Partha Nandy

Janssen Research & Development, LLC, Raritan, New Jersey, United States

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Publications (22)76.76 Total impact

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    ABSTRACT: Abiraterone acetate, an androgen biosynthesis inhibitor, prolongs survival in men with metastatic castration-resistant prostate cancer (mCRPC) in the pre- and post-chemotherapy setting as demonstrated by the pivotal phase III studies COU-AA-301 and COU-AA-302. We performed population pharmacokinetic analyses to estimate pharmacokinetic parameters after oral administration of 1,000 mg/day of abiraterone acetate in patients with mCRPC, with or without prior chemotherapy, and after a single 1,000 mg dose in healthy volunteers. The study objectives were to determine consistency between patient populations and to characterize factors that may influence abiraterone pharmacokinetics.
    Clinical Pharmacokinetics 09/2014; · 5.49 Impact Factor
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    ABSTRACT: The objective was to develop a quantitative model of disease progression of knee osteoarthritis over 6 years using the total WOMAC score from patients enrolled into the Osteoarthritis Initiative (OAI) study. The analysis was performed using data from the Osteoarthritis Initiative database. The time course of the total WOMAC score of patients enrolled into the progression cohort was characterized using non-linear mixed effect modeling in NONMEM. The effect of covariates on the status of the disease and the progression rate was investigated. The final model provided a good description of the experimental data using a linear progression model with a common baseline (19 units of the total WOMAC score). The WOMAC score decreased by 1.77 units/year in 89% of the population or increased by 1.74 units/year in 11% of the population. Multiple covariates were found to affect the baseline and the rate of progression, including BMI, sex, race, the use of pain medications, and the limitation in activity due to symptoms. A mathematical model to describe the disease progression of osteoarthritis in the studied population was developed. The model identified two subpopulations with increasing or decreasing total WOMAC score over time, and the effect of important covariates was quantified.
    The Journal of Clinical Pharmacology 09/2014; · 2.84 Impact Factor
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    ABSTRACT: Mixed-effects beta regression (BR), boundary-inflated beta regression (ZOI), and coarsening model (CO) were investigated for analyzing bounded outcome scores with data at the boundaries in the context of Alzheimer's disease. Monte Carlo simulations were conducted to simulate disability assessment for dementia (DAD) scores using these three models, and each set of simulated data were analyzed by the original simulation model. One thousand trials were simulated, and each trial contained 250 subjects. For each subject, DAD scores were simulated at baseline, 13, 26, 39, 52, 65, and 78 weeks. The simulation-reestimation exercise showed that all the three models could reasonably recover their true parameter values. The bias of the parameter estimates of the ZOI model was generally less than 1%, while the bias of the CO model was mainly within 5%. The bias of the BR model was slightly higher, i.e., less than or in the order of 20%. In the application to real-world DAD data from clinical studies, examination of prediction error and visual predictive check (VPC) plots suggested that both BR and ZOI models had similar predictive performance and described the longitudinal progression of DAD slightly better than the CO model. In conclusion, the investigated three modeling approaches may be sensible choices for bounded outcome scores with data on the edges. Prediction error and VPC plots can be used to identify the model with best predictive performance.
    The AAPS Journal 08/2014; · 4.39 Impact Factor
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    ABSTRACT: The objective of this analysis was to develop a nonlinear disease progression model, using an expanded set of covariates that captures the longitudinal Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) scores. These were derived from the Alzheimer's Disease Neuroimaging Initiative ADNI-1 study, of 301 Alzheimer's disease and mild cognitive impairment patients who were followed for 2-3 years.
