Every year, WRIB manages to capture where bioanalysis actually is, not just where we say it is in guidance documents or individual perspectives. This year’s combined WRIB and Global Bioanalytical CRO Council (GCC) meeting felt particularly honest and grounded, with discussions squarely focused on aligning analytical rigor with biological and clinical meaning. I came away with a renewed appreciation that progress in bioanalysis is being driven less by any single technology and more by how thoughtfully we integrate data, platforms, and scientific judgment.
As someone whose background is chromatographic bioanalysis rather than deep specialization in ligand binding assays (LBA) and immunogenicity, I found myself listening closely to areas both familiar and adjacent to my own expertise. What follows are reflections that personally resonated with me, where the science challenged my assumptions, clarified my thinking, or reinforced directions I already see emerging across the field.
Immunogenicity: Listening, Learning, and Context Matters
Immunogenicity (IG) and ADA assay strategy were heavily discussed topics at WRIB. I found the discussions particularly useful precisely because they highlighted how much the field is evolving and how careful one must be not to treat legacy frameworks as immutable truths.
Moving Beyond Purely Binary Thinking
A recurring theme was the growing discomfort with forcing continuous biological immune responses into strictly binary positive/negative outcomes. The shift toward continuous signal-to-noise data, especially in early and nonpivotal studies, makes intuitive sense, and there seemed to be good consensus on this. Improved assay performance has changed the landscape, and interpretation strategies are clearly working to catch up.
What stood out to me was the restraint shown in these conversations. Rather than advocating for sweeping abandonment of tiered strategies, most speakers emphasized context, phase-appropriateness, and robust assay understanding. That balance between innovation and caution felt like a recurring WRIB theme.
Confirmatory Tier Testing: No Single Right Answer
The discussion around confirmatory assays reinforced how situational IG strategy really is. I heard thoughtful arguments on both sides: concerns about limited orthogonality and biological insight on the one hand, and the ongoing need for false-positive control and regulatory confidence on the other.
From where I sit, the most compelling takeaway was not whether confirmatory tiers should stay or go, but how strongly participants emphasized prespecification, data-driven justification, and regulator dialogue if changes are contemplated. That framing made it clear that this is less about dismantling paradigms and more about applying them judiciously.
AI, ML, and Automation: From Curiosity to Capability
If immunogenicity challenged me to listen closely, AI/ML and automation felt like areas where my own curiosity and experience were directly engaged. These topics generated substantial conversation, but what struck me most was how pragmatic, and in some cases sobering, the collective perspective has become.
Hype Is Fading, Integration Is Growing
There was broad agreement that AI and ML are delivering real value today, but only in very specific contexts. Success stories tended to share common traits: well-defined problems, strong data foundations, and clear ownership. Conversely, many initiatives never make it past proof-of-concept when data quality, workflow integration, or change management are underestimated.
What resonated most with me was the consistent framing of AI/ML as an enabler, not a solution in search of a problem. Whether applied to QC trending, anomaly detection, biomarker data interpretation, or even report drafting, the emphasis was squarely on augmentation, not replacement of scientific judgment.
The Hard Work Is Often Upstream
Several conversations reinforced an uncomfortable truth: making data “AI-ready” is often the real challenge. Standardization, metadata discipline, and cross-platform integration are prerequisites that don’t always get the same attention as the end-objective intent. In that sense, AI/ML maturity feels tightly coupled to organizational maturity rather than purely technical capability.
In regulated bioanalysis, the bar is understandably even higher. Explainability, validation strategy, lifecycle management, and accountability were recurring themes, and rightly so. The sense I came away with is that meaningful adoption is happening, but deliberately, and with eyes wide open.
Hybrid IA–LC–MS and HRMS: A Personal Anchor Point
Advanced LC–MS, including hybrid IA–LC–MS and HRMS, felt like one of the most mature and almost settled areas of discussion at the meeting and perhaps the one that resonated most strongly with my own perspective.
