Pharmacokinetics, Pharmacodynamics, and Safety of Edoxaban in Pediatric Subjects: A Phase I Single-Dose Study.

This was an open-label, single-dose, phase I study to characterize the pharmacokinetics (PKs), pharmacodynamics (PDs), and safety of edoxaban in pediatric subjects from birth to 18 years at risk for venous thromboembolism (VTE). Children requiring anticoagulant therapy were enrolled into 5 age cohorts (0 to < 6 months (N = 12), 0.5 to < 2 years (N = 13), 2 to < 6 years (N = 13), 6 to < 12 years (N = 13), and 12 to < 18 years (N = 15)) receiving tablet or oral suspension of edoxaban at doses expected to be equivalent to 30 or 60 mg once daily (q.d.) in adult subjects with VTE. Sixty-six pediatric subjects were enrolled and completed the study. Edoxaban plasma concentration peaked between 1 and 3 hours and declined rapidly until 4-8 hours. The range of mean total apparent clearance across 5 age cohorts at low and high doses was 0.47 to 1.11 L/h/kg. The ranges of mean volume of central compartment and apparent peripheral volume were 2.31 to 3.59 L/kg and 1.92 to 4.14 L/kg, respectively. Across all age groups, the estimated median exposures were within the 0.5- to 1.5-fold of the median area under the plasma drug concentration-time curve (AUC) in adult subjects receiving corresponding doses (30 mg q.d. for low dose and 60 mg q.d. for high dose). In all age groups, PD parameters (prothrombin time, activated partial thromboplastin time, and anti-Factor Xa activity) showed a linear PK-PD relationship and were in line with previous adult data. The results support further evaluation of the pediatric doses in larger pivotal trials.

Virtual Populations for Quantitative Systems Pharmacology Models.

Quantitative systems pharmacology (QSP) places an emphasis on dynamic systems modeling, incorporating considerations from systems biology modeling and pharmacodynamics. The goal of QSP is often to quantitatively predict the effects of clinical therapeutics, their combinations, and their doses on clinical biomarkers and endpoints. In order to achieve this goal, strategies for incorporating clinical data into model calibration are critical. Virtual population (VPop) approaches facilitate model calibration while faced with challenges encountered in QSP model application, including modeling a breadth of clinical therapies, biomarkers, endpoints, utilizing data of varying structure and source, capturing observed clinical variability, and simulating with models that may require more substantial computational time and resources than often found in pharmacometrics applications. VPops are frequently developed in a process that may involve parameterization of isolated pathway models, integration into a larger QSP model, incorporation of clinical data, calibration, and quantitative validation that the model with the accompanying, calibrated VPop is suitable to address the intended question or help with the intended decision. Here, we introduce previous strategies for developing VPops in the context of a variety of therapeutic and safety areas: metabolic disorders, drug-induced liver injury, autoimmune diseases, and cancer. We introduce methodological considerations, prior work for sensitivity analysis and VPop algorithm design, and potential areas for future advancement. Finally, we give a more detailed application example of a VPop calibration algorithm that illustrates recent progress and many of the methodological considerations. In conclusion, although methodologies have varied, VPop strategies have been successfully applied to give valid clinical insights and predictions with the assistance of carefully defined and designed calibration and validation strategies. While a uniform VPop approach for all potential QSP applications may be challenging given the heterogeneity in use considerations, we anticipate continued innovation will help to drive VPop application for more challenging cases of greater scale while developing new rigorous methodologies and metrics.

Model-Based Meta-Analysis Compares DAS28 Rheumatoid Arthritis Treatment Effects and Suggests an Expedited Trial Design for Early Clinical Development.

