Use of Quantitative Pharmacology in the Development of HAE1, a High-Affinity Anti-IgE Monoclonal Antibody

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 HA...

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Veröffentlicht in:The AAPS journal 2008-06, Vol.10 (2), p.425-430, Article 425
Hauptverfasser: Putnam, Wendy S., Li, Jing, Haggstrom, Jonas, Ng, Chee, Kadkhodayan-Fischer, Saloumeh, Cheu, Melissa, Deniz, Yamo, Lowman, Henry, Fielder, Paul, Visich, Jennifer, Joshi, Amita, Jumbe, Nelson “Shasha”
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Sprache:eng
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Zusammenfassung: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.
ISSN:1550-7416
1550-7416
DOI:10.1208/s12248-008-9045-4