Challenges in ADC Neutralizing Anti-Drug Antibody (NAb) Detection

Challenges in ADC Neutralizing Anti-Drug Antibody (NAb) Detection

Antibody-drug conjugates (ADCs) are an emerging class of anti-cancer therapeutic drugs. This type of drug relies on the specificity of monoclonal antibodies to deliver cytotoxins to tumor sites, which can not only improve the efficacy of chemotherapy, but also reduce or eliminate the toxicity of cytotoxic molecules to non-target tissues and non-target cells. ADCs drugs are multi-domain molecules composed of monoclonal antibodies (mAbs), linkers and small molecule cytotoxins. mAbs can specifically bind to target antigens on the surface of tumor cells, while ADCs drugs enter tumor cells through internalization mediated by mAb recognition receptors, and subsequently release cytotoxins to exert cell killing effects.

Antibody-drug conjugate (ADC) characterizationFig. 1. Antibody-drug conjugate (ADC) characterization (Journal of pharmaceutical and biomedical analysis. 2021, 201: 114094).

What is Anti-drug Antibody (ADA)?

Immunogenicity is the property of therapeutic protein products to induce an immune response in the body (against the therapeutic protein itself or its related proteins) or to induce clinically relevant adverse immune reactions. The immune response induced by therapeutic protein drugs may affect pharmacokinetics, pharmacodynamics, drug safety and effectiveness. The immunogenicity of macromolecule drugs is generally evaluated by detecting anti-drug antibodies (ADA) produced by humoral immunity. For different products, the production of ADA may not cause obvious clinical consequences, but may also lead to serious adverse events, such as allergic reactions, cross-reactivity with endogenous proteins, neutralization of endogenous proteins leading to loss of their functions, etc. Neutralizing antibody (NAb) is a special kind of ADA. NAbs interfere with the in vivo activity of drugs by blocking the product from reaching its target or interfering with receptor/ligand binding. Therefore, NAbs, as a subset of antidrug antibodies, form an important part of immunogenicity research and evaluation.

The monoclonal antibodies, linkers, linker-cytotoxic molecules, and new epitopes introduced by conjugation of ADCs drugs may all be immunogenic, which makes the immune response induced by ADCs drugs in the body more complicated. The particularity of the drug structure and mechanism of action of ADCs determines that the detection and evaluation of NAbs are also different from antibody drugs and face greater difficulties and challenges.

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ADC Neutralizing Anti-Drug Antibody (NAb) Analysis

Challenges in the development of drug-neutralizing antibody test methods for ADCs include: difficulty in distinguishing antibody epitopes with cell-based antibodies, difficulty in selecting appropriate positive control antibodies, large variation in cell lines, large drug interference in the matrix, etc.

Cell-based Neutralizing Activity Assay

For cell-based neutralizing antibody analysis tests, cell lines that are more sensitive to drugs and can tolerate higher matrix interference are generally selected. However, after cells have been passaged many times, genes may be lost or genotypes may change. Researchers should examine the number of passages at which cell lines are stable to reduce test variability. For matrix interference, the minimum dilution factor can be determined during method development, and the matrix interference can be eliminated or reduced by diluting the sample. The minimum dilution factor recommended by the FDA is 5 to 100 times. Excessive dilution factors may lead to false negative results.

ADA may contain neutralizing antibodies targeting monoclonal antibodies, linkers, linker-drugs, and neoepitopes, and neutralizing antibodies targeting different epitopes can elicit different cellular responses. NAbs directed against monoclonal antibodies can block the binding of ADCs drugs to target antigens, leading to failure of receptor-mediated internalization, manifested by increased cell activity compared to drug controls. After NAbs targeting cytotoxins or linker-cytotoxins are internalized into target cells, they may be acidified and enzymatically catalyzed in the special environment of lysosomes to release cytotoxins. This does not affect the function of the cytotoxins, and is worse than that of drugs. There was no change in drug activity in the control group. There is an opposite situation, that is, neutralizing antibodies against cytotoxins or linker-cytotoxins are internalized in the form of immune complexes and can still bind to cytotoxin molecules after entering lysosomes, thereby inhibiting the killing effect of cytotoxins, which is manifested as increased cell activity compared with the drug control group. NAb has the ability to combine free cytotoxins and the functional domains of ADCs drugs, causing poisoning of non-target tissues due to immune complex scavenging function and ingestion of immune complexes. Therefore, cell-based assays for drug neutralizing activity against ADCs cannot detect all types of neutralizing antibodies and may underestimate the presence of neutralizing antibodies.