    Neuropsychiatric Disease and Treatment 01/2014; 10:929-52. · 2.00 Impact Factor
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    ABSTRACT: Beta regression models have been recommended for continuous bounded outcome scores that are often collected in clinical studies. Implementing beta regression in NONMEM presents difficulties since it does not provide gamma functions required by the beta distribution density function. The objective of the study was to implement mixed-effects beta regression models in NONMEM using Nemes’ approximation to the gamma function and to evaluate the performance of the NONMEM implementation of mixed-effects beta regression in comparison to the commonly used SAS approach. Monte Carlo simulations were conducted to simulate continuous outcomes within an interval of (0, 70) based on a beta regression model in the context of Alzheimer’s disease. Six samples per subject over a 3 years period were simulated at 0, 0.5, 1, 1.5, 2, and 3 years. One thousand trials were simulated and each trial had 250 subjects. The simulation–reestimation exercise indicated that the NONMEM implementation using Laplace and Nemes’ approximations provided only slightly higher bias and relative RMSE (RRMSE) compared to the commonly used SAS approach with adaptive Gaussian quadrature and built-in gamma functions, i.e., the difference in bias and RRMSE for fixed-effect parameters, random effects on intercept, and the precision parameter were <1–3 %, while the difference in the random effects on the slope was <3–7 % under the studied simulation conditions. The mixed-effect beta regression model described the disease progression for the cognitive component of the Alzheimer’s disease assessment scale from the Alzheimer’s Disease Neuroimaging Initiative study. In conclusion, with Nemes’ approximation of the gamma function, NONMEM provided comparable estimates to those from SAS for both fixed and random-effect parameters. In addition, the NONMEM run time for the mixed beta regression models appeared to be much shorter compared to SAS, i.e., 1–2 versus 20–40 s for the model and data used in the manuscript.
    Journal of Pharmacokinetics and Pharmacodynamics 05/2013; 40(4). · 1.81 Impact Factor
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    ABSTRACT: Shrinkage of empirical Bayes estimates (EBEs) of posterior individual parameters in mixed-effects models has been shown to obscure the apparent correlations among random effects and relationships between random effects and covariates. Empirical quantification equations have been widely used for population pharmacokinetic/pharmacodynamic models. The objectives of this manuscript were (1) to compare the empirical equations with theoretically derived equations, (2) to investigate and confirm the influencing factor on shrinkage, and (3) to evaluate the impact of shrinkage on estimation errors of EBEs using Monte Carlo simulations. A mathematical derivation was first provided for the shrinkage in nonlinear mixed effects model. Using a linear mixed model, the simulation results demonstrated that the shrinkage estimated from the empirical equations matched those based on the theoretically derived equations. Simulations with a two-compartment pharmacokinetic model verified that shrinkage has a reversed relationship with the relative ratio of interindividual variability to residual variability. Fewer numbers of observations per subject were associated with higher amount of shrinkage, consistent with findings from previous research. The influence of sampling times appeared to be larger when fewer PK samples were collected for each individual. As expected, sample size has very limited impact on shrinkage of the PK parameters of the two-compartment model. Assessment of estimation error suggested an average 1:1 relationship between shrinkage and median estimation error of EBEs.
    The AAPS Journal 09/2012; 14(4):927-36. · 4.39 Impact Factor
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    ABSTRACT: To understand the relationship between the risk of opioid-related gastrointestinal adverse effects (AEs) and exposure to tapentadol and oxycodone as well as its active metabolite, oxymorphone, using pharmacokinetic/pharmacodynamic models. The analysis was based on a study in patients with moderate-to-severe pain following bunionectomy. Population PK modeling was conducted to estimate population PK parameters for tapentadol, oxycodone, and oxymorphone. Time to AEs was analyzed using Cox proportional-hazards models. Risk of nausea, vomiting, and constipation significantly increased with exposure to tapentadol or oxycodone/oxymorphone. However, elevated risk per drug exposure of AEs for tapentadol was ~3-4 times lower than that of oxycodone, while elevated AE risk per drug exposure of oxycodone was ~60 times lower than that for oxymorphone, consistent with reported in vitro receptor binding affinities for these compounds. Simulations show that AE incidence following administration of tapentadol IR is lower than that following oxycodone IR intake within the investigated range of analgesic noninferiority dose ratios. This PK/PD analysis supports the clinical findings of reduced nausea, vomiting and constipation reported by patients treated with tapentadol, compared to patients treated with oxycodone.
    Pharmaceutical Research 05/2012; 29(9):2555-64. · 4.74 Impact Factor
  • Xu Steven Xu, Min Yuan, Partha Nandy
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    ABSTRACT: Assessing dose-response from flexible-dose clinical trials (e.g., titration or dose escalation studies) is challenging and often problematic due to the selection bias caused by 'titration-to-response'. We investigate the performance of a dynamic linear mixed-effects (DLME) model and marginal structural model (MSM) in evaluating dose-response from flexible-dose titration clinical trials via simulations. The simulation results demonstrated that DLME models with previous exposure as a time-varying covariate may provide an unbiased and efficient estimator to recover exposure-response relationship from flexible-dose clinical trials. Although the MSM models with independent and exchangeable working correlations appeared to be able to recover the right direction of the dose-response relationship, it tended to over-correct selection bias and overestimated the underlying true dose-response. The MSM estimators were also associated with large variability in the parameter estimates. Therefore, DLME may be an appropriate modeling option in identifying dose-response when data from fixed-dose studies are absent or a fixed-dose design is unethical to be implemented.
