Max Tsai
Takeda Pharmaceutical Company
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Featured researches published by Max Tsai.
principles and practice of constraint programming | 2012
Max Tsai; Jingtao Wu; Lhanoo Gunawardhana; Himanshu Naik
OBJECTIVE Febuxostat, a non-purine selective xanthine oxidase (XO) inhibitor, may affect the metabolism of theophylline as XO hydroxylates 1-methylxanthine to 1-methyluric acid. The objective of this study was to examine the effects of febuxostat on the pharmacokinetics of theophylline and its metabolites. METHODS 24 healthy subjects received febuxostat 80 mg (Regimen A) or matching placebo (Regimen B) daily for 7 days along with a single oral dose of theophylline 400 mg on Day 5 in a double-blind, randomized, cross-over fashion (≥ 7 day washout between periods) followed by collection of plasma and urine samples for 72 h. RESULTS For Regimens A and B, mean theophylline Cmax values were 4.4 and 4.1 μg/ml, respectively, and mean theophylline AUC0-tlqc was 122.3 and 115.2 μg x h/ml, respectively. The ratios of theophylline Cmax and AUC0-tlqc central values following coadministration with febuxostat or placebo were 1.03 (90% confidence intervals (CIs), 0.917 - 1.149) and 1.04 (90% CI, 0.927 - 1.156). Both 90% CIs fell within the no-effect range of 0.8 and 1.25. Mean excreted amounts in urine for 1-methylxanthine levels were higher in Regimen A vs. B (40.1 vs. 0.1 mg), while 1-methyluric acid levels were lower (3.1 vs. 56.2 mg). Mean excreted amounts of theophylline and other metabolites were comparable between Regimen A and B. CONCLUSIONS No dose adjustment for theophylline is necessary when coadministered with febuxostat 80 mg, as coadministration does not affect the plasma pharmacokinetics of theophylline and neither 1-methylxanthine nor 1-methyluric have any pharmacological effect.
The Journal of Clinical Pharmacology | 2016
Max Tsai; Jingtao Wu; Stuart Kupfer; Majid Vakilynejad
Population pharmacokinetic and exposure‐response models for azilsartan medoxomil (AZL‐M) and chlorthalidone (CLD) were developed using data from an 8‐week placebo‐controlled phase 3, factorial study of 20, 40, and 80 mg AZL‐M every day (QD) and 12.5 and 25 mg CLD QD in fixed‐dose combination (FDC) in subjects with moderate to severe essential hypertension. A 2‐compartment model with first‐order absorption and elimination was developed to describe pharmacokinetics. An Emax model for exposure‐response analysis evaluated AZL‐M/CLD effects on ambulatory systolic blood pressure (SBP). Estimated oral clearance and apparent volume of distribution (central compartment) were 1.47 L/h and 3.98 L for AZL, and 4.13 L/h and 62.1 L for CLD. Age as a covariate had the largest effect on AZL and CLD exposure (±20% change). Predicted maximal SBP responses (Emax) were –15.6 and –23.9 mm Hg for AZL and CLD. Subgroup analysis identified statistically significant Emax differences for black vs nonblack subjects, whereby the reduced AZL response in black subjects was offset by greater response to CLD. The estimated Emax for AZL and CLD was generally greater in subjects with higher baseline BP. In conclusion, no dose adjustments to AZL‐M or CLD are warranted based on identified covariates, and antihypertensive efficacy of AZL‐M/CLD combination therapy is comparable in black and nonblack subjects.