A nonlinear mixed effects modeling approach was used to conduct a model-based meta-analysis (MBMA) of longitudinal, summary-level, baseline-corrected 28-joint Disease Activity Score (ΔDAS28) clinical trial data from seven approved rheumatoid arthritis (RA) drugs (abatacept, adalimumab, certolizumab, etanercept, rituximab, tocilizumab, and tofacitinib), representing 130 randomized clinical trials in 27,355 patients. All of the drugs except tocilizumab were found to have relatively similar ΔDAS28 time courses and efficacy (baseline-corrected and placebo-corrected) at 24 weeks and beyond of approximately 0.87-1.3 units in the typical RA patient population. Tocilizumab was estimated to have a differentially greater response of 1.99 at 24 weeks, likely due to its disproportionate effect on the acute-phase cytokine interleukin-6. Baseline DAS28, disease duration, percentage of male participants, and the year of conduct of the trial were found to have statistically significant effects on the timing and/or magnitude of ΔDAS28 in the control arms. Clinical trial simulations using the present MBMA indicated that abatacept, certolizumab, etanercept, tocilizumab, and tofacitinib would be expected to have a greater than 70% probability of showing a statistically significant difference vs. control at Week 6 with a sample size of ~ 30 patients per arm. In future RA clinical trials, an interim analysis conducted as early as 6 weeks after treatment initiation, with relatively small sample sizes, should be sufficient to detect the ΔDAS28 treatment effect vs. placebo.

Modeling and Simulation of the Pharmacokinetics and Target Engagement of an Antagonist Monoclonal Antibody to Interferon-γ-Induced Protein 10, BMS-986184, in Healthy Participants to Guide Therapeutic Dosing.

BMS-986184 is a human, second-generation, anti-interferon-γ-induced protein 10 (IP-10) monoclonal antibody. In this study the pharmacokinetics and target engagement (TE) of BMS-986184 in healthy participants were characterized using population-based target-mediated drug disposition (TMDD) modeling and data from a first-in-human study (NCT02864264). The results of the first-in-human study and the model generated were used to conduct stochastic simulations of a virtual population of healthy participants to predict pharmacokinetic exposures and TE responses for different dosage regimens. A 2-compartment, 2-target, TMDD structural model, assuming quasi-steady-state and stimulated production on treatment, was developed by simultaneous fitting of the total drug, serum-free IP-10, and serum total IP-10 concentration data, with the second unobservable target contribution to drug elimination described by the Michaelis-Menten elimination term. Model evaluation confirmed agreement between model predictions and observed data. Simulation of a virtual population of healthy individuals demonstrated that steady state was reached at the eighth dosing interval, and that around 150 mg subcutaneously every other week could be a suitable target dosage regimen for future clinical trials. Integrated modeling strategies such as this can be used to help guide rational clinical trial development of drugs with TMDD, leading to improved dose selection and greater patient benefits.

Evaluating a Multiscale Mechanistic Model of the Immune System to Predict Human Immunogenicity for a Biotherapeutic in Phase 1.

A mechanistic model of the immune response was evaluated for its ability to predict anti-drug antibody (ADA) and their impact on pharmacokinetics (PK) and pharmacodynamics (PD) for a biotherapeutic in a phase 1 clinical trial. Observed ADA incidence ranged from 33 to 67% after single doses and 27-50% after multiple doses. The model captured the single dose incidence well; however, there was overprediction after multiple dosing. The model was updated to include a T-regulatory (Treg) cell mediated tolerance, which reduced the overprediction (relative decrease in predicted incidence rate of 21.5-59.3% across multidose panels) without compromising the single dose predictions (relative decrease in predicted incidence rate of 0.6-13%). The Treg-adjusted model predicted no ADA impact on PK or PD, consistent with the observed data. A prospective phase 2 trial was simulated, including co-medication effects in the form of corticosteroid-induced immunosuppression. Predicted ADA incidences were 0-10%, depending on co-medication dosage. This work demonstrates the utility in applying an integrated, iterative modeling approach to predict ADA during different stages of clinical development.

QSP Toolbox: Computational Implementation of Integrated Workflow Components for Deploying Multi-Scale Mechanistic Models.

