title: Use of quantitative pharmacology in the development of HAE1, a high-affinity anti-IgE monoclonal antibody.
abstract: 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.
authors.affiliation: Development Sciences, Genentech Inc., 1 DNA Way, South San Francisco, California, 94080-4990, USA. wputnam@gene.com
authors.forename: Wendy S
authors.initials: WS
authors.lastname: Putnam
authors.forename: Jing
authors.initials: J
authors.lastname: Li
authors.forename: Jonas
authors.initials: J
authors.lastname: Haggstrom
authors.forename: Chee
authors.initials: C
authors.lastname: Ng
authors.forename: Saloumeh
authors.initials: S
authors.lastname: Kadkhodayan-Fischer
authors.forename: Melissa
authors.initials: M
authors.lastname: Cheu
authors.forename: Yamo
authors.initials: Y
authors.lastname: Deniz
authors.forename: Henry
authors.initials: H
authors.lastname: Lowman
authors.forename: Paul
authors.initials: P
authors.lastname: Fielder
authors.forename: Jennifer
authors.initials: J
authors.lastname: Visich
authors.forename: Amita
authors.initials: A
authors.lastname: Joshi
authors.forename: Nelson Shasha
authors.initials: NS
authors.lastname: Jumbe
mesh_terms: D000888:Antibodies, Anti-Idiotypic; D000911:Antibodies, Monoclonal / Q000276:immunology / Q000494:pharmacology / Q000627:therapeutic use; D061067:Antibodies, Monoclonal, Humanized; D000915:Antibody Affinity / Q000276:immunology*; D001249:Asthma / Q000188:drug therapy; D002460:Cell Line; D015195:Drug Design; D006801:Humans; D007073:Immunoglobulin E / Q000276:immunology*; D000069444:Omalizumab; D017455:Receptors, IgE / Q000276:immunology
chemical_list: D000888:Antibodies, Anti-Idiotypic; D000911:Antibodies, Monoclonal; D061067:Antibodies, Monoclonal, Humanized; D017455:Receptors, IgE; D000069444:Omalizumab; D007073:Immunoglobulin E