Rapid and reliable assessment of RNA purity, content, and length is essential to advance mRNA therapeutic development. Here, we present a high-throughput microfluidic multi-attribute method for directional analysis of mRNA, LNP, and DP samples. This approach streamlines characterization by enabling simultaneous evaluation of multiple RNA attributes, improving data turnaround and scalability while maintaining analytical quality and achieving substantial cost savings compared to traditional chromatographic methods.

In the discovery and development of novel biotherapeutics and genetic medicines, an increasingly complex landscape of antigen and therapeutic modalities demands synergistic implementation of advanced tools for robust characterization. We present an integrative toolkit for biophysical characterization combining dynamic light scattering, size-exclusion chromatography-multiangle light scattering, and microfluidic nano particle analysis that delivers deep insights to drive innovation in antibody-antigen, lipid nanoparticle, and virus-like particle platforms.

In our most recent, under-review work, we show that resting CD8β T cells exhibit a bimodal distribution of buoyant mass, measured label-free by our SMR, that defines an intrinsic immune-fitness axis. Mechanistically, “light” cells are activation-delayed/exhaustion-prone with impaired mitochondrial function and stalled biogenesis, whereas “heavy” cells are biosynthetically primed. In a neoadjuvant melanoma cohort, a pre-treatment T cell buoyant-mass profile stratified checkpoint-therapy response: a single “heavy-cell mass” metric achieved AUC 0.81, and a combined model reached AUC 0.88, outperforming tumor mutational burden. Our rapid assay, performed in a CLIA-certified lab, provides the first and only label-free estimate of T cell immune fitness.

Cryo-EM is increasingly applicable to small proteins through innovative scaffold strategies. We present a coiled-coil fusion approach enabling atomic-level structure determination of kRasG12C at 3.7 Å resolution, bound to MRTX849 and GDP. This method is simple to implement and adaptable to other targets. We also evaluated complementary techniques for proteins lacking terminal helices. These findings expand Cryo-EM’s utility in drug discovery and structural biology.

We have recently developed a novel, high-throughput nanoscale HDX-MS (nHDX) platform for structural proteomics, delivering unprecedented sensitivity for complex protein systems. By reducing sample needs to the nanogram level, nHDX facilitates the rapid screening of antibody-target interactions. This robust, automated platform provides high-resolution epitope/paratope mapping across a broad affinity range, reliably analyzing lower purity material and small batch purifications, bypassing the need for extensive front-end processing.

The Institute for Protein Innovation (IPI) has developed a scalable workflow that applies biophysical characterization standards from therapeutic antibody development to research-grade reagents. This systematic approach integrates surface plasmon resonance, flow cytometry, and immunofluorescence to assess binding kinetics, affinity, and functional performance. A distinguishing feature is comprehensive cross-reactivity profiling across related protein families, providing quantitative specificity insights that enhance reproducibility and confidence in antibody-based research tools.

• Formulation challenges of novel modalities (e.g., ADCs, bispecifics) compared with conventional mAbs
• In silico modeling tools to support formulation design and risk assessment
• Analytical and biophysical methods for characterizing developability and stability
• Opportunities and limitations of AI/ML in formulation development of next-generation biologics​

• Role of biophysical methods (e.g., SPR, BLI) in assessing antibody binding and kinetics
• Strengths and limitations of biophysical data in predicting performance in downstream applications
• Challenges in translating affinity and kinetics into functional or biological relevance
• Integrating biophysical data with cell-based and application-specific validation approaches
• Frameworks for interpreting and contextualizing validation evidence across different assay types
• Opportunities to standardize how validation data are generated, compared, and communicated​

Although mass spectrometry-based methods are some of the most informative assays in the biotherapeutic discovery toolkit, they are among the most difficult to automate due to multistep sample preparation protocols and diverse instrument methods. Unique attribute reporting needs across different modalities and project phases (late discovery and lead development) increases the complexity of requirements for a harmonized data analysis solution. In this talk, we will discuss our solutions for 1) a scalable, adaptable robotic sample preparation system and 2) a flexible, rapidly adaptable data-acquisition, data processing, and reporting pipeline.

High-throughput protein expression demands fast QC. Manual analysis and reporting were a bottleneck, consuming excessive hands-on analyst time and limiting throughput. We standardized rule-based QC criteria and automated extraction of key MS metrics to enable consistent pass/fail assessment. A web-based parsing and reporting tool cut hands-on time by 80% while maintaining ~98% concordance. This framework delivers scalable, high-throughput intact MS QC and establishes the foundation for end-to-end automation.

We present an automated deep-field LC-MS/MS workflow that dramatically improves detection of low-abundance host cell proteins without enrichment. By iteratively expanding peak-exclusion lists on the Orbitrap Exploris AcquireX platform, the method eliminates redundant sampling, boosts MS/MS quality, and uncovers HCPs missed by traditional DDA—even at far lower digest loading. Validated across multiple commercial mAbs, this approach delivers higher-confidence identifications and extends seamlessly to broader biologics characterization.

NMR spectroscopy holds great promise for RNA-based drug discovery. However, the low proton density in RNA limits short-range structural information, posing a challenge for NMR studies. Long-range restraints, such as residual dipolar couplings (RDCs), are crucial for accurate tertiary structure determination. Using a state-of-the-art 1.3 GHz NMR, we successfully measured RDCs of an RNA aptamer. This demonstrates the feasibility of obtaining precise structural insights into therapeutic RNA using Ultra-High-Field NMR.

Predictive stability modeling is revolutionizing biologic drug shelf-life evaluation by providing accurate long-term stability forecasts based on relevant short-term data. Several practical applications will be presented. The integration of scientific rigor and statistical robustness in these models supports critical CMC decision-making, optimizes stability filing strategies, and accelerates the development timeline for new biologic therapies.

Developability assessments are an important stage gate in the journey of antibody therapeutics. A thorough risk profiling of the leads in research is essential for effective selection, and success later in development. However, with complex formats, early risk profiling is not always predictive. Focusing on a core set of characteristics of a large panel of molecules in early research may have a bigger payoff in selecting more diverse leads and save on critical resources.

Sedimentation Velocity Analytical Ultracentrifugation (SV AUC) is a powerful technique for characterizing therapeutics and vaccines. By directly analyzing size variants and polydispersity in native sample matrices across a broad dynamic range, it provides an ideal approach for assessing diverse drug candidates during development. This presentation showcases examples of how recent advancements in instrumentation and data analysis are enabling faster, more informative characterization of therapeutic proteins, oligonucleotides, and vaccines.