A passive cutaneous anaphylaxis (PCA) mouse model was utilized to select allergen-specific monoclonal antibody (mAb) cocktails that bind to allergen and prevent binding to specific IgE. These antibodies provided symptomatic relief in individuals with cat or birch allergy as measured by significant reductions in total nasal symptom score (TNSS) following nasal allergen challenge (NAC) and robust suppression of allergen-specific skin prick tests (SPT) relative to baseline in Phase 1 studies. 

Mice, humanized for FceR1a, were administered anti-allergen single mAbs, combinations, or an isotype control mAb and then sensitized intradermally with IgE containing baseline plasma from patients in clinical studies evaluating either a single subcutaneous dose of a Fel d 1 mAb cocktail (REGN1908-1909) for cat allergy or a Bet v 1 mAb cocktail (REGN5713-5714-5715) for birch allergy. Mice were subsequently administered cat or birch allergen, respectively, with Evans blue dye. Spectrophotometric dye leakage into tissue was quantified as a measure of mast cell degranulation. 

Blockade of mast cell degranulation in the PCA mouse model correlates with the corresponding percent reduction in TNSS after NAC and allergen specific SPT relative to baseline (modest, non-significant correlation for Bet v 1; strong correlation for Fel d 1: r = 0.7, 0.8 for TNSS and r = 0.9 for SPT, all p ≤ 0.1). Additionally, utilizing logistic regression classification methods, there is modest to good accuracy in predicting TNSS and SPT responses across different thresholds based on the blockade of mast cell degranulation (Bet v 1 and Fel d 1: AUC of ROC curves of 0.67 to 0.94 for TNSS and 0.8 to 0.84 for SPT). Blockade of individual mAbs versus mAb cocktails confirms optimal blocking efficacy of Fel d 1 mAb cocktail (REGN1908-1909) compared with either single mAb; Bet v 1 triple mAb cocktail (REGN5713-5714-5715) compared with single mAb (REGN5715) or dual mAb cocktail (REGN5713-5715). 

Blockade of mast cell degranulation in the PCA mouse model correlates to efficacy in clinical settings, validating the model as a useful tool for selection of efficacious anti-allergen therapeutics.