title: Mitigation of Pre-existing Antibodies to a Biotherapeutic in Non-clinical Species When Establishing Anti-drug Antibody Assay Cutpoint.
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.
authors.affiliation: BioMedicine Design, Pfizer Inc, One Burtt Road, G-2002D, Andover, Massachusetts, 01810, USA.
authors.forename: Seema C
authors.initials: SC
authors.lastname: Kumar
authors.affiliation: Celldex Therapeutics Inc., Needham, Massachusetts, 02494, USA.
authors.forename: Jason A
authors.initials: JA
authors.lastname: DelCarpini
authors.affiliation: EMD Serono, Billerica, Massachusetts, 01821, USA.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Qu
authors.affiliation: Exponent, 149 Commonwealth Drive, Menlo Park, California, 94025, USA.
authors.forename: Martin
authors.initials: M
authors.lastname: Kane
authors.affiliation: BioMedicine Design, Pfizer Inc, One Burtt Road, G-2002D, Andover, Massachusetts, 01810, USA. Boris.gorovits@pfizer.com.
authors.forename: Boris
authors.initials: B
authors.lastname: Gorovits
mesh_terms: D000818:Animals; D000911:Antibodies, Monoclonal / Q000097:blood* / Q000276:immunology / Q000627:therapeutic use; D001688:Biological Products / Q000097:blood* / Q000276:immunology; D001691:Biological Therapy / Q000379:methods; D005189:False Positive Reactions; D066298:In Vitro Techniques; D008163:Luminescent Measurements / Q000379:methods* / Q000706:statistics & numerical data; D008252:Macaca fascicularis; D008954:Models, Biological; D015233:Models, Statistical; D011919:Rats, Inbred Strains
chemical_list: D000911:Antibodies, Monoclonal; D001688:Biological Products
keywords: Gaussian mixture model; anti-drug antibody (ADA); assay cutpoint; floating cutpoint factor (CPF); negative control (NC); positive control (PC); pre-existing antibodies