Abstract. The Global Bioanalysis Consortium (GBC) set up an international team to explore the impact of immunogenicity on pharmacokinetic (PK) assessments. The intent of this paper is to define the field and propose best practices when developing PK assays for biotherapeutics. We focus on the impact of anti-drug antibodies (ADA) on the performance of PK assay leading to the impact on the reported drug concentration and exposure. The manuscript describes strategies to assess whether the observed change in the drug concentration is due to the ADA impact on drug clearance rates or is a consequence of ADA interference in the bioanalytical method applied to measure drug concentration. This paper provides the bioanalytical scientist guidance for developing ADA-tolerant PK methods. It is essential that the data generated in the PK, ADA, pharmacodynamic and efficacy/toxicity evaluations are viewed together. Therefore, the extent for the investigation of the PK sensitivity to the presence of ADA should be driven by the project needs and risk based.
Abstract. Pre-existing antibodies to biotherapeutic drugs have been detected in drug-naïve subjects for a variety of biotherapeutic modalities. Pre-existing antibodies are immunoglobulins that are either specific or cross-reacting with a protein or glycan epitopes on a biotherapeutic compound. Although the exact cause for pre-existing antibodies is often unknown, environmental exposures to non-human proteins, glycans, and structurally similar products are frequently proposed as factors. Clinical consequences of the pre-existing antibodies vary from an adverse effect on patient safety to no impact at all and remain highly dependent on the biotherapeutic drug modality and therapeutic indication. As such, pre-existing antibodies are viewed as an immunogenicity risk factor requiring a careful evaluation. Herein, the relationships between biotherapeutic modalities to the nature, prevalence, and clinical consequences of pre-existing antibodies are reviewed. Initial evidence for pre-existing antibody is often identified during anti-drug antibody (ADA) assay development. Other interfering factors known to cause false ADA positive signal, including circulating multimeric drug target, rheumatoid factors, and heterophilic antibodies, are discussed.
Abstract. Fulranumab, a human IgG2 monoclonal antibody that neutralizes nerve growth factor (NGF), is currently in development for the treatment of pain. Our initial immunogenicity test method was found to be prone to NGF interference, leading to a high apparent incidence of anti-drug antibody (ADA) in phase 1 studies. The ADA immunoassay comprised a homogeneous bridging electrochemiluminescence (ECL) format with biotin and ruthenium-labeled fulranumab bound together ("bridged") by ADA in test samples for detection. In this assay, NGF produced a false-positive signal due to its ability to bridge fulranumab molecules. Thus, we developed a specificity assay to eliminate the NGF false-positive results. We encountered the challenge of eliminating drug interference as well as drug target interference, and discovered that the acid-dissociation-based pretreatment of samples used for mitigating drug interference dramatically increased drug target interference. Several strategies were investigated to eliminate the NGF interference; yet only one strategy specifically removed NGF and produced true fulranumabspecific ADA results by using competitive inhibition with fulranumab and utilizing an alternative NGF binding antibody to eliminate NGF interference. Using this new method, we confirmed that the high apparent anti-fulranumab antibody incidence (>60%) in clinical study samples was in fact due to fulranumab-bound NGF released during the acid-dissociation step of the ADA testing method. We conclude that our revised method accurately identifies anti-fulranumab antibodies by incorporating steps to eliminate fulranumab and NGF interference. We advise that acid-dissociation pretreatment must not be universally applied to improve ADA assays without investigating its bioanalytical risks versus benefits.
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