Use of quantitative pharmacology in the development of HAE1, a high-affinity anti-IgE monoclonal antibody

被引:32
|
作者
Putnam, Wendy S. [1 ]
Li, Jing [1 ]
Haggstrom, Jonas [2 ]
Ng, Chee [1 ]
Kadkhodayan-Fischer, Saloumeh [1 ]
Cheu, Melissa [1 ]
Deniz, Yamo [3 ]
Lowman, Henry [4 ]
Fielder, Paul [1 ]
Visich, Jennifer [1 ]
Joshi, Amita [1 ]
Jumbe, Nelson Shasha [1 ]
机构
[1] Genentech Inc, Dev Sci, San Francisco, CA 94080 USA
[2] Genentech Inc, Design Anal & Technol Adm, San Francisco, CA 94080 USA
[3] Genentech Inc, Immunol Tissue Growth & Repair Clin Sci, San Francisco, CA 94080 USA
[4] Genentech Inc, Antibody Engn, San Francisco, CA 94080 USA
来源
AAPS JOURNAL | 2008年 / 10卷 / 02期
关键词
anti-IgE; monoclonal antibody; quantitative pharmacology;
D O I
10.1208/s12248-008-9045-4
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
HAE1, a high-affinity anti-IgE monoclonal antibody, is discussed here as a case study in the use of quantitative pharmacology in the development of a second-generation molecule. In vitro, preclinical, and clinical data from the first-generation molecule, omalizumab, were heavily leveraged in the HAE1 program. A preliminary mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model for HAE1 was developed using an existing model for omalizumab, together with in vitro binding data for HAE1 and omalizumab. When phase I data were available, the model was refined by simultaneously modeling PK/PD data from omalizumab studies with the available HAE1 phase I data. The HAE1 clinical program was based on knowledge of the quantitative relationship between a pharmacodynamic biomarker, suppression of free IgE, and clinical response (e.g., lower exacerbation rates) obtained in pivotal studies with omalizumab. A clinical trial simulation platform was developed to predict free IgE levels and clinical responses following attainment of a target free IgE level (<= 10 IU/ml). The simulation platform enabled selection of four doses for the phase II dose-ranging trial by two independent methods: dose-response non-linear fitting and linear mixed modeling. Agreement between the two methods provided confidence in the doses selected. Modeling and simulation played a large role in supporting acceleration of the HAE1 program by enabling data-driven decision-making, often based on confirmation of projections and/or learning from incoming new data.
引用
收藏
页码:425 / 430
页数:6
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