Selection of Positive Control Antibodies

Neutralizing antibody detection results are highly dependent on the sensitivity and specificity of the assay. Test methods with high sensitivity, specificity, and selectivity are highly dependent on the selection of positive control antibodies. Antibodies derived from subjects positive for anti-drug neutralizing antibodies are the best choice for positive control antibodies. But obtaining enough of these positive control antibodies is very difficult. Therefore, most of the positive control antibodies used in the development and validation of analytical methods are derived from experimental animals, such as rabbits and mice. Currently, experimental animals are mostly immunized with drugs to obtain anti-idiotypic polyclonal antibodies or monoclonal antibodies as positive control antibodies. For the same test method, higher sensitivity, relatively good selectivity and specificity can be obtained by using a higher affinity positive control antibody. ADCs drugs are multi-domain drugs, and each domain may cause an immune response in the body. It is easier to prepare positive control antibodies against the entire drug or monoclonal antibodies of ADCs, but it is more challenging to prepare positive control antibodies with neutralizing activity and high affinity against haptens such as small cytotoxic molecules and linker-cytotoxic molecules. In addition, ADCs drugs may form new immunogenic epitopes after being connected. Due to the lack of understanding of such epitopes, it is very difficult to prepare antibodies against such antigens. For this reason, it is almost impossible to achieve epitope-specific analysis of the neutralizing activity of antidrug antibodies.

Since the positive control antibody is derived from animals, the neutralizing antibody profile of the real sample is different from the positive control antibody, and the neutralizing activity of the positive control antibody does not represent the true NAb neutralizing activity. Therefore, the sensitivity, drug resistance and other parameters of the test method established using positive control antibodies can only be used as a reference.

Drug or Target Interference

The body's circulation system often contains both free drugs, free ADA, and drug-ADA immune complexes. Free drugs in the matrix often interfere with immunogenicity detection, while the presence of ADA-drug immune complexes leads to increased missed detection rates of NAbs. After long-term and multiple administrations, high concentrations of free drugs or drug-ADA immune complexes are often present in samples, resulting in a significant increase in false negative rates. Since the nature of the positive control antibody, experimental design, drug concentration and other factors all have a certain impact on the resistance of the experimental method, it is impossible to determine the drug tolerance level under multiple factors.

Free targets that may be present in the matrix can compete with NAbs for drug binding, exerting the same effect of reducing drug activity as neutralizing antibodies. The free targets in individual matrices may fluctuate to a large extent due to factors such as different seasons, subject or patient disease status, age, gender, etc. Therefore, the interference of free targets in determining the critical value should be considered during method validation. In the same way, different concentrations of free targets in the sample should also be considered during sample detection, which may lead to an increase in the false positive rate. At this time, it can be considered to increase the sample processing steps, remove the free target in the matrix, and reduce or eliminate the target interference.

Key Reagents

The cytotoxic molecules of ADCs drugs may be derived from naturally occurring substances or have structures similar to natural products. Therefore, there may be natural neutralizing antibodies targeting such molecules in the stroma of individuals who have not been treated with ADCs drugs. Naturally occurring anti-drug neutralizing antibodies shift the critical value and subsequently adversely affect the test results of the sample. The selection of blank individuals in the process of critical value verification needs to be carefully considered, which can be comprehensively considered according to the characteristics of the drug, the mechanism of action, the disease status of the selected blank individuals and other factors.

Competitive ligand binding assay (CLBA) uses the principle of competitive binding of target proteins and NAb drugs to analyze and evaluate neutralizing antibodies. The purity of the target protein and its similarity to endogenous protein properties are important factors affecting experimental parameters. Based on the detection principle and sample processing needs, when labeling ADCs drugs with biotin, Sulfo-tag, etc., it is necessary to consider that the labeling site is occupied by the linker, resulting in low labeling efficiency or labeling failure. Labeling leads to an increase in the aggregation tendency of ADCs and reduces the stability and immunological activity of ADCs. A high ratio of tags may mask the recognition epitopes of ADA and NAbs.

ADCs drugs have received increasing attention due to their highly specific targeted therapy. With the increase in the number of ADCs drugs, the accumulated experience in immunogenicity evaluation of ADCs drugs can be used to evaluate the clinical immunogenicity risk of ADCs drugs connected using the same linker, cytotoxic molecule and the same drug-antibody ratio, and determine the production of ADA and Nab, thereby judging the trend of ADA and NAb production and predict the epitopes recognized by ADA and NAb. At the same time, it should also be recognized that the immunogenicity risk of each ADCs drug is closely related to the monoclonal antibodies, linkers, cytotoxins and their cleavage methods, the subject's immune status and other factors. The immunogenicity evaluation methods and results of individual ADCs drugs are only used as a reference for the design and development of immunogenicity detection methods for this type of drugs, and cannot yet provide direct reference for the formulation of immunogenicity risk assessment strategies for other ADCs drugs. Therefore, it is necessary to evaluate the immunogenicity risk of each ADCs drug, strengthen the development and optimization of detection methods, guide drug development, and increase drug safety. In addition, the ability of ADCs to deliver cytotoxic drugs has inspired the generation of new conjugated targeted therapeutic macromolecules, such as antibody-antibiotic conjugates targeting infectious pathogens, antibody-glucocorticoid conjugates targeting inflammation, etc. , which will also bring new challenges to the immunogenicity evaluation of ADCs drugs.


  1. Martelet, A. et al. Multi-attribute method based characterization of antibody drug conjugates (ADC) at the intact and subunit levels. Journal of pharmaceutical and biomedical analysis. 2021, 201: 114094.
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