarily by passive diffusion The blood-brain barrier (BBB 1 ) consists of a continuous layer of endothelial cells joined by tight junctions at the cerebral vasculature. It represents a physical and enzymatic barrier to restrict and regulate the penetration of compounds into and out of the brain and maintain the homeostasis of the brain microenvironment (Davson and Segal, 1995). Brain penetration is essential for compounds where the site of action is within the central nervous system, whereas BBB penetration needs to be minimized for compounds that target peripheral sites to reduce potential central nervous system-related side effects. Therefore, it is critical during the drug discovery phase to select compounds that have appropriate brain penetration properties. Brain penetration is commonly assessed by two experimental approaches, namely equilibrium distribution between brain and blood and BBB permeability. The equilibrium distribution is defined as the ratio of concentrations in brain and blood (BB, quantified as logBB). LogBB is determined at

This review discusses strategies to optimize brain penetration from the perspective of drug discovery and development. Brain penetration kinetics can be described by the extent and time to reach brain equilibrium. The extent is defined as the ratio of free brain concentration to free plasma concentration at steady state. For all central nervous system (CNS) drug discovery programs, optimization of the extent of brain penetration should focus on designing and selecting compounds having low efflux transport at the blood-brain barrier (BBB). The time to reach brain equilibrium is determined by both BBB permeability and brain tissue binding. Rapid brain penetration can be achieved by increasing passive permeability and reducing brain tissue binding. Although many drug transporters have been identified at the BBB, the available literature demonstrates only the in vivo functional importance of P-glycoprotein (P-gp) in limiting brain penetration of its substrates. Drug-drug interactions mediated by P-gp at the BBB are possible due to inhibition or induction of P-gp. For newly identified drug transporters at the BBB, more research is needed to reveal their in vivo significance. We propose the following strategies for addressing drug transporters at the BBB. 1) Drug discovery screens should be used to eliminate good P-gp substrates for CNS targets. Special consideration could be given to moderate P-gp substrates as potential CNS drugs based on a high unmet medical need and the presence of a large safety margin. 2) Selection of P-gp substrates as drug candidates for non-CNS targets can reduce their CNS-mediated side effects.Brain is separated from the systemic circulation by two barriers: the blood-brain barrier (BBB) and the blood-cerebrospinal-fluid barrier (BCSFB). The BBB is composed of cerebral endothelial cells that differ from those in the rest of the body by the presence of extensive tight junctions, absence of fenestrations, and sparse pinocytotic vesicular transport. The BCSFB is formed by a continuous layer of polarized epithelial cells that line the choroid plexus. The BBB and BCSFB exhibit very low paracellular permeability and express multiple drug transporters. These characteristics restrict the entry of hydrophilic compounds or efflux transport substrates into brain (Davson and Segal, 1995). In this review, we will summarize recent published data relevant to assess drug brain penetration and present the authors' opinions on how to effectively address BBB issues in drug discovery and development.

No abstract

This study was designed 1) to examine the effects of bloodbrain barrier (BBB) permeability [quantified as permeabilitysurface area product (PS)], unbound fraction in plasma (f u,plasma ), and brain tissue (f u,brain ) on the time to reach equilibrium between brain and plasma and 2) to investigate the drug discovery strategies to design and select compounds that can rapidly penetrate the BBB and distribute to the site of action. The pharmacokinetics of seven model compounds: caffeine, CP-141938 [methoxy-3-[(2-phenyl-piperadinyl-3-aminopropranolol, theobromine, and theophylline in rat brain and plasma after subcutaneous administration were studied. The in vivo log PS and log f u,brain calculated using a physiologically based pharmacokinetic model correlates with in situ log PS (R 2 ϭ 0.83) and in vitro log f u,brain (R 2 ϭ 0.69), where the in situ PS and in vitro f u,brain was determined using in situ brain perfusion and equilibrium dialysis using brain homogenate, respectively. The time to achieve brain equilibrium can be quantitated with a proposed parameter, intrinsic brain equilibrium, where V b is the physiological volume of brain. The in vivo log t 1/2eq,in does not correlate with in situ log PS (R 2 Ͻ 0.01) but correlates inversely with log(PS ⅐ f u,brain ) (R 2 ϭ 0.85). The present study demonstrates that rapid brain equilibration requires a combination of high BBB permeability and low brain tissue binding. A high BBB permeability alone cannot guarantee a rapid equilibration. The strategy to select compounds with rapid brain equilibration in drug discovery should identify compounds with high BBB permeability and low nonspecific binding in brain tissue.The blood-brain barrier (BBB) consists of a continuous layer of endothelial cells joined by tight junctions at the cerebral vasculature. It represents a physical and enzymatic barrier to restrict and regulate the penetration of compounds into and out of the brain and maintain the homeostasis of the brain microenvironment. Brain penetration is essential for compounds where the site of action is within the central nervous system (CNS), whereas BBB penetration needs to be minimized for compounds that target peripheral sites to reduce potential CNS-related side effects. Therefore, it is critical during the drug discovery phase to design and select compounds having appropriate brain penetration properties for drug targets that reside within and outside the CNS (Chen et al., 2003a; 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 brainplasma partition coefficient (K p ), 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...

