Guohui Liu
Takeda Pharmaceutical Company
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Featured researches published by Guohui Liu.
Blood | 2014
Paul G. Richardson; Rachid Baz; Michael Wang; Andrzej J. Jakubowiak; Jacob P. Laubach; R. Donald Harvey; Moshe Talpaz; Deborah Berg; Guohui Liu; Jiang Yu; Neeraj Gupta; Alessandra Di Bacco; Ai Min Hui; Sagar Lonial
Ixazomib is the first investigational oral proteasome inhibitor to be studied clinically. In this phase 1 trial, 60 patients with relapsed/refractory multiple myeloma (median of 4 prior lines of therapy; bortezomib, lenalidomide, thalidomide, and carfilzomib/marizomib in 88%, 88%, 62%, and 5%, respectively) received single-agent ixazomib 0.24 to 2.23 mg/m(2) (days 1, 4, 8, 11; 21-day cycles). Two dose-limiting toxicities (grade 3 rash; grade 4 thrombocytopenia) occurred at 2.23 mg/m(2). The maximum tolerated dose was 2.0 mg/m(2), which 40 patients received in 4 expansion cohorts. Patients received a median of 4 cycles (range, 1-39); 18% received ≥12 cycles. Eighty-eight percent had drug-related adverse events, including nausea (42%), thrombocytopenia (42%), fatigue (40%), and rash (40%); drug-related grade ≥3 events included thrombocytopenia (37%) and neutropenia (17%). Grade 1/2 drug-related peripheral neuropathy occurred in 12% (no grade ≥3). Two patients died on the study (both considered unrelated to treatment). The terminal half-life of ixazomib was 3.3 to 7.4 days; plasma exposure increased proportionally with dose (0.48-2.23 mg/m(2)). Among 55 response-evaluable patients, 15% achieved partial response or better (76% stable disease or better). These findings have informed the subsequent clinical development of ixazomib in multiple myeloma. This trial was registered at www.clinicaltrials.gov as #NCT00932698.
The Journal of Clinical Pharmacology | 2018
Neeraj Gupta; Michael J. Hanley; Karthik Venkatakrishnan; Alberto Bessudo; Drew W. Rasco; Sunil Sharma; Bert H. O'Neil; Bingxia Wang; Guohui Liu; Alice Ke; Chirag Patel; Karen Rowland Yeo; Cindy Xia; Dixie Lee Esseltine; John Nemunaitis
At clinically relevant ixazomib concentrations, in vitro studies demonstrated that no specific cytochrome P450 (CYP) enzyme predominantly contributes to ixazomib metabolism. However, at higher than clinical concentrations, ixazomib was metabolized by multiple CYP isoforms, with the estimated relative contribution being highest for CYP3A at 42%. This multiarm phase 1 study (Clinicaltrials.gov identifier: NCT01454076) investigated the effect of the strong CYP3A inhibitors ketoconazole and clarithromycin and the strong CYP3A inducer rifampin on the pharmacokinetics of ixazomib. Eighty‐eight patients were enrolled across the 3 drug‐drug interaction studies; the ixazomib toxicity profile was consistent with previous studies. Ketoconazole and clarithromycin had no clinically meaningful effects on the pharmacokinetics of ixazomib. The geometric least‐squares mean area under the plasma concentration‐time curve from 0 to 264 hours postdose ratio (90%CI) with vs without ketoconazole coadministration was 1.09 (0.91‐1.31) and was 1.11 (0.86‐1.43) with vs without clarithromycin coadministration. Reduced plasma exposures of ixazomib were observed following coadministration with rifampin. Ixazomib area under the plasma concentration‐time curve from time 0 to the time of the last quantifiable concentration was reduced by 74% (geometric least‐squares mean ratio of 0.26 [90%CI 0.18‐0.37]), and maximum observed plasma concentration was reduced by 54% (geometric least‐squares mean ratio of 0.46 [90%CI 0.29‐0.73]) in the presence of rifampin. The clinical drug‐drug interaction study results were reconciled well by a physiologically based pharmacokinetic model that incorporated a minor contribution of CYP3A to overall ixazomib clearance and quantitatively considered the strength of induction of CYP3A and intestinal P‐glycoprotein by rifampin. On the basis of these study results, the ixazomib prescribing information recommends that patients should avoid concomitant administration of strong CYP3A inducers with ixazomib.
