ABSTRACT
Biotherapeutics are known for their potential to induce drug specific immune responses, which are commonly evaluated by the detection of anti-drug antibodies (ADAs). For some biotherapeutics, pre-existing ADAs against drug have been observed in drug-naïve matrix. The presence of pre-existing drug specific antibodies may significantly complicate assessment of the screening ADA assay cutpoint value, which is usually established based on the statistical analysis of signal distribution from the drug-naïve individuals. A Gaussian mixture model-based approach is presented herein to address high prevalence of pre-existing ADAs to a modified monoclonal antibody-based biotherapeutic (m-mAb). A high prevalence of pre-existing anti-m-mAb antibodies was observed in drug-naïve individual cynomolgus monkey serum samples with signal ranging from 100 to 7000 relative light units (RLU, as determined in an electrochemiluminescence readout-based assay). Application of the industry standard statistical algorithm resulted in a relatively high floating screening assay cutpoint factor (CPF) of 9.80, which potentially would have reported a high percent of false negative samples. An alternative, Gaussian mixture model-based approach was applied to identify the least reactive individual samples in the tested population, which resulted in a floating screening assay CPF of 2.35. The low CPF value significantly reduced the risk of reporting false negative results. The proposed Gaussian mixture model-based approach described herein provides an alternate method for the calculation of biologically relevant screening assay CPF when high prevalence of pre-existing drug specific antibodies is observed.
