Mechanistic Models to Simulate Dose Response of IgE Suppression Following Dosing of Anti-IgE Monoclonal Antibodies
Pascal Chanu (1), Balaji Agoram (2), Rene Bruno (1)
(1) Pharsight, a CertaraTM company, St. Louis, MO, USA; (2) Pfizer, Clinical Pharmacology, Sandwich, UK
Objectives: The aim of this study was to use mechanistic models to simulate dose response of IgE suppression for anti-IgE monoclonal antibodies such as omalizumab vs. higher affinity antibodies.
Methods: A previously published instantaneous equilibrium (IE) drug-IgE binding model for omalizumab [1,2] was used to perform simulations of expected IgE suppression for anti-IgE monoclonal antibodies. The equilibrium assumption being only valid for limited ranges of drug affinity and dose, the IE model was extended to a full target-mediated disposition (TMD) model [3]. The models were implemented in Pharsight® Trial SimulatorTM to perform simulations. Model implementation was evaluated by simulating multiple replicates of the data in the original papers and comparing with published plots and results. The TMD model was then used to simulate dose response (proportion of patients with IgE suppression below threshold levels, e.g. 50 ng/mL) in specific regions of the omalizumab dosing table including patients non-treatable by omalizumab (Xolair package insert) for omalizumab, and other more potent anti-IgE antibodies (10-to 30-fold increase in affinity) to characterize the affinity-potency relationship of such antibodies.
Results: Both the IE and TMD models reproduced well the data in the original papers. The IE model however, predicted continuous increase in in-vivo potency with increasing IgE affinity whereas the TMD model predicted a maximum 2.4 to 3-fold increase in potency with a 10-fold increased affinity and no difference between 10-fold and 30-fold increase in affinity. The latter is consistent with clinical data [4]. Simulations demonstrated that a 10-fold more potent drug would suppress free IgE below 50 ng/mL in 95% of the patients (a suppression associated with clinical efficacy in asthma) at 350 mg every 4 weeks in the most challenging patient subgroup (i.e. patients with high IgE and large body weight).
Conclusions: A fully mechanistic TMD model is required for PKPD translation across anti-IgE antibodies and should be pursued in the clinical setting wherever possible. There is potential to treat a larger patient population with a more convenient dosing paradigm and a higher potency anti-IgE antibody.
References:
[1] Hayashi N, Tsukamoto Y, Sallas WM, Lowe PJ. A mechanism-based binding model for the population pharmacokinetics and pharmacodynamics of omalizumab. Br. J. Clin. Pharmacol. 63, 548-561, 2007.
[2] Lowe PJ, Tannenbaum S, Gautier A, Jimenez P. Relationship between omalizumabpharmacokinetics, IgE pharmacodynamics and symptoms in patients with severe persistent allergic (IgE-mediated) asthma. Br. J. Clin. Pharmacol. 68, 61-76, 2009.
[3] Agoram BM. Use of pharmacokinetic/pharmacodynamic modelling for starting dose selection in first-in-human trials of high-risk biologics. Br. J. Clin. Pharmacol. 67, 153-160, 2009.
[4] Putman WS, Li J, Haggstrom J, Ng C, Kadkhodayan-Fischer S, Cheu M, DenizY, Lowman H, Fielder P, Visich J, Joshi A, "Shasha" Jumbe N. Use of quantitative pharmacology in the development of HAE1, a high-affinity anti-IgE monoclonal antibody. AAPS J. 10, 425-430, 2008.