    Pharmaceutical Statistics 03/2012; 11(4):280-6. · 0.99 Impact Factor
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    ABSTRACT: Doripenem dosing regimens for patients receiving continuous venovenous hemofiltration (CVVH) and continuous venovenous hemodiafiltration (CVVHDF) were devised based on an established efficacy criterion (free plasma doripenem concentrations above the minimum inhibitory concentration [fT > MIC] of 1 mg/L for ≥35% of the dosing interval) while maintaining exposure below that with the highest studied dose of 1000 mg infused over 1 hour every 8 hours in healthy subjects. Simulations were utilized to assure ≥90% probability of achieving the efficacy criterion with the recommended doripenem regimens. Inflated intersubject variability of 40% (coefficient of variation) was used for pharmacokinetic parameters (representative of clinical variation) and nonrenal clearance was doubled to account for potential changes with acute renal insufficiency. Results indicate that a reduction in doripenem dose will be needed for critically ill patients receiving CVVH or CVVHDF. This work was conducted to fulfill a health authority request and resulted in the addition of dosing recommendations to the Doribax Summary of Product Characteristics.
    ISRN pharmacology. 01/2012; 2012:782656.
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    The AAPS Journal 12/2011; 14(1):60-7. · 4.39 Impact Factor
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    ABSTRACT: The objectives of the simulation study were to evaluate the impact of BQL data on pharmacokinetic (PK) parameter estimates when the incidence of BQL data is low (e.g. ≤10%), and to compare the performance of commonly used modeling methods for handling BQL data such as data exclusion (M1) and likelihood-based method (M3). Simulations were performed by adapting the method of a recent publication by Ahn et al. (J Phamacokinet Pharmacodyn 35(4):401-421, 2008). The BQL data in the terminal elimination phase were created at frequencies of 1, 2.5, 5, 7.5, and 10% based on a one- and a two-compartment model. The impact of BQL data on model parameter estimates was evaluated based on bias and imprecision. The simulations demonstrated that for the one-compartment model, the impact of ignoring the low percentages of BQL data (≤10%) in the elimination phase was minimal. For the two-compartment model, when the BQL incidence was less than 5%, omission of the BQL data generally did not inflate the bias in the fixed-effect parameters, whereas more pronounced bias in the estimates of inter-individual variability (IIV) was observed. The BQL data in the elimination phase had the greatest impact on the volume of distribution estimate of the peripheral compartment of the two-compartment model. The M3 method generally provided better parameter estimates for both PK models than the M1 method. However, the advantages of the M3 over the M1 method varied depending on different BQL censoring levels, PK models and parameters. As the BQL percentages decreased, the relative gain of the M3 method based on more complex likelihood approaches diminished when compared to the M1 method. Therefore, it is important to balance the trade-off between model complexity and relative gain in model improvement when the incidence of BQL data is low. Understanding the model structure and the distribution of BQL data (percentage and location of BQL data) allows selection of an appropriate and effective modeling approach for handling low percentages of BQL data.