PLOS ONE | 2013
Himanshu Naik; Max Tsai; Jill Fiedler-Kelly; Ping Qiu; Majid Vakilynejad
Peginesatide (OMONTYS®) is an erythropoiesis-stimulating agent that was indicated in the United States for the treatment of anemia due to chronic kidney disease in adult patients on dialysis prior to its recent marketing withdrawal by the manufacturer. The objective of this analysis was to develop a population pharmacokinetic and pharmacodynamic model to characterize the time-course of peginesatide plasma and hemoglobin concentrations following intravenous and subcutaneous administration. Plasma samples (n = 2,665) from 672 patients with chronic kidney disease (on or not on dialysis) and hemoglobin samples (n = 18,857) from 517 hemodialysis patients (subset of the 672 patients), were used for pharmacokinetic-pharmacodynamic model development in NONMEM VI. The pharmacokinetic profile of peginesatide was best described by a two-compartment model with first-order absorption and saturable elimination. The relationship between peginesatide and hemoglobin plasma concentrations was best characterized by a modified precursor-dependent lifespan indirect response model. The estimate of maximal stimulatory effect of peginesatide on the endogenous production rate of progenitor cells (Emax) was 0.54. The estimate of peginesatide drug concentration required for 50% of maximal response (EC50) estimates was 0.4 µg/mL. Several significant (P<0.005) covariates affected simulated peginesatide exposure by ≤36%. Based upon ≤0.2 g/dL effects on simulated hemoglobin levels, none were considered clinically relevant.
Cancer Research | 2011
Yue Gao; Peng Guo; Ze Lu; Max Tsai; M. Guillaume Wientjes; Jessie L.-S. Au
Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL Clinical studies have established that the efficacy of intraperitoneal paclitaxel therapy is dependent on the tumor size, producing survival advantage in patients with small tumors (<1 cm diameter) but not in patients with larger tumors. This study was to investigate the mechanisms of this observation. We developed computational models to examine the effects of tumor size, drug binding (to extracellular proteins), tumor heterogeneity, and drug absorption on drug interstitial transport. The required model parameters were obtained from the literature. The models were used to simulate the drug penetration in small (0.3 cm) and larger (1 cm) tumors. Model performance was evaluated by comparing the simulated results to lab-generated experimental data using paclitaxel in mice bearing peritoneal metastases of ovarian tumors. The experiments measured drug concentration vs tumor penetration depth using autoradiography. The validated models were then used to generate penetration kinetic data for tumors of different sizes. The simulated penetration kinetics was subsequently compared to the pharmacodynamic data obtained from the literature (i.e., the C×T50 that produced 50% inhibition of tumor growth). The penetration kinetic models described the interstitial paclitaxel transport by both diffusion and convection, and the drug absorption into tumor vasculature by diffusion. The model-predicted concentration-penetration depth profiles were in general agreement with the experimental profiles (average deviation of 13.7%), indicating good model performance. The simulated drug C×T exceeded the C×T50 value at depth of up to 3 mm (from all sides of the outer tumor perimeter), indicating that for a spherical tumor of 1 cm diameter, 6.4% of the tumor (volume) would receive less than the therapeutic exposure, C×T50. Additionally, doubling the tumor diameter to 2 cm increased the subtherapeutic tumor volume fraction by nearly 5-times (34.3%). We have developed computational models to depict interstitial drug transport in peritoneal tumors during intraperitoneal therapy. These models provide quantitative measures of the effect of tumor size on local drug exposure for the tumor, and have the potential of predicting the tumor pharmacokinetics-pharmacodynamics for a given treatment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5453. doi:10.1158/1538-7445.AM2011-5453
Psychopharmacology | 2016
Max Tsai; Lambros Chrones; Jinhui Xie; Hakop Gevorkyan; Thomas A. Macek
European Journal of Clinical Pharmacology | 2016
Nicholas J. A. Webb; Thomas G. Wells; Max Tsai; Zhen Zhao; Attila Juhasz; Caroline Dudkowski
Archive | 2011
Lhanoo Gunawardhana; Max Tsai; Himanshu Naik
European Journal of Clinical Pharmacology | 2017
Caroline Dudkowski; Max Tsai; Jie Liu; Zhen Zhao; Eric Schmidt; Jeannie Xie
Drugs in R & D | 2017
Paul Goldsmith; John Affinito; Maggie McCue; Max Tsai; Stefan Roepcke; Jinhui Xie; Lev Gertsik; Thomas A. Macek
Kidney research and clinical practice | 2012
Himanshu Naik; Max Tsai; Ping Qiu; Majid Vakilynejad