Statistical and bioanalytical considerations for establishing a depletion criterion for specificity testing during immunogenicity assessment of a biotherapeutic.

Immunogenicity assessment of fully human monoclonal antibody-based biotherapeutics requires sensitive and specific ligand binding assays. One of the components of specificity is the depletion of signal by a relevant biotherapeutic that is commonly based on an arbitrary depletion criterion of inhibition of the original response or reduction of the signal below the screening assay cut point (ACP). Hence, there is a need to develop a statistically derived physiologically relevant specificity criterion. We illustrate an optimization approach to determine the concentration of biotherapeutic required for the specificity evaluation. Naïve donor sample sets with and without circulating drug and antitherapeutic/drug antibody (ADA) were prepared. Next, a depletion cut point (DCP) using naïve and ADA-containing donor sets with the optimized biotherapeutic concentration was evaluated. A statistically derived design of experiment was used to establish a validated DCP. A reliable DCP requires naïve (no ADA) donors treated only with an optimized concentration of biotherapeutic. The additional DCPs generated using two distinct concentrations of ADA-spiked sample sets led to a physiologically irrelevant criterion that was not necessarily representative of real-time samples. This increased the risk of false positives or negatives. In this study, well-defined bioanalytical and statistical methods were employed to validate a DCP to confirm the presence of biotherapeutic specific ADA in human serum samples. A physiologically relevant and effective strategy to confirm specificity in immune reactive samples, especially those that are close to the ACP, is proposed through this study.

Clinical validation of the "in silico" prediction of immunogenicity of a human recombinant therapeutic protein.

Antibodies elicited by protein therapeutics can cause serious side effects in humans. We studied immunogenicity of a recombinant fusion protein (FPX) consisting of two identical, biologically active, peptides attached to human Fc fragment. EpiMatrix, an in silico epitope-mapping tool, predicted promiscuous T-cell epitope(s) within the 14-amino-acid carboxy-terminal region of the peptide portion of FPX. On administration of FPX in 76 healthy human subjects, 37% developed antibodies after a single injection. A memory T-cell response against the above carboxy-terminus of the peptide was observed in antibody-positive but not in antibody-negative subjects. Promiscuity of the predicted T-cell epitope(s) was confirmed by representation of all common HLA alleles in antibody-positive subjects. As predicted by EpiMatrix, HLA haplotype DRB1*0701/1501 was associated with the highest T-cell and antibody response. In conclusion, in silico prediction can be successfully used to identify Class II restricted T-cell epitopes within therapeutic proteins and predict immunogenicity thereof in humans.