Literature DB >> 27873117

Mitigation of Pre-existing Antibodies to a Biotherapeutic in Non-clinical Species When Establishing Anti-drug Antibody Assay Cutpoint.

Seema C Kumar1, Jason A DelCarpini2, Qiang Qu3, Martin Kane4, Boris Gorovits5.   

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.

Entities:  

Keywords:  Gaussian mixture model; anti-drug antibody (ADA); assay cutpoint; floating cutpoint factor (CPF); negative control (NC); positive control (PC); pre-existing antibodies

Mesh:

Substances:

Year:  2016        PMID: 27873117     DOI: 10.1208/s12248-016-0011-2

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  12 in total

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Review 9.  Pre-existing Antibody: Biotherapeutic Modality-Based Review.

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Journal:  AAPS J       Date:  2016-01-28       Impact factor: 4.009

10.  Statistical approaches for the determination of cut points in anti-drug antibody bioassays.

Authors:  Frank Schaarschmidt; Matthias Hofmann; Thomas Jaki; Bettina Grün; Ludwig A Hothorn
Journal:  J Immunol Methods       Date:  2015-02-27       Impact factor: 2.303

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Journal:  AAPS J       Date:  2020-01-06       Impact factor: 4.009

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