Practical implications of recent FDA guidance on immunogenicity risk assessments on your IND submissions
Comprehensive bioanalytical strategy has become an important part of safety assessment of biologic therapies, and unless sponsors execute adequate testing to ascertain immunogenicity of candidate biologic drugs, regulatory agencies may place a clinical hold on a program, costing a company valuable time.
In January 2019, the FDA updated its guidance for the development and validation of immunogenicity testing assays, recommending a risk-based approach to evaluating and managing immune responses elicited by therapeutic proteins. There are many updates in the 2019 guidance compared to the earlier guidance, but updates in three areas – determination of the cut point, development of assays for neutralizing antibodies (NAbs) and changes in documentation – carry significant consequences for building the IND package.
During the course of immunogenicity testing, if antidrug antibodies are identified, it’s very important to assess if any of these antidrug antibodies are NAbs that would cause adverse effects on the therapeutic protein. NAbs have the potential to dramatically interfere with clinical activity of a therapeutic protein including, changing PK, PD, safety and efficacy.
The FDA recommends that companies carry out assays to determine whether NAbs are present if early immunogenicity testing results in statistically significant (above cut point) ADA responses. As with all immunogenicity testing, inadequate testing ahead of first in-human trials risks clinical hold, which can affect program budgets and timelines.
Developing reliable neutralization assays can be challenging especially when it’s critical that any NAb assay has the capability to reliably detect NAbs with adequate sensitivity, specificity, selectivity and precision(2). The differing assay formats – whether cell-based or non-cell-based – can carry distinct challenges. For example, previous guidance recommended using cell-based assays as much as possible for NAb detection, yet certain mechanisms of action – enzymatic replacement that doesn’t require cellular update, for example – are not amenable to cell-based assays. Given this, the FDA’s updates allow greater flexibility for designing the most appropriate assay to detect NAbs.
Statistical Approach to Determining Cut Point
The cut-point of the assay determines whether the sample response is positive or negative, and establishing the appropriate cut-point is critical to reducing false-negative results, and assays should be designed such that they generate a 5% false positive rate, which is important for ensuring the assay identifies all subjects who may develop antibodies to a therapeutic protein.
The importance of the cut point is further emphasized by updates in the guidance that require sponsors to develop a statistically-sound method to determine the cut point, whereas older guidance recommended estimating the cut point using a small number of samples.
In developing the cut point for a screening assay, the guidance suggests a statistical approach that applies a 90% one-sided lower confidence interval for the 95th percentile of the negative control population. This assures at least a 5% false-positive rate with a 90% confidence level.
For estimating the cut point for confirmatory assays, FDA advises the use of an 80 to 90% one-sided lower confidence interval for the 99th percentile. The goal of the confirmatory assay is to eliminate false-positive samples arising as a result of non-specific binding. Therefore, FDA recommends designing the cut point to a more stringent 1% false positive rate.
These new statistical calculations recommended by the FDA offer more clarity than the 2016 guidance. To date, there is no generally-accepted standard method for these determinations, which can be challenging for complex therapeutic programs.
One method developed by WuXi AppTec and its partner Integrated Medical Development CRO, is a statistically-sound estimation package including outlier exclusion and cut-point estimation, satisfying the new FDA requirements. The statistical methodology is based on order statistics – Bayesian and Monte Carlo methods – and can be applied to any assay data with at least 50 samples. These are implemented using standard statistical programming languages SAS and R, is designed to satisfy or exceed the FDA confidence requirements without being too conservative.
A major update in the 2019 guidance for development of immunogenicity assays concerns how immunogenicity data is presented in documentation to the FDA. Previously, immunogenicity data was dispersed throughout the electronic common technical document (eCTD), the standard format sponsors use for submitting data to the FDA. This presented challenges for reviewers trying to understand a therapeutic drug candidate’s immunogenicity profile.
New guidance directs sponsors to add an integrated immunogenicity summary report that clearly summarizes the data generated in support of a potential therapeutic protein’s regulatory filings, allowing FDA reviewers to understand immunogenicity data up front.
The summary report should be divided into distinct sections:
- Immunogenicity Risk Assessment
- Tiered Bioanalytical Strategy and Assay Validation Summaries
- Clinical Study Design and Detailed Immunogenicity Sampling Plans
- Clinical Immunogenicity Data Analysis
- Conclusions and Risk Evaluation and Mitigation Strategies (REMS)
The Right Outsourcing Partner Can Help Avoid Pitfalls with the FDA
A multidisciplinary outsourcing partner familiar with the latest regulatory changes and updates can help navigate pitfalls that can stymie a therapy’s first in-human trials. WuXi AppTec has the knowledge and experience to develop, execute and analyze the immunogenicity assays that are essential to maximize submission success of your development programs.
- FDA, Guidance for Industry: Immunogenicity Testing of Therapeutic Protein Products – Developing and Validating Assays for Anti-Drug Antibody Detection (Silver Spring, MD, January 2019).
- Wu, B, et. al., “Strategies to Determine Assay Format for the Assessment of Neutralizing Antibody Responses to Biotherapeutics,” AAPS J, 18(6): 1335-1350, 2016.