▉ Introduction

Protein drugs have the potential to induce immunogenicity, which can affect efficacy and even endanger life. New paradigms in biotherapy, such as antibody-drug conjugates (ADC), fusion proteins, and pegylation carry non-native human protein sequences and/or structural motifs, which may increase their immunogenicity risk. Therefore, comprehensive risk assessment, strategies, and analysis are needed to monitor and characterize the immunogenicity of ADCs and other biotherapies to predict and understand potential clinical effects.

Immunogenicity in Clinical Practice and Drug Development: When is it Significant?

ADCs are covalently linked to cytotoxic agents via stable linkers to monoclonal antibodies (mAb), combining the specificity of monoclonal antibodies for tumor cell surface target antigens with the efficacy of cytotoxic drugs. Although current ADCs use human or humanized monoclonal antibodies and small molecule payloads, their hapten-like structures may increase their immunogenic potential compared to therapeutic monoclonal antibodies. Antidrug antibodies (ADAs) can target different domains in ADCs, such as mAb epitopes, novel mAb epitopes, linkers, and cytotoxic agents. If large ADC-ADA immune complexes are taken up by non-target immune cells leading to cell death, the presence of ADAs against cytotoxic agents poses potential safety risks.

Elimination of drug through accelerated clearance.

ADAs indicates antidrug antibodies; TNF, tumor necrosis factor. Image source:《Immunogenicity in biologic therapy: implications for dermatology.》

It is generally believed that the industry practices and regulatory guidelines followed for assessing the immunogenicity of biotherapeutics apply to ADCs. The key to ADC immunogenicity assessment is risk assessment, appropriate testing and additional characteristics specific to ADA domains. Immunogenicity risk assessment includes various known factors related to patients and products that may influence the immunogenicity of the drug and the potential consequences of the immune response. For ADCs, this risk is typically considered higher than that of therapeutic monoclonal antibodies.

Immunogenicity Experimental Process

Based on risk assessment, an immunogenicity data analysis was conducted on 8 ADC drugs across 11 clinical trials involving a range of solid tumors and hematological malignancies. For each ADC, the incidence of ADAs at baseline, the incidence after treatment, and other characteristics of immune responses were assessed.

▉ Baseline Incidence of ADAs

From the baseline incidence of ADAs data obtained from all ADC studies, the baseline incidence of ADAs ranges from 1.4% to 8.1%, which is within the range reported for other monoclonal antibody-derived biotherapies, including the ADC drug Kadcyla.

In these clinical studies of 8 ADC antibodies, these antibodies are unlikely to be related to other components of the ADC. Moreover, in the assessed 8 ADCs, the background signal in untreated patient population samples was similar to the mixed serum control signal from healthy volunteers.

▉ Incidence of ADAs After ADC Treatment

The incidence of post-baseline ADAs ranged from 0% to 35.8%, with ADC patients targeting hematological malignancies having fewer ADAs than solid tumor patients, with 8 cases out of 169 in hematological malignancies and 83 cases out of 459 in solid tumors, which can be attributed to immune killing in hematological malignancy patients.

However, there were some exceptions in ADA incidence, such as the ADA incidence for ADC C targeting plasma cells being 25.9%, while the incidence for melanoma ADC G was 0%, but patients received glucocorticoids as part of their treatment, which has known immunosuppressive effects.

Studies were also conducted on ADC A and I, where ADC A had only one patient with treatment-induced ADA in one study. For ADC I, the number of ADA-positive patients in the study ranged from 5 to 18, with corresponding ADA incidence between 20.8% to 32.0%. Additionally, it is noteworthy that in Phase I studies, ovarian cancer patients had a higher ADA incidence than lung cancer patients, with rates of 31.0% (9/29) and 16.4% (9/55), respectively. Similar ADA incidence was also observed in Phase II studies for ovarian cancer patients.

▉ Characteristics of ADA Immune Responses

For the eight ADCs evaluated here, most ADAs are targeting the mAb domains of the ADCs, ranging from 86% to 100%. These results are similar to those of Adcetris (brentuximab-vedotin), which has the same linker and toxic drug as the eight ADCs described in this article.

Overall, these data suggest that compared to traditional therapeutic monoclonal antibodies, the hapten-like structures of these ADCs do not seem to increase their immunogenicity risk.

Regarding ADA levels, the total titer range for these ADCs is broad, from less than 1.30 to 4.92 titer units, with an average titer exceeding 2.50 titer units for all ADCs.