Quantitative systems pharmacology (QSP) modeling has become increasingly important in pharmaceutical research and development, and is a powerful tool to gain mechanistic insights into the complex dynamics of biological systems in response to drug treatment. However, even once a suitable mathematical framework to describe the pathophysiology and mechanisms of interest is established, final model calibration and the exploration of variability can be challenging and time consuming. QSP models are often formulated as multi-scale, multi-compartment nonlinear systems of ordinary differential equations. Commonly accepted modeling strategies, workflows, and tools have promise to greatly improve the efficiency of QSP methods and improve productivity. In this paper, we present the QSP Toolbox, a set of functions, structure array conventions, and class definitions that computationally implement critical elements of QSP workflows including data integration, model calibration, and variability exploration. We present the application of the toolbox to an ordinary differential equations-based model for antibody drug conjugates. As opposed to a single stepwise reference model calibration, the toolbox also facilitates simultaneous parameter optimization and variation across multiple in vitro, in vivo, and clinical assays to more comprehensively generate alternate mechanistic hypotheses that are in quantitative agreement with available data. The toolbox also includes scripts for developing and applying virtual populations to mechanistic exploration of biomarkers and efficacy. We anticipate that the QSP Toolbox will be a useful resource that will facilitate implementation, evaluation, and sharing of new methodologies in a common framework that will greatly benefit the community.

Use of systems pharmacology modeling to elucidate the operating characteristics of SGLT1 and SGLT2 in renal glucose reabsorption in humans.

In the kidney, glucose in glomerular filtrate is reabsorbed primarily by sodium-glucose cotransporters 1 (SGLT1) and 2 (SGLT2) along the proximal tubules. SGLT2 has been characterized as a high capacity, low affinity pathway responsible for reabsorption of the majority of filtered glucose in the early part of proximal tubules, and SGLT1 reabsorbs the residual glucose in the distal part. Inhibition of SGLT2 is a viable mechanism for removing glucose from the body and improving glycemic control in patients with diabetes. Despite demonstrating high levels (in excess of 80%) of inhibition of glucose transport by SGLT2 in vitro, potent SGLT2 inhibitors, e.g., dapagliflozin and canagliflozin, inhibit renal glucose reabsorption by only 30-50% in clinical studies. Hypotheses for this apparent paradox are mostly focused on the compensatory effect of SGLT1. The paradox has been explained and the role of SGLT1 demonstrated in the mouse, but direct data in humans are lacking. To further explore the roles of SGLT1/2 in renal glucose reabsorption in humans, we developed a systems pharmacology model with emphasis on SGLT1/2 mediated glucose reabsorption and the effects of SGLT2 inhibition. The model was calibrated using robust clinical data in the absence or presence of dapagliflozin (DeFronzo et al., 2013), and evaluated against clinical data from the literature (Mogensen, 1971; Wolf et al., 2009; Polidori et al., 2013). The model adequately described all four data sets. Simulations using the model clarified the operating characteristics of SGLT1/2 in humans in the healthy and diabetic state with or without SGLT2 inhibition. The modeling and simulations support our proposition that the apparent moderate, 30-50% inhibition of renal glucose reabsorption observed with potent SGLT2 inhibitors is a combined result of two physiological determinants: SGLT1 compensation and residual SGLT2 activity. This model will enable in silico inferences and predictions related to SGLT1/2 modulation.

Quantitative Systems Pharmacology can reduce attrition and improve productivity in pharmaceutical research and development.