This study was designed to evaluate the use of cerebrospinal fluid (CSF) drug concentration and plasma unbound concentration (C(u,plasma)) to predict brain unbound concentration (C(u,brain)). The concentration-time profiles in CSF, plasma, and brain of seven model compounds were determined after subcutaneous administration in rats. The C(u,brain) was estimated from the product of total brain concentrations and unbound fractions, which were determined using brain tissue slice and brain homogenate methods. For theobromine, theophylline, caffeine, fluoxetine, and propranolol, which represent rapid brain penetration compounds with a simple diffusion mechanism, the ratios of the area under the curve of C(u,brain)/C(CSF) and C(u,brain)/C(u,plasma) were 0.27 to 1.5 and 0.29 to 2.1, respectively, using the brain slice method, and were 0.27 to 2.9 and 0.36 to 3.9, respectively, using the brain homogenate method. A P-glycoprotein substrate, CP-141938 (methoxy-3-[(2-phenyl-piperadinyl-3-amino)-methyl]-phenyl-N-methyl-methane-sulfonamide), had C(u,brain)/C(CSF) and C(u,brain)/C(u,plasma) ratios of 0.57 and 0.066, using the brain slice method, and 1.1 and 0.13, using the brain homogenate method, respectively. The slow brain-penetrating compound, N[3-(4'-fluorophenyl)-3-(4'-phenylphenoxy)propyl-]sarcosine, had C(u,brain)/C(CSF) and C(u,brain)/C(u,plasma) ratios of 0.94 and 0.12 using the brain slice method and 0.15 and 0.018 using the brain homogenate method, respectively. Therefore, for quick brain penetration with simple diffusion mechanism compounds, C(CSF) and C(u,plasma) represent C(u,brain) equally well; for efflux substrates or slow brain penetration compounds, C(CSF) appears to be equivalent to or more accurate than C(u,plasma) to represent C(u,brain). Thus, we hypothesize that C(CSF) is equivalent to or better than C(u,plasma) to predict C(u,brain). This hypothesis is supported by the literature data.

ABSTRACT:(R)-3-[1-(2,6-Dichloro-3-fluoro-phenyl)-ethoxy]-5-(1-piperidin-4-yl-1H-pyrazol-4-yl)-pyridin-2-ylamine (PF02341066) was identified as an orally available, ATP-competitive small molecule inhibitor of cMet receptor tyrosine kinase. The objectives of the present studies were to characterize 1) the pharmacokinetic-pharmacodynamic relationship of the plasma concentrations of PF02341066 to cMet phosphorylation in tumor (biomarker) and 2) the relationship of cMet phosphorylation to antitumor efficacy (pharmacological response). Athymic mice implanted with GTL16 gastric carcinoma or U87MG glioblastoma xenografts were treated with PF02341066 once daily at doses selected to encompass ED 50 values. Plasma concentrations of PF02341066 were best described by a one-compartment pharmacokinetic model. A time-delay (hysteresis) was observed between the plasma concentrations of PF02341066 and the cMet phosphorylation response. A link model was therefore used to account for this hysteresis. The model fitted the time courses of cMet phosphorylation well, suggesting that the main reason for the hysteresis is a rate-limiting distribution from plasma into tumor. The EC 50 and EC 90 values were estimated to be 19 and 167 ng/ml, respectively. For tumor growth inhibition, the exponential tumor growth model fitted the time courses of individual tumor growth inhibition well. The EC 50 for the GTL16 tumor growth inhibition was estimated to be 213 ng/ml. Thus, the EC 90 for the inhibition of cMet phosphorylation corresponded to the EC 50 for the tumor growth inhibition, suggesting that near-complete inhibition of cMet phosphorylation (>90%) is required to significantly inhibit tumor growth (>50%). The present results will be helpful in determining the appropriate dosing regimen and in guiding dose escalation to rapidly achieve efficacious systemic exposure in the clinic.Pharmacokinetic-pharmacodynamic (PKPD) modeling is increasingly being applied in drug discovery and development. Specific applications include 1) the selection of drug candidates with most favorable PKPD properties and 2) the prediction of exposure response in patients with the aim of optimizing the design of early clinical trials. The increased understanding of drug action derived from PKPD-based drug development leads to more information, especially with regard to the identification of drug dosage regimen that results in optimal therapeutic outcome (Derendorf et al., 2000;Lesko et al., 2000;Chien et al., 2005). The use of PKPD modeling in this context relies on prediction of the time course of drug effects in patients, using information from preclinical investigation. Preclinical studies are useful alternatives to investigate PKPD relationships to get insight into the in vivo mechanism of drug action. The integration of PKPD modeling and simulation in drug development has provided opportunities to accelerate the evaluation of new chemical entities in the clinic. Thus, the PKPD investigation could contribute to shortening the overall period of drug development.