    Journal of Pharmacokinetics and Biopharmaceutics 05/2011; 38(4):423-32. · 2.06 Impact Factor
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    ABSTRACT: Tapentadol is a new, centrally active analgesic agent with two modes of action--mu opioid receptor agonism and norepinephrine reuptake inhibition--and the immediate-release (IR) formulation is approved in the US for the relief of moderate to severe acute pain. The aims of this analysis were to develop a population pharmacokinetic model to facilitate the understanding of the pharmacokinetics of tapentadol IR in healthy subjects and patients following single and multiple dosing, and to identify covariates that might explain variability in exposure following oral administration. The analysis included pooled data from 11,385 serum pharmacokinetic samples from 1827 healthy subjects and patients with moderate to severe pain. Population pharmacokinetic modelling was conducted using nonlinear mixed-effects modelling (NONMEM) software to estimate population pharmacokinetic parameters and the influence of the subjects' demographic characteristics, clinical laboratory chemistry values and disease status on these parameters. Simulations were performed to assess the clinical relevance of the covariate effects on tapentadol exposure. A two-compartment model with zero-order release followed by first-order absorption and first-order elimination best described the pharmacokinetics of tapentadol IR following oral administration. The interindividual variability (coefficient of variation) in apparent oral clearance (CL/F) and the apparent central volume of distribution after oral administration were 30% and 29%, respectively. An additive error model was used to describe the residual variability in the log-transformed data, and the standard deviation values were 0.308 and 0.314 for intensively and sparsely sampled data, respectively. Covariate analysis showed that sex, age, bodyweight, race, body fat, hepatic function (using total bilirubin and total protein as surrogate markers), health status and creatinine clearance were statistically significant factors influencing the pharmacokinetics of tapentadol. Total bilirubin was a particularly important factor that influenced CL/F, which decreased by more than 60% in subjects with total bilirubin greater than 50 micromol/L. The population pharmacokinetic model for tapentadol IR identified the relationship between pharmacokinetic parameters and a wide range of covariates. The simulations of tapentadol exposure with identified, statistically significant covariates demonstrated that only hepatic function (as characterized by total bilirubin and total protein) may be considered a clinically relevant factor that warrants dose adjustment. None of the other covariates are of clinical relevance, nor do they necessitate dose adjustment.
    Clinical Pharmacokinetics 10/2010; 49(10):671-82. · 5.49 Impact Factor
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    ABSTRACT: To identify and validate the efficacious monotherapy dosing regimen for topiramate in children aged 2 to <10 years with newly diagnosed epilepsy using pharmacokinetic-pharmacodynamic (PK-PD) modeling and simulation bridging. Several models were developed in pediatric and adult populations to relate steady-state trough plasma concentrations (C(min)) of topiramate to the magnitude of clinical effect in monotherapy and adjunctive settings. These models were integrated to derive and support the monotherapy dosing regimen for pediatric patients. A two-compartmental population PK model with first-order absorption described the time course of topiramate C(min) as a function of dosing regimen. Disposition of topiramate was related to age, body weight, and use of various concomitant antiepileptic drugs. The PK-PD model for monotherapy indicated that the hazard of time to first seizure decreased with increasing C(min) and time since randomization. Higher baseline seizure frequency increased risk for seizures. Age did not significantly influence hazard of time to first seizure after randomization to monotherapy. For adjunctive therapy, the distribution of drug and placebo responses was not significantly different among age groups. Based on the available PK-PD modeling data, the dosing regimen expected to achieve a 65-75% seizure freedom rate after 1 year for pediatric patients age 2-10 years is approximately 6-9 mg/kg per day. This analysis indicated no difference in PK-PD of topiramate between adult and pediatric patients. Effects of indication and body weight on PK were adequately integrated into the model, and monotherapy dosing regimens were identified for children 2-10 years of age.
    Epilepsia 09/2010; 51(10):1954-62. · 3.96 Impact Factor
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    Partha Nandy, Mahesh N Samtani, Rachel Lin
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    ABSTRACT: A population pharmacokinetic model of doripenem was constructed using data pooled from phase 1, 2, and 3 studies utilizing nonlinear mixed effects modeling. A 2-compartment model with zero-order input and first-order elimination best described the log-transformed concentration-versus-time profile of doripenem. The model was parameterized in terms of total clearance (CL), central volume of distribution (V(c)), peripheral volume of distribution (V(p)), and distribution clearance between the central and peripheral compartments (Q). The final model was described by the following equations (for jth subject): CL(j) (liters/h) = 13.6.(CL(CR)(j)/98 ml/min)(0.659).(1 + CL(race)(j) [0 for Caucasian]); V(c)(j) (liters) = 11.6.(weight(j)/73 kg)(0.596); Q(j) (liters/h) = 4.74.(weight(j)/73)(1.06); and V(p)(j) (liters) = 6.04.(CL(CR)(j)/98 ml/min)(0.417).(weight(j)/73 kg)(0.840).(age(j)/40 years)(0.307). According to the final model, population mean parameter estimates and interindividual variability (percent coefficient of variation [% CV]) for CL (liters/h), V(c) (liters), V(p) (liters), and Q (liters/h) were 13.6 (19%), 11.6 (19%), 6.0 (25%), and 4.7 (42%), respectively. Residual variability, estimated using three separate additive residual error models, was 0.17 standard deviation (SD), 0.55 SD, and 0.92 SD for phase 1, 2, and 3 data, respectively. Creatinine clearance was the most significant predictor of doripenem clearance. Mean Bayesian clearance was approximately 33%, 55%, and 76% lower for individuals with mild, moderate, or severe renal impairment, respectively, than for those with normal renal function. The population pharmacokinetic model based on healthy volunteer data and patient data informs us of doripenem disposition in a more general population as well as of the important measurable intrinsic and extrinsic factors that significantly influence interindividual pharmacokinetic differences.