From Novelty to Normalized Practice
Despite the continued absence of modality-specific regulatory guidance, these platforms are now broadly accepted and routinely deployed in regulated bioanalysis. What struck me was how little defensiveness there was around their use; the conversation has clearly moved from Can we? to What is the right tool for this question?
Hybrid IA-LC-MS is no longer framed as a challenger to ligand-binding assays, but as a complementary capability, especially valuable where selectivity, reagent independence, or molecular specificity are limiting factors. For complex modalities such as ADCs, emerging conjugates and oligonucleotides, advanced LC–MS approaches are increasingly the default rather than the exception.
That same theme carried into several positive discussions around the use of high-resolution mass spectrometry (HRMS) for oligonucleotide and large-molecule bioanalysis, including ADCs and protein biomarkers. HRMS was consistently framed as an enabling technology for situations where molecular structure doesn’t align with MS/MS fragmentation, metabolite complexity (e.g. oligonucleotide metabolism), or selectivity limitations strain more traditional platforms. Rather than being viewed as experimental or aspirational, HRMS approaches appear increasingly normalized. What struck me was how often HRMS was positioned as complementary to existing workflows: extending analytical insight without displacing established platform approaches. As with other areas discussed at WRIB, success with HRMS was tied not to the technology itself, but to clear scientific intent, appropriate validation strategies, and thoughtful integration into broader bioanalytical and development decision-making.
Fit for Purpose Still in Vogue
An adjacent discussion that I found particularly thoughtful centered on the often-raised question of whether more explicit regulatory guidance is needed for large-molecule and biomarker LC–MS bioanalysis. Given the growing diversity of analyte modalities we are now asked to measure, there was a shared view that truly prescriptive guidance may be difficult, if not counterproductive, to define. Instead, many seemed comfortable treating ICH M10 as a foundational reference point, with the recognition that it cannot (and likely should not) anticipate every modality-specific nuance. From there, the scientific question “what needs to be measured, with what confidence, and for what decision” naturally takes precedence and should drive both the assay design and the overall bioanalytical strategy.
This emphasis on fit-for-purpose design also connected back to a poster my colleague Jason Truesdale presented on multiplexing immunogenicity assays using a Luminex® platform. While distinct from LC–MS, the poster reflected a similar mindset: start with the biological and analytical question, then design the assay architecture accordingly. The work demonstrated that a multiplexed, bead-based approach can reliably support multi-domain immunogenicity assessment within a single assay. On-demand bead coupling improved assay stability and consistency while enabling a more rapid workflow, and the method achieved sensitivities below 100 ng/mL without evidence of prozone effects up to 20,000 ng/mL across both the Cas9 and PEG domains of the multidomain construct under study. Importantly, adjusting bead ratios allowed balanced detection despite differing minimum required dilutions, while the multiplex format reduced reagent consumption, sample volume, and overall development effort relative to single-plex assays.
What resonated with me personally was how forward-looking the discussion around next steps was, expanding domain coverage for more complex multi-specific therapeutics, integrating automation to support higher-throughput clinical studies, formally bridging across platforms, and ultimately deploying the assay in early-phase trials to test performance under real-world conditions. In many ways, the poster reinforced a broader WRIB theme: whether developing multiplex immunogenicity assays or advanced LC–MS methods, durable progress comes from platform-agnostic thinking anchored in scientific intent, operational practice, and clinical relevance.
Conclusions
What I took away most strongly from WRIB and GCC this year is a sense of measured maturity across the field. Whether discussing IG strategy evolution, AI/ML adoption, or advanced LC–MS platforms, the dominant tone was not one of disruption for its own sake, but of thoughtful refinement.
For me personally, the meeting reinforced the value of staying close to adjacent disciplines, even where they are not your core strengths. The best discussions were those that linked analytical choices to biological meaning and clinical relevance. This all reminded me that the real progress in bioanalysis lies not in any single technology, but in how well we connect the pieces.