The empirical hypothesis generation and testing approach to pharmaceutical research and development (R&D), and biomedical research has proven very effective over the last half-century; resulting in tremendous increases productivity and the rates of approval for new drug applications at the Food and Drug Administration (FDA). However, as discovery of new therapeutic approaches for diseases with unmet medical need becomes more challenging, the productivity and efficiency of the traditional approach to drug discovery and development is diminishing. Innovative approaches are needed, such as those offered by Quantitative Systems Pharmacology (QSP) modeling and simulation. This "systems" approach to modeling and simulation can be used to guide the hypothesis generation and testing process in pharmaceutical R&D, in a manner similar to its adoption in other industries in the past. Embedding QSP into the existing processes within pharmaceutical discovery and development will be required in order to realize the full beneficial impact of this innovative approach.

Virtual Systems Pharmacology (ViSP) software for simulation from mechanistic systems-level models.

Multiple software programs are available for designing and running large scale system-level pharmacology models used in the drug development process. Depending on the problem, scientists may be forced to use several modeling tools that could increase model development time, IT costs and so on. Therefore, it is desirable to have a single platform that allows setting up and running large-scale simulations for the models that have been developed with different modeling tools. We developed a workflow and a software platform in which a model file is compiled into a self-contained executable that is no longer dependent on the software that was used to create the model. At the same time the full model specifics is preserved by presenting all model parameters as input parameters for the executable. This platform was implemented as a model agnostic, therapeutic area agnostic and web-based application with a database back-end that can be used to configure, manage and execute large-scale simulations for multiple models by multiple users. The user interface is designed to be easily configurable to reflect the specifics of the model and the user's particular needs and the back-end database has been implemented to store and manage all aspects of the systems, such as Models, Virtual Patients, User Interface Settings, and Results. The platform can be adapted and deployed on an existing cluster or cloud computing environment. Its use was demonstrated with a metabolic disease systems pharmacology model that simulates the effects of two antidiabetic drugs, metformin and fasiglifam, in type 2 diabetes mellitus patients.

Quantitative Extrapolation: An Approach to Validation of Adult Drug Efficacy in Pediatric Subjects.

Confirmation of efficacy in pediatric drug development has traditionally required large, fully powered efficacy studies that have proven to have major feasibility and ethical challenges. Extrapolation of efficacy in the framework provided by the US Food and Drug Administration and European Medicines Agency is an appropriate solution when there is similarity of disease. When there is uncertainty regarding the degree of disease similarity, partial extrapolation may be utilized. The authors propose a more quantitative approach to partial extrapolation (ie, quantitative extrapolation), involving (1) integration of adult pharmacokinetic (PK), pharmacodynamic (PD), and clinical outcome data using pharmacometric models, (2) extrapolation using the adult pharmacometric model to predict PD and efficacy outcomes in pediatric subjects, and (3) validation of pediatric predictions with a streamlined plan of pediatric trials (ie, a quantitative extrapolation plan). A case study is presented for quantitative extrapolation using dipeptidyl peptidase 4 (DPP-4) inhibitors. In this example, the authors demonstrate how adult PK, PD, and HbA1c data can be integrated using a pharmacometric model for DPP-4 inhibitors with pediatric dose selection and efficacy validated with relatively few pediatric subjects.

Tamoxifen induces expression of immune response-related genes in cultured normal human mammary epithelial cells.