    Antimicrobial Agents and Chemotherapy 04/2010; 54(6):2354-9. · 4.57 Impact Factor
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    ABSTRACT: The growing number of infections caused by multidrug-resistant pathogens has prompted a more rational use of available antibiotics given the paucity of new, effective agents. Monte Carlo simulations were utilized to determine the appropriateness of several doripenem dosing regimens based on the probability of attaining the critical drug exposure metric of time that drug concentrations remain above the drug MIC (T>MIC) for 35% (and lower thresholds) of the dosing interval in >80 to 90% of the population (T>MIC 35% target). This exposure level generally correlates with in vivo efficacy for carbapenems. In patients with creatinine clearance of >50 ml/min, a 500-mg dose of doripenem infused over 1 h every 8 h is expected to be effective against bacilli with doripenem MICs of < or =1 microg/ml based on a T>MIC 35% target and MICs of < or =2 microg/ml based on lower targets. A longer, 4-hour infusion time improved target attainment in most cases, such that the T>MIC was adequate for pathogens with doripenem MICs as high as 4 microg/ml. Efficacy is expected for infections caused by pathogens with doripenem MICs of < or =2 microg/ml in patients with moderate renal impairment (creatinine clearance, 30 to 50 ml/min) who receive doripenem at 250 mg infused over 1 h every 8 h and in patients with severe impairment (creatinine clearance between 10 and 29 ml/min) who receive doripenem at 250 mg, infused over 1 h or 4 h, every 12 h. Results of pharmacokinetics/pharmacodynamics (PK/PD) modeling can guide dose optimization, thereby potentially increasing the clinical efficacy of doripenem against serious Gram-negative bacterial infections.
    Antimicrobial Agents and Chemotherapy 04/2010; 54(6):2360-4. · 4.57 Impact Factor
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    ABSTRACT: Levofloxacin was recently (May 2008) approved by the U.S. Food and Drug Administration as a treatment for children following inhalational exposure to anthrax. Given that no clinical trials to assess the efficacy of a chosen dose was conducted, the basis for the dose recommendation was based upon pharmacometric analyses. The objective of this paper is to describe the basis of the chosen pediatric dose recommended for the label. Pharmacokinetic (PK) data from 90 pediatric patients receiving 7 mg/kg of body weight levofloxacin and two studies of 47 healthy adults receiving 500 and 750 mg/kg levofloxacin were used for the pharmacometric analyses. Body weight was found to be a significant covariate for levofloxacin clearance and the volume of distribution. Consistently with developmental physiology, clearance also was found to be reduced in pediatric patients under 2 years of age due to immature renal function. Different dosing regimens were simulated to match adult exposure (area under the concentration-time curve from 0 to 24 h at steady state, maximum concentration of drug in serum at steady state, and minimum concentration of drug in serum at steady state) following the approved adult dose of 500 mg once a day. The recommended dose of 8 mg/kg twice a day was found to match the exposure of the dose approved for adults in a manner that permitted confidence that this dose in children would achieve efficacy comparable to that of adults.