As for the timing of treatment-induced ADA occurrence, it shows that the occurrence of ADAs is variable across all ADCs, with ADA occurrence timing ranging from 3 to 42 weeks. Furthermore, 6 out of the 8 ADCs had more than 60% of patients developing ADAs within 3 to 6 weeks after starting treatment.

The majority of responses for all ADCs are durable, with ADC H and I exhibiting the highest transient responses (43.8% and 34.1%, respectively). However, dividing ADA responses into durable or transient in oncology studies may be misleading, as treatment durations are often short. In fact, a more detailed data assessment of ADA-positive responses indicates that three ADCs (ADC F, H, and I) have a higher ADA positive rate.

Among 652 patients, 33 had antibodies present at baseline, of which 3 showed enhanced ADA responses. The ADA titers for these three patients varied over time, with baseline titers ranging from 1.89 to 2.71, while post-baseline titers ranged from 2.50 to 4.10. Two of the three patients reached peak ADA levels at the first post-treatment baseline time point, with the timing of enhanced responses ranging from 3 to 9 weeks. ADA levels for all patients at the last time point were below peak levels. ADA domain specificity remained unchanged at baseline and post-baseline time points.

▉ Impact of ADAs on Other Clinical Data

Immunogenicity is an important component of the clinical characteristics of protein drugs, and its data should be evaluated in the context of other factors (such as efficacy, PK, and safety). Here we focus on the three ADCs with a higher number of patients generating ADAs, namely ADC F, H, and I, with 19, 16, and 43 patients respectively showing post-baseline ADA-positive responses.

ADC F had an ADA incidence of 35.8% (19/53), with 18 patients having treatment-induced ADAs and 1 patient having treatment-enhanced ADAs. Overall, no differences were observed in PK, safety, or efficacy outcomes compared to patients who did not generate antibodies to ADC F.

As for ADC-H, the ADA incidence was 25% (16/64), with all 16 patients having treatment-induced ADAs. Similar to ADC F, some patients with higher ADA titers had lower total antibody trough levels than those with lower ADA titers, but overall, higher total ADA titers did not correspond with lower total antibody levels.

ADC I had a total of 43 patients with ADAs, with 41 patients induced and 2 patients enhanced. Notably, 7 patients (including 2 enhanced ADA patients) had total antibody levels below detection levels at one or more trough time points. However, comprehensive analysis is still needed to draw conclusions: ADA titers may impact PK in these patients. However, it is noteworthy that high ADA titer values (∼4.00) had significant impacts on the PK curves of trastuzumab ADCs in cynomolgus monkeys.

Limited data from marketed ADCs suggest that ADAs have minimal impact on clinical outcomes. Adcetris has a 37% incidence of ADAs, with a higher infusion reaction rate in patients with persistent positive ADAs, leading to treatment discontinuation in two patients. The incidence of ADAs with Kadcyla is 5.3%, and the development of ADAs does not seem to affect safety, PK, or efficacy. In Phase I studies, Mylotarg had some ADA-positive patients, one of whom experienced transient dyspnea related to ADAs. No additional immunogenicity data for Mylotarg has been generated under the currently recommended dosing regimen. In the clinical trials of Besponsa, the incidence of ADAs was 3%, with no impact on the clearance rate of the ADC.

▉ Conclusion

Chemical structure of MMAE-ADCs with MC-VC-PABC linker

Image source:《Semi-mechanistic Multiple-Analyte Pharmacokinetic Model for an Antibody-Drug-Conjugate in Cynomolgus Monkeys》

In the extensive range of tumor indications across 11 clinical trials, the incidence of ADAs for 8 vc-MMAE-ADCs ranges from 0% to 35.8%. Most ADA responses are directed against the mAb domains in the ADCs, indicating that hapten-like structures play a very minor role in generating immune responses against these ADCs. These results reinforce the fact that molecular structure is an important factor in the immunogenic response of biotherapies, but not the only factor.

Although the data for these 8 vc-MMAE-ADCs suggest that the risk may decrease as projects enter later stages of clinical development, it is still recommended to take a conservative approach for novel ADCs that may use different linkers and more potent cytotoxic drugs. Furthermore, as the use of predictive immunogenicity tools becomes more widespread, they will provide additional information to incorporate into the risk assessment and immunogenicity strategies for ADCs and novel therapies.

Classic Antibody Drug ADA Incidence and Detection Methods

Data source:《Pros and cons of the immunogenicity of monoclonal antibodies in cancer treatment: a lesson from autoimmune diseases》

References:

1. Immunogenicity of antibody-drug conjugates: observations across 8 molecules in 11 clinical trials. Bioanalysis. 2019 Sep;11(17):1555-1568.

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