Use of tamoxifen is associated with a 50% reduction in breast cancer incidence and an increase in endometrial cancer incidence. Here, we documented tamoxifen-induced gene expression changes in cultured normal human mammary epithelial cells (strains 5, 16, and 40), established from tissue taken at reduction mammoplasty from three individuals. Cells exposed to 0, 10, or 50 micromol/L of tamoxifen for 48 hours were evaluated for (E)-alpha-(deoxyguanosine-N(2)-yl)-tamoxifen (dG-N(2)-TAM) adduct formation using TAM-DNA (DNA modified with dG-N(2)-TAM) chemiluminescence immunoassay, gene expression changes using National Cancer Institute DNA-oligonucleotide microarray, and real-time PCR. At 48 hours, cells exposed to 10 and 50 micromol/L of tamoxifen were 85.6% and 48.4% viable, respectively, and there were no measurable dG-N(2)-TAM adducts. For microarrays, cells were exposed to 10 micromol/L of tamoxifen and genes with expression changes of >3-fold were as follows: 13 genes up-regulated and 1 down-regulated for strain 16; 17 genes up-regulated for strain 5, and 11 genes up-regulated for strain 40. Interferon-inducible genes (IFITM1, IFIT1, MXI, and GIP3), and a potassium ion channel (KCNJ1) were up-regulated in all three strains. No significant expression changes were found for genes related to estrogen or xenobiotic metabolism. Real-time PCR revealed the up-regulation of IFNA1 and confirmed the tamoxifen-induced up-regulation of the five other genes identified by microarray, with the exception of GIP3 and MX1, which were not up-regulated in strain 40. Induction of IFN-related genes in the three normal human mammary epithelial cell strains suggests that, in addition to hormonal effects, tamoxifen exposure may enhance immune response in normal breast tissue.

Chemoimmunotherapy reinduction with epratuzumab in children with acute lymphoblastic leukemia in marrow relapse: a Children's Oncology Group Pilot Study.

PURPOSE: To determine the tolerability and serum concentration of epratuzumab, a humanized monoclonal antibody targeting CD22, administered alone and in combination with reinduction chemotherapy in children with relapsed acute lymphoblastic leukemia (ALL), and to preliminarily assess tumor targeting and efficacy. PATIENTS AND METHODS: Therapy consisted of a single-agent phase (epratuzumab 360 mg/m(2)/dose intravenously twice weekly x four doses), followed by four weekly doses of epratuzumab in combination with standard reinduction chemotherapy. Morphologic and minimal residual disease (MRD) responses were determined at the end of this 6-week period. Serum concentrations of epratuzumab were determined before and 30 minutes after infusions, and CD22 targeting efficiency was determined by quantifying changes in CD22 expression after epratuzumab administration. RESULTS: Fifteen patients (12 fully assessable for toxicity) with first or later CD22-positive ALL marrow relapse enrolled on the feasibility portion of this study from December 2005 to June 2006. Two dose-limiting toxicities occurred: one grade 4 seizure of unclear etiology and one asymptomatic grade 3 ALT elevation. In all but one patient, surface CD22 was not detected by flow cytometry on peripheral blood leukemic blasts within 24 hours of drug administration, indicating effective targeting of leukemic cells by epratuzumab. Nine patients achieved a complete remission after chemoimmunotherapy, seven of whom were MRD negative. CONCLUSION: Treatment with epratuzumab plus standard reinduction chemotherapy is feasible and acceptably tolerated in children with relapsed CD22-positive ALL. CD22 targeting was efficient, and the majority of patients achieved favorable early responses.

Identification and characterization of genetic variation in the folylpolyglutamate synthase gene.

Folylpolyglutamate synthase (FPGS) catalyzes the polyglutamation of folic acid, methotrexate, and pemetrexed to produce highly active metabolites. To characterize genetic variation in the FPGS gene, FPGS, have resequenced the gene in four different ethnic populations. Thirty-four single nucleotide polymorphisms were identified including five nonsynonymous coding single nucleotide polymorphisms that altered the FPGS protein sequence: F13L and V22I polymorphisms in the mitochondrial isoform of FPGS, and R466/424C, A489/447V, and S499/457F polymorphisms, which exist in both the mitochondrial and cytosolic isoforms. When expressed in AuxB1 cells, the A447V cytosolic variant was functionally similar to the wild-type cytosolic (WT Cyt) allozyme, whereas the R424C and S457F cytosolic variants were reduced by approximately 2-fold in protein expression compared with WT Cyt (P < 0.01). The intrinsic clearance of glutamate was reduced by 12.3-fold (R424C, P < 0.01) and 6.2-fold (S457F, P < 0.01), whereas the intrinsic clearance of methotrexate was reduced by 4.2-fold (R424C, P < 0.05) and 5.4-fold (S457F, P < 0.05) in these two cytosolic variants when compared with the WT Cyt isoform. Additionally, the in vitro enzyme velocity at saturating pemetrexed concentrations was reduced by 1.6-fold (R424C, P < 0.05) and 2.6-fold (S457F, P < 0.01) compared with WT Cyt. AuxB1 cells harboring these same cytosolic variant allozymes displayed significant increases in the EC(50) for folic acid and in the IC(50) values for both methotrexate and pemetrexed relative to the WT Cyt form of FPGS. These observations suggest that genetic variations in FPGS may alter the efficacy of antifolate therapy in cancer patients.