    Antimicrobial Agents and Chemotherapy 10/2009; 54(1):375-9. · 4.57 Impact Factor
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    ABSTRACT: Ceftobiprole, a broad-spectrum cephalosporin with activity against methicillin (meticillin)-resistant staphylococci, was statistically noninferior to a combination of vancomycin plus ceftazidime in patients with complicated skin and skin structure infections (cSSSI). This analysis used data from this clinical trial to determine the relationship between therapeutic outcome and the percentage of time that the unbound ceftobiprole concentration exceeds the MIC (percent T>MIC). From the trial of ceftobiprole (500 mg every 8 h, 2-h infusion) for cSSSI due to gram-positive and/or gram-negative bacteria, data from 309 patients in the microbiological intent-to-treat analysis set with measured ceftobiprole concentrations and baseline MICs were used to assess the relationship between percent T>MIC and therapeutic outcome. Individual pharmacokinetic (PK) profiles were obtained from a three-compartment population PK model. The relationship between percent T>MIC and a clinical cure was determined. For the clinical trial dosing regimen, individual percent T>MICs were used to calculate fractional target attainment rates (TARs) for >or=30 and >or=50% T>MIC targets at various MICs. There was a statistically significant relationship between achieving a >or=30 or >or=50% T>MIC and a clinical cure (P = 0.003 and P = 0.007, respectively; Pearson's chi(2) test). The fractional TAR was greater than 90% at a MIC of <or=4 mg/liter for patients with normal renal function. A relationship between percent T>MIC and a clinical cure with ceftobiprole was demonstrated. A ceftobiprole regimen of 500 mg every 8 h as a 2-h infusion has a high probability of achieving a target of >or=30 or >or=50% T>MIC for patients with cSSSI due to gram-positive and gram-negative pathogens.
    Antimicrobial Agents and Chemotherapy 07/2009; 53(8):3371-4. · 4.57 Impact Factor
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    ABSTRACT: Characterization of the time course and magnitude of enzyme induction due to multiple inducers is important for interpretation of clinical data from drug-drug interaction studies. A population interaction model was developed to quantify efavirenz autoinduction and further induction with concurrent carbamazepine coadministration. Efavirenz concentration data in the absence and presence of carbamazepine following single- and multiple-dose oral administrations in healthy subjects were used for model development. The proposed model was able to describe the time-dependent efavirenz autoinduction and the further induction with carbamazepine when the agents were combined. The estimated population averages of efavirenz oral clearance were 5.5, 9.4, 14.4, and 16.7 liters/h on days 1, 14, and 35 and at steady state for the interaction, respectively, for efavirenz monotherapy for 2 weeks followed by the coadministration of carbamazepine for 3 weeks. The estimated times to 50% of the steady state for efavirenz autoinduction and for the induction resulting from the concurrent administration of efavirenz and carbamazepine were similar (around 10 to 12 days). With this model-based analysis, efavirenz exposures can be projected prior to and at the steady state of induction, allowing a better understanding of the time course and magnitude of enzyme induction.
    Antimicrobial Agents and Chemotherapy 03/2009; 53(6):2346-53. · 4.57 Impact Factor
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    ABSTRACT: Population pharmacokinetic analysis demonstrated that renal function, as assessed by creatinine clearance (CL(CR)), was the patient characteristic that had a clinically relevant impact on ceftobiprole pharmacodynamics. Dosing adjustments based on CL(CR) for subjects with renal impairment should provide ceftobiprole exposure similar to that in patients with normal renal function.
    Antimicrobial Agents and Chemotherapy 01/2009; 53(3):1228-30. · 4.57 Impact Factor
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    ABSTRACT: Ñ There were no deaths or other serious adverse events (AEs). Ñ AEs occurring in greater than 20% of the subjects in Arm A were: - EFV Alone: Dizziness (33%) - EFV + DTZ: Headache (36%) Ñ AEs occurring in greater than 20% of the subjects in Arm B were: - DTZ Alone: Abnormal dreams (21%) - DTZ + EFV: Euphoric mood (31%) Ñ Most laboratory abnormalities were Grade 1 of which, low calcium (26%), decreased hemoglobin (22%), high potassium (15%), neutropenia (11%), leucopenia (11%), and elevations in ALT (11%) and AST (7%) were most common. Ñ There were two Grade 2 ALT elevations, one Grade 3 high Ñ There were no deaths or other serious AEs. Ñ AEs occurring in greater than 20% of the subjects in Arm A were: - EFV Alone: Feeling drunk (65%) - EFV + ITR: Diarrhea (28%) and nausea (22%) Ñ AEs occurring in greater than 20% of the subjects in Arm B were: - ITR Alone: Diarrhea (55%) and headache (35%) - ITR + EFV: Feeling drunk (55%) and headache (35%) Ñ Most laboratory abnormalities were Grade 1 of which, lymphopenia (24%), neutropenia (5%), leucopenia (5%), and elevations in ALT (10%), Alk. Phos. (8%), and AST (5%) were most common. Ñ There was one Grade 2 ALT elevation and no Grade 3/4
    01/2007;