Brian Hee
Pfizer
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Publication
Featured researches published by Brian Hee.
Clinical Pharmacology & Therapeutics | 2002
Jonathan Q. Tran; Carolyn Petersen; May Garrett; Brian Hee; Bradley M. Kerr
Our objective was to determine the pharmacokinetic interaction between amprenavir and delavirdine.
Drug Metabolism and Disposition | 2014
Bill J. Smith; Yazdi K. Pithavala; Hai-Zhi Bu; Ping Kang; Brian Hee; Alan J. Deese; William F. Pool; Karen J. Klamerus; Ellen Y. Wu; Deepak Dalvie
The disposition of a single oral dose of 5 mg (100 μCi) of [14C]axitinib was investigated in fasted healthy human subjects (N = 8). Axitinib was rapidly absorbed, with a median plasma Tmax of 2.2 hours and a geometric mean Cmax and half-life of 29.2 ng/ml and 10.6 hours, respectively. The plasma total radioactivity-time profile was similar to that of axitinib but the AUC was greater, suggesting the presence of metabolites. The major metabolites in human plasma (0–12 hours), identified as axitinib N-glucuronide (M7) and axitinib sulfoxide (M12), were pharmacologically inactive, and with axitinib comprised 50.4%, 16.2%, and 22.5% of the radioactivity, respectively. In excreta, the majority of radioactivity was recovered in most subjects by 48 hours postdose. The median radioactivity excreted in urine, feces, and total recovery was 22.7%, 37.0%, and 59.7%, respectively. The recovery from feces was variable across subjects (range, 2.5%–60.2%). The metabolites identified in urine were M5 (carboxylic acid), M12 (sulfoxide), M7 (N-glucuronide), M9 (sulfoxide/N-oxide), and M8a (methylhydroxy glucuronide), accounting for 5.7%, 3.5%, 2.6%, 1.7%, and 1.3% of the dose, respectively. The drug-related products identified in feces were unchanged axitinib, M14/15 (mono-oxidation/sulfone), M12a (epoxide), and an unidentified metabolite, comprising 12%, 5.7%, 5.1%, and 5.0% of the dose, respectively. The proposed mechanism to form M5 involved a carbon-carbon bond cleavage via M12a, followed by rearrangement to a ketone intermediate and subsequent Baeyer-Villiger rearrangement, possibly through a peroxide intermediate. In summary, the study characterized axitinib metabolites in circulation and primary elimination pathways of the drug, which were mainly oxidative in nature.
British Journal of Clinical Pharmacology | 2014
May Garrett; Bill Poland; Meghan Brennan; Brian Hee; Yazdi K. Pithavala; Michael Amantea
AIMS Axitinib is a potent and selective second generation inhibitor of vascular endothelial growth factor receptors 1, 2 and 3 approved for second line treatment of advanced renal cell carcinoma. The objectives of this analysis were to assess plasma pharmacokinetics and identify covariates that may explain variability in axitinib disposition following single dose administration in healthy volunteers. METHODS Plasma concentration-time data from 337 healthy volunteers in 10 phase I studies were analyzed, using non-linear mixed effects modelling (nonmem) to estimate population pharmacokinetic parameters and evaluate relationships between parameters and food, formulation, demographic factors, measures of renal and hepatic function and metabolic genotypes (UGT1A1*28 and CYP2C19). RESULTS A two compartment structural model with first order absorption and lag time best described axitinib pharmacokinetics. Population estimates for systemic clearance (CL), central volume of distribution (Vc ), absorption rate constant (ka ) and absolute bioavailability (F) were 17.0 l h(-1) , 45.3 l, 0.523 h(-1) and 46.5%, respectively. With axitinib Form IV, ka and F increased in the fasted state by 207% and 33.8%, respectively. For Form XLI (marketed formulation), F was 15% lower compared with Form IV. CL was not significantly influenced by any of the covariates studied. Body weight significantly affected Vc , but the effect was within the estimated interindividual variability for Vc . CONCLUSIONS The analysis established a model that adequately characterizes axitinib pharmacokinetics in healthy volunteers. Vc was found to increase with body weight. However, no change in plasma exposures is expected with change in body weight; hence no dose adjustment is warranted.
Xenobiotica | 2017
Justine L. Lam; Alfin D. N. Vaz; Brian Hee; Yali Liang; Xin Yang; M. Naveed Shaik
Abstract 1. The metabolism, excretion and pharmacokinetics of glasdegib (PF-04449913) were investigated following administration of a single oral dose of 100 mg/100 μCi [14C]glasdegib to six healthy male volunteers (NCT02110342). 2. The peak concentrations of glasdegib (890.3 ng/mL) and total radioactivity (1043 ngEq/mL) occurred in plasma at 0.75 hours post-dose. The AUCinf were 8469 ng.h/mL and 12,230 ngEq.h/mL respectively, for glasdegib and total radioactivity. 3. Mean recovery of [14C]glasdegib-related radioactivity in excreta was 91% of the administered dose (49% in urine and 42% in feces). Glasdegib was the major circulating component accounting for 69% of the total radioactivity in plasma. An N-desmethyl metabolite and an N-glucuronide metabolite of glasdegib represented 8% and 7% of the circulating radioactivity, respectively. Glasdegib was the major excreted component in urine and feces, accounting for 17% and 20% of administered dose in the 0–120 hour pooled samples, respectively. Other metabolites with abundance <3% of the total circulating radioactivity or dose in plasma or excreta were hydroxyl metabolites, a desaturation metabolite, N-oxidation and O-glucuronide metabolites. 4. Elimination of [14C]glasdegib-derived radioactivity was essentially complete, with similar contribution from urinary and fecal routes. Oxidative metabolism appears to play a significant role in the biotransformation of glasdegib.
Clinical Pharmacology & Therapeutics | 2003
J. Q. Tran; X. Lin; May Garrett; Brian Hee; Keith D. Wilner
Clinical Pharmacology & Therapeutics (2003) 73, P80–P80; doi:
British Journal of Clinical Pharmacology | 2018
M. Naveed Shaik; Brian Hee; Hua Wei; Robert R. LaBadie
This study aimed to evaluate the effect of a strong CYP3A inducer, rifampin, on glasdegib pharmacokinetics in healthy volunteers.
Cancer Chemotherapy and Pharmacology | 2010
Yazdi K. Pithavala; Michael A. Tortorici; Melvin Toh; May Garrett; Brian Hee; Uma Kuruganti; Grace Ni; Karen J. Klamerus
Investigational New Drugs | 2012
Yazdi K. Pithavala; Warren Tong; Janessa Mount; Sadayappan V. Rahavendran; May Garrett; Brian Hee; Paulina Selaru; Nenad Sarapa; Karen J. Klamerus
Investigational New Drugs | 2011
Michael A. Tortorici; Melvin Toh; Sadayappan V. Rahavendran; Robert R. LaBadie; Christine Alvey; Thomas Marbury; Ernesto Fuentes; Matthew Green; Grace Ni; Brian Hee; Yazdi K. Pithavala
Clinical Pharmacokinectics | 2013
Ying Chen; Michael A. Tortorici; May Garrett; Brian Hee; Karen J. Klamerus; Yazdi K. Pithavala