C-terminal modification is required for GABARAP-mediated GABA(A) receptor trafficking.

We investigated the ubiquitin-like modification of GABA(A) receptor-associated protein (GABARAP) and its function. A fusion protein of GABARAP with v5 in the N terminus and myc in the C terminus was expressed in rat cultured hippocampal neurons and PC12 cells. Western blotting with antibodies to v5 and myc revealed that the C terminus of GABARAP was cleaved off. Cleavage was blocked by mutating the C-terminal Gly116 to Ala, suggesting that G116 is required for the processing. Unlike ubiquitin, GABARAP was not incorporated covalently into higher-molecular-weight protein complexes. Nor was GABARAP degraded by ubiquitinylation through the proteasome, although GABARAP formed noncovalent dimers. Immunofluorescent confocal microscopy demonstrated that recombinantly expressed GABARAP was diffusely localized in PC12 cells. However, prevention of C-terminal processing in the mutant GABARAP(G116A) resulted in redistribution to the Golgi. In neurons, punctate cytoplasmic staining of GABARAP was seen in soma and processes, whereas GABARAP(G116A) was limited to soma. Compared with wild-type GABARAP, the colocalization and interaction of GABARAP(G116A) with GABA(A) receptors were significantly reduced, resulting in a reduction in expression of receptors in the plasma membrane. When alpha1beta2gamma2S-containing GABA(A) receptors were expressed in oocytes, the increased surface expression of GABA(A) receptors, as shown by increased GABA currents and surface-accessible GABA(A) receptor subunit polypeptides resulting from GABARAP coexpression, was prevented by mutation G116A. In addition, the distribution of NSF (N-ethylmaleimide-sensitive factor) was affected in GABARAP(G116A)-expressing neurons. These results suggest that glycine 116 is required for C-terminal processing of GABARAP and that processing is essential for the localization of GABARAP and its functions as a trafficking protein.

Cisplatin-DNA damage in p21WAF1/Cip1 deficient mouse keratinocytes exposed to cisplatin.

In response to DNA damage, cell cycle arrest, apoptosis, and DNA repair are mediated by a TP53 pathway that induces p21(WAF1/Cip1). The chemotherapeutic drug cis-diamminedichloroplatinum-II (cisplatin) damages cellular DNA by forming cis-diammineplatinum-N(7)-d[GpG] and cis-diammine-platinum-N(7)-d[ApG] adducts. To investigate the role of p21, skin keratinocytes from p21(WAF1/Cip1) wild-type (+/+), heterozygous (+/-), and null (-/-) mice, cultured in calcium levels designed to maintain a proliferating state, were exposed to 5 microM cisplatin continuously for 0, 8, 24, 48 and 72 h. At all time points the (+/-) cells had the fewest Pt-DNA adducts, and at 24 h mean Pt-DNA adduct levels were 541, 153 and 779 fmol adduct/mug DNA for p21(WAF1/Cip1) (+/+), (+/-) and (-/-) cells, respectively [P < 0.05 for (+/+) versus (+/-) and (-/-) versus (+/-)]. In order to understand underlying events, we examined p21(WAF1/Cip1) messenger RNA (mRNA), cell cycle arrest, and apoptosis in these cells. At 48 h of cisplatin exposure p21(WAF1/Cip1) mRNA expression was 2-fold higher in the (+/+) cells, compared to the (+/-) cells. At 24 h, the % of cells in S-phase in cisplatin-exposed cultures, compared to unexposed cultures, was decreased by 51, 40 and 11% in p21(WAF1/Cip1) (+/+), (+/-) and (-/-) cells, respectively (P = 0.04, ANOVA). At 24, 48 and 72 h the % of cisplatin-exposed (+/+) cells in apoptosis was 9.4-10.5%, while the cisplatin-exposed (+/-) and (-/-) cells had 1.2-3.7% of cells in apoptosis. The data support the interpretation that DNA replication arrest and apoptosis do not completely explain the low levels of Pt-DNA adducts in the (+/-) cells, and suggest that p21(WAF1/Cip1) controls activity resulting in either low Pt-DNA adduct formation or enhanced Pt-DNA adduct removal.

