Proteomics in Transition: From Discovery to Diagnostic Utility
The promise of proteomics lies in its ability to illuminate disease biology at scale, transform translational research, and guide the development of precision diagnostics and targeted therapies. While genomic technologies have matured into routine tools for mutation detection and risk stratification, proteomics remains fragmented by platform inconsistencies, quantification challenges, and limited clinical translatability.
Recent advances in ultrasensitive immunoassay technologies are bridging this gap. Among these, the Simoa® digital immunoassay technology has redefined the landscape of biomarker detection through high sensitivity, absolute quantitation, and scalable clinical readiness. By enabling reproducible measurement of low-abundance proteins in plasma, CSF, and alternative matrices such as urine and saliva, Simoa is accelerating the translation of biomarkers from discovery to diagnostic utility—an evolution explored in greater depth in our latest white paper.
The Need for Analytical Rigor in Translational Proteomics
Conventional proteomics platforms, while valuable for early discovery, struggle with key limitations when applied to real-world clinical development. These include relative quantitation models, high coefficients of variation (CVs), and inconsistent detectability across sample types or collection protocols.
To move from signal detection to diagnostic-grade performance, assays must meet stringent criteria for limit of detection (LOD), precision (%CV), dynamic range, matrix tolerance, and lot-to-lot reproducibility. Furthermore, they must be deployable in regulated settings under CLIA, LDT, or IVD frameworks, requiring robust quality systems and traceable calibration.
Simoa meets these criteria across a growing portfolio of biomarkers relevant to neurology, immunology, oncology, infectious disease, and cardiometabolic research. As of 2025, over 3,000 peer-reviewed publications have demonstrated Simoa’s translational utility, with widespread adoption by top biopharma sponsors, academic centers, and CROs.
Translating Biomarkers into Clinical Utility
For proteomics to impact medicine, biomarkers must evolve into actionable endpoints that guide diagnosis, trial design, and reimbursement. Simoa technology enables this transformation across four key domains:
1. Early Detection and Risk Stratification
Protein biomarkers such as pTau217 and neurofilament light chain (NfL) have been shown to rise years before the onset of clinical symptoms in neurodegenerative conditions such as Alzheimer’s disease and ALS (Preische et al., 2019; Janelidze et al., 2022). Their early detectability enables patient stratification based on biological evidence of disease, supporting preventive interventions and reducing misclassification in clinical trials.
Validation data from the ALZpath pTau217 assay on the Quanterix HD-X platform confirmed high analytical sensitivity, with LLOQs as low as 0.00977 pg/mL in plasma, and clear separation between Alzheimer’s patients and controls across plasma, serum, and CSF. These results underscore the assay’s ability to detect preclinical disease states, making it well-suited for early-enrichment strategies in therapeutic trials (Yang et al., 2024).
2. Trial Acceleration
The ability to measure biomarkers in plasma using minimally invasive methods reduces reliance on PET imaging and lumbar punctures, both of which limit participant access and increase cost. Plasma pTau217 and BD-Tau correlate strongly with tau PET (Palmqvist et al., 2025), enabling use as pre-screening tools to prioritize PET or CSF follow-up only in biomarker-positive cases.
Trial modeling has shown that implementing such enrichment strategies can cut screen failures by up to 40% and reduce recruitment timelines by several months (Inan et al., 2020). These efficiencies translate directly into cost savings and faster trial execution, particularly in competitive therapeutic areas such as Alzheimer’s, ALS, and MS.
3. Pharmacodynamic Monitoring
Longitudinal biomarker measurement allows real-time assessment of target engagement and therapeutic efficacy. For example, NfL levels have been used as pharmacodynamic markers in ALS and MS trials, where decreases correlate with slowed neurodegeneration (Ahmad et al., 2022).
A head-to-head evaluation by Frontage Laboratories compared two pTau217 assays using the same antibody pairs, one run on the Quanterix HD-X platform and other on Alamar’s ARGO HT system. The HD-X achieved 100% detectability across all plasma samples, while the ARGO HT system detected only 85%. More critically, the Simoa platform maintained coefficient of variation (CV) values under 10%, compared to 14–17% for the ARGO HT system, a level of imprecision that undermines utility in dynamic clinical trials.
Such analytical robustness is essential for adaptive designs, early futility decisions, and pharmacoeconomic modeling. When treatment effects are subtle or population heterogeneity is high, platform-level precision can determine whether a trial succeeds or fails.
4. Companion Diagnostics and Reimbursement
Several Simoa-based biomarkers, including pTau217 and NfL, are currently under regulatory evaluation as potential companion diagnostics for emerging Alzheimer’s therapies. The transition from research-use-only to diagnostic status requires alignment with FDA guidance on analytical validation, clinical performance, and labeling.
Quanterix is actively supporting this transition through collaborative studies, quality-system compliance, and platform standardization across labs. As value-based care models become more prevalent, biomarkers that enable diagnostic labeling and therapeutic targeting are also likely to drive payer adoption and coverage decisions, especially when supported by robust real-world data and health economics analyses.
Conclusion: A New Standard for Translational Proteomics
Proteomic biomarkers are entering a new phase, one defined not by exploratory signals but by rigorously validated assays that meet the analytical and regulatory standards required for clinical adoption. As drug development grows more targeted and time-sensitive, platforms must provide quantifiable, reproducible, and biologically meaningful outputs that support decision-making across all stages of translational research. Technologies like Simoa are no longer niche tools, they are setting the benchmark for how protein biomarkers will be developed, validated, and deployed across medicine.
Written by: Shana Tetrault, PhD, Director of Product Marketing
References:
- Ahmad, A. Z., et al. (2022). Neurofilament light chain levels as a biomarker for disease activity and response to therapy in multiple sclerosis and ALS. Journal of Neuroimmunology, 368, 577874.
- Inan, H. N., et al. (2020). Modeling biomarkerguided enrichment strategies to reduce screen failure rates in Alzheimer’s disease clinical trials. Alzheimer’s & Dementia, 16(12), 1681–1691.
- Janelidze, S., et al. (2022). Plasma Ptau217 performs better than Ptau181 as a biomarker of Alzheimer’s disease. Nature Medicine, 28(3), 658–662.
- Palmqvist, S., et al. (2025). Plasma ptau217 and tau PET in early Alzheimer’s disease. The Lancet Neurology, in press.
- Preische, O., et al. (2019). Serum neurofilament dynamics predict neurodegeneration and clinical progression in presymptomatic Alzheimer’s disease. Nature Medicine, 25, 277–283.
- Zhang, H., Liu, J., Zhang, N., Jeromin, A., & Lin, Z. J. (2024). Validation of an ultrasensitive method for quantitation of phosphoTau 217 (pTau217) in human plasma, serum, and CSF using the ALZpath pTau217 assay on the Quanterix HDX platform