Clinical Pharmacology & Therapeutics | 2018
Neeraj Gupta; Michael J. Hanley; Paul Matthias Diderichsen; Huyuan Yang; Alice Ke; Zhaoyang Teng; Richard Labotka; Deborah Berg; Chirag Patel; Guohui Liu; Helgi van de Velde; Karthik Venkatakrishnan
Model‐informed drug development (MIDD) was central to the development of the oral proteasome inhibitor ixazomib, facilitating internal decisions (switch from body surface area (BSA)‐based to fixed dosing, inclusive phase III trials, portfolio prioritization of ixazomib‐based combinations, phase III dose for maintenance treatment), regulatory review (model‐informed QT analysis, benefit–risk of 4 mg dose), and product labeling (absolute bioavailability and intrinsic/extrinsic factors). This review discusses the impact of MIDD in enabling patient‐centric therapeutic optimization during the development of ixazomib.
Clinical and Translational Science | 2018
Zhaoyang Teng; Neeraj Gupta; Zhaowei Hua; Guohui Liu; Vivek Samnotra; Karthik Venkatakrishnan; Richard Labotka
The failure rate for phase III trials in oncology is high; quantitative predictive approaches are needed. We developed a model‐based meta‐analysis (MBMA) framework to predict progression‐free survival (PFS) from overall response rates (ORR) in relapsed/refractory multiple myeloma (RRMM), using data from seven phase III trials. A Bayesian analysis was used to predict the probability of technical success (PTS) for achieving desired phase III PFS targets based on phase II ORR data. The model demonstrated a strongly correlated (R2 = 0.84) linear relationship between ORR and median PFS. As a representative application of the framework, MBMA predicted that an ORR of ∼66% would be needed in a phase II study of 50 patients to achieve a target median PFS of 13.5 months in a phase III study. This model can be used to help estimate PTS to achieve gold‐standard targets in a target product profile, thereby enabling objectively informed decision‐making.
Investigational New Drugs | 2015
David C. Smith; Thea Kalebic; Jeffrey R. Infante; Lillian L. Siu; Daniel M. Sullivan; Gordana Vlahovic; John Kauh; Feng Gao; Allison Berger; Stephen Tirrell; Neeraj Gupta; Alessandra Di Bacco; Deborah Berg; Guohui Liu; Jianchang Lin; Ai Min Hui; John A. Thompson
Investigational New Drugs | 2016
Neeraj Gupta; Richard Labotka; Guohui Liu; Ai-Min Hui; Karthik Venkatakrishnan
Journal of Clinical Oncology | 2010
E. T. Rodler; Jeffrey R. Infante; Lillian L. Siu; David C. Smith; Daniel C. Sullivan; Gordana Vlahovic; J. Gomez-Navarro; Guohui Liu; S. Blakemore; John A. Thompson
Clinical Lymphoma, Myeloma & Leukemia | 2015
Sagar Lonial; Kathleen Colson; R.D. Harvey; Shaji Kumar; Ai-Min Hui; Guohui Liu; Deborah Berg; Paul G. Richardson
Blood | 2017
Meletios A. Dimopoulos; Jacob P. Laubach; Maria Asunción Echeveste Gutierrez; Norbert Grząśko; Craig C. Hofmeister; Jesús F. San Miguel; Shaji Kumar; Vickie Lu; Zhaoyang Teng; Guohui Liu; Catriona Byrne; Deborah Berg; Richard Labotka; Helgi van de Velde; Paul G. Richardson
Journal of Clinical Oncology | 2017
Peter R. Martin; Julie E. Chang; Robert M. Rifkin; Ai-Min Hui; Deborah T. Berg; Neeraj Gupta; Guohui Liu; Alessandra Di Bacco; Sarit Assouline