GABAA receptor-associated protein regulates GABAA receptor cell-surface number in Xenopus laevis oocytes.

GABA(A) receptor-associated protein (GABARAP) was isolated previously in a yeast two-hybrid screen using the intracellular loop of the gamma2 subunit of the GABA(A) receptor as bait. GABARAP has been shown to participate in the membrane-clustering and intracellular-trafficking of GABA(A) receptors, including a stimulation of the surface expression of GABA(A) receptors. To assess this quantitatively, we used Xenopus laevis oocytes expressing alpha1beta2gamma2S-containing GABA(A) receptors to demonstrate that coexpression of GABARAP increased net surface levels of GABA(A) receptors as shown by both increased GABA currents and surface-expressed protein. This GABARAP stimulation of GABA currents required the receptor gamma2 subunit and full-length GABARAP: deletion of the microtubule-binding domain (amino acids 1-22) or disrupting the polymerization of microtubules abolished the enhancement, indicating that the effect of GABARAP was derived from the interaction with microtubules. GABARAP coexpression did not alter the general properties of GABA(A) receptors such as sensitivity to GABA or benzodiazepines, but it increased surface levels of receptor protein in oocytes. Rather, it seems to supplement inadequate amounts of endogenous GABARAP to support optimum trafficking and/or stabilization of surface GABA(A) receptors.

GABAA receptor-associated protein traffics GABAA receptors to the plasma membrane in neurons.

The trafficking of GABA(A) receptors is an important component of the pathway that regulates plasticity of inhibitory synapses. The 17 kDa GABA(A) receptor-associated protein (GABARAP) has been implicated in the trafficking of GABA(A) receptors because of its ability to interact not only with the gamma2 subunit of the receptor but also with microtubules and the N-ethylmaleimide-sensitive factor (NSF). To elucidate the role of GABARAP in the trafficking of GABA(A) receptors, we have constructed a yellow fluorescent protein (YFP) fusion protein of GABARAP and expressed it in neurons using adenovirus, so that its function may be examined. YFP-GABARAP colocalized with gamma2 subunit-containing GABA(A) receptors and NSF to the perinuclear cytoplasm in cultured hippocampal neurons and to the proximal regions of dendrites that are making synaptic contact. Expression of YFP-GABARAP in Cos7 cells and cultured hippocampal neurons was able to increase the level of GABA(A) receptors detected at the plasma membrane, even at low levels of YFP-GABARAP expression. This effect is specific to the function of GABARAP on GABA(A) receptor trafficking, because point mutations in the gamma2-binding domain of YFP-GABARAP interfered with the ability of YFP-GABARAP to increase GABA(A) receptor surface levels. These mutations also disrupted the colocalization of YFP-GABARAP with the gamma2 subunit and with NSF in hippocampal neurons. The results of this study show for the first time that GABARAP has a functional effect on the trafficking of GABA(A) receptors and provide decisive evidence for the role of GABARAP in transporting GABA(A) receptors to the plasma membrane in neurons.