Over 19 years ago, I began my career in regulated bioanalysis. Like many scientists of my generation, I started in small molecule quantitation before moving into immunoassay technologies as biologics continued their rapid expansion. For the last 15 years, immunogenicity testing has been a major focus of my work, and during that time I've had the opportunity to observe several significant shifts in how our industry evaluates anti-drug antibodies (ADA) and neutralizing antibodies (NAb).
When I first entered the field, ADA methods often looked surprisingly similar to pharmacokinetic assays. Results were reported in semi-quantitative units, and the objective was relatively simple: determine whether antibodies were present and estimate response magnitude.
As biologics became more complex and regulatory expectations matured, the industry rapidly transitioned toward the now-familiar three-tier testing paradigm consisting of screening, confirmatory, and titer assessment, often followed by NAb characterization. The focus was on standardization, sensitivity, drug tolerance, and ensuring clinically meaningful immune responses were not overlooked.
For many years, that paradigm served the industry remarkably well and that success is now contributing to its own evolution. Over the last two decades, we've generated an enormous volume of ADA and NAb data across virtually every therapeutic modality imaginable. Monoclonal antibodies, fusion proteins, enzyme replacement therapies, cell therapies, gene therapies, and countless other biologics have collectively provided a growing body of evidence linking immunogenicity findings to real-world clinical outcomes.
As our experience has expanded, so has an important realization, not every detectable immune response is clinically meaningful.
Shifting the Question
Early in my career, immunogenicity discussions often focused on analytical capability. The line of questioning typically focused on items such as: How sensitive is the assay? How much drug tolerance can be achieved? Can we detect lower concentrations of ADA?
Today, the conversation increasingly focuses on interpretation. Does the detected ADA impact pharmacokinetics? Does it influence pharmacodynamic activity? Does it affect efficacy or safety? Does the result change clinical decision-making?
These questions represent a subtle but significant shift in mindset. Rather than focusing exclusively on whether an immune response can be detected, the industry is increasingly evaluating whether the data generated meaningfully improves scientific understanding.
What Decades of Experience Are Teaching Us
Recent scientific discussions, consortium publications, and conference presentations have consistently challenged several long-standing assumptions surrounding ADA and NAb testing. Topics receiving increasing attention include, the relationship between screening-tier signal magnitude and traditional titer measurements, the practical value of confirmatory testing in well-characterized assay systems, the role of dedicated NAb assays when PK, PD, efficacy, or biomarker data may already provide functional insight, if and when maximizing assay sensitivity always improves clinical interpretation, in addition to how modality-specific risk should influence testing strategy.
None of these questions suggest that ADA or NAb testing is becoming less important. Instead, they highlight a growing recognition that immunogenicity risk is not uniformly distributed across drug classes, mechanisms of action, or patient populations. A fully human monoclonal antibody may require a very different testing strategy than an enzyme replacement therapy or gene therapy product.
The challenge is no longer developing a method capable of generating data. The challenge is generating the right data for the scientific question being asked.
The Influence of 3Rs and New Approach Methodologies
This discussion currently extends well beyond immunogenicity, across drug development, the principles of the 3Rs (Replacement, Reduction, and Refinement) and the adoption of New Approach Methodologies (NAMs) are driving scientists to critically examine how data are generated and, more importantly, how those data are used. The broader goal is not to collect less information; it is to generate information that meaningfully influences decisions.
This philosophical approach is increasingly applicable to ADA and NAb assessment. Particularly relevant to nonclinical development, there is growing recognition that extensive immunogenicity characterization may not always improve interpretation of toxicology, pharmacology, or exposure-response relationships. Increasingly sensitive and drug tolerant testing strategies may generate additional data without proportionally improving scientific understanding or development decisions. In many cases, the scientific value lies not in generating additional testing tiers or detecting 10 ng/mL of ADA in the presence of 1 mg/mL of drug/antigen, but in understanding how immune responses influence study outcomes. Viewed through this lens, fit-for-purpose immunogenicity strategies are not about reducing rigor, they are about aligning analytical effort with clinical and scientific relevance
Why This Matters Now
I don't believe the industry is abandoning the traditional three-tier paradigm, rather, I believe we're entering the next stage of its evolution. The original framework was developed when clinical experience with biologics was limited, and the consequences of undetected immunogenicity were less predictable. Today's environment is different, we have decades of accumulated evidence, thousands of clinical studies, and a far better understanding of how ADA and NAb responses relate to patient outcomes.
That evidence is encouraging us to move beyond a one-size-fits-all approach and toward testing strategies informed by risk, mechanism of action, modality, patient biology, and intended data use. After years spent optimizing detection, the field has become increasingly focused on optimizing interpretation.
Continuing the Conversation
The future of immunogenicity assessment will not be defined by how well we detect antibodies, but by how well we understand their relevance and allow this to shape testing strategy. Decades of clinical experience have demonstrated that not all immune responses carry the same consequence, and testing paradigms should reflect that reality. As biologics continue to diversify, the most effective immunogenicity programs will be those that balance analytical rigor with scientific context, focusing on generating data that meaningfully informs patient safety, efficacy, and development decisions.
These themes became the foundation for a much larger discussion than I originally intended. What began as observations from nearly two decades in bioanalysis ultimately grew into a comprehensive white paper exploring the evolution of ADA and NAb assessment and the growing movement toward fit-for-purpose immunogenicity strategies.
Take a deeper dive and read the full white paper.
Mike Mulvana has over 19 years of CRO experience in regulated bioanalysis. Mike started his bioanalytical career in 2007 performing regulated sample analysis, development, and validation of LC-MS based methods until 2009 when he shifted to supporting large molecule biologics by Immunoassay. In 2011, Mike moved into a leadership role providing oversight of immunogenicity activities, and between 2012-2022 he continued to support a major immunogenicity lab as laboratory manager and scientific lead. Since October 2022, Mike has continued to leverage his experience with IQVIA Laboratories and provide bioanalytical scientific support towards a broadening range of therapeutics ranging from antibodies, antibody drug conjugates, pegylated proteins, fusion proteins, biosimilars, peptides, gene therapy, CAR-T, and oligonucleotides.