Home Single Molecule Counting (SMC^®) TechnologyWhat Is Single Molecule Counting (SMC^®) Technology? An Overview of Ultrasensitive Immunoassay Technology

What Is Single Molecule Counting (SMC^®) Technology?
An Overview of Ultrasensitive Immunoassay Technology

Curious about how ultrasensitive immunoassay technology can enhance your research? Learn how Single Molecule Counting (SMC^®) technology is advancing research in immunology, cardiotoxicity, neuroscience, and more. Also, explore the advantages of SMC^® technology and see how researchers are using these high sensitivity assays to advance their discoveries.

What Is SMC^® Technology?
SMC^® Technology Workflow
Ultrasensitive Biomarker Detection Platform
Research Applications
Frequently Cited Advantages of SMC^® Technology
Tips and Tricks for Running SMC^® Assays
Related Webinars and Events
Publications Using SMC^® Technology

What Is SMC^® Technology?

Single Molecule Counting (SMC^®) technology is an advanced ultrasensitive immunoassay technology that gives researchers the power to detect biomarkers that were previously undetectable down to the femtogram/mL. It provides an indispensable tool in the researcher’s arsenal to help them move novel biology forward, fueling the discovery and development of new therapeutics. SMC^® technology, originally developed by Singulex^®, Inc. in 2004, relies on a basic sandwich immunoassay format utilizing two antibodies specific to the analyte of interest: a capture antibody coated on a plate or magnetic bead and a detection antibody conjugated to a fluorescent protein. Only SMC^® immunoassay technology allows researchers to use both plate-based and bead-based assay designs, thus offering unmatched flexibility in assay design.

SMC^® Technology Workflow

Scientists familiar with traditional immunoassays, such as ELISAs, know that sensitivity, matrix effects, and dynamic range affect how they make measurements — or if they can make them at all. Combining a traditional immunoassay workflow with patented SMC^® technology enables the detection of low-abundant biomarkers, such as proteins and nucleic acids, with unparalleled sensitivity and accuracy, capturing concentrations down to the femtogram/mL level. Researchers can detect, and monitor changes in, extremely low levels of established disease biomarkers such as cardiac troponin I and cytokines.

The SMC^® technology workflow has 5 steps described below. Distinguishing SMC^® assays from traditional immunoassays, an elution buffer is used to break apart the immunoassay complex once constructed. The eluate containing the fluorescent reporter molecule is transferred to a 384-well plate, thus removing other assay components that contribute to high background fluorescent signal, such as the magnetic beads and antibodies used for analyte capture. The plate is loaded into the SMCxPRO^® instrument, the second-generation SMC^® instrument, where a laser excites the fluorescent-labeled detection antibody as it passes through a narrow interrogation window. Individual photons are captured by an avalanche photodiode and the signal is recorded. This allows for the digital quantification of individual molecules. Analyte concentrations in the unknown samples are calculated using the corresponding standard curve.

The steps in the SMC^® Technology Workflow include:

Analyte of interest in solution

Capture on plate or bead

Detect

Elute

a. Complex is chemically broken apart

Quantify

a. Sample is detected by laser and detection tags are counted

After following a traditional sandwich ELISA workflow, the proprietary SMC^® protocol steps concentrate the signal by disassociating the fluorescent-labeled detection antibody from the sandwich complex. The fluorescent-labeled detection antibody is the signal acquired in the SMCxPRO^® instrument. This results in reproducible signal, and improved quantification of proteins, particularly those at very low abundance. With better precision and sensitivity, researchers can:

Quantify previously undetectable analytes
Better stratify sample populations
Gain insights into novel biological mechanisms
Require fewer data points for critical decision making
Accelerate drug discovery and development
Reduce program costs and improve productivity

Ultrasensitive Biomarker Detection Platform

SMC^® technology offers an ultrasensitive biomarker detection platform with the flexible SMCxPRO^® platform. Table 1 compares running assays on this platform to running traditional ELISAs.

Ancillary Equipment and Kits to Enhance the SMC^® Workflow

To enhance the SMCxPRO^® platform, we also offer ancillary equipment and kits specifically for SMC^® technology, such as:

Research Applications

Ultrasensitive immunoassays can enhance research in a variety of fields because the improved sensitivity allows researchers to dive deeper into their studies. Research applications of SMC^® technology include the areas of:

Frequently Cited Advantages of SMC^® Technology

Single Molecule Counting (SMC^®) technology provides maximum immunoassay performance while following a workflow very similar to traditional ELISA technology.

Traditional ELISA methodologies demonstrate limitations in sensitivity and dynamic range, typically require high sample volumes, and are susceptible to matrix effects. Combined, these factors reduce the utility of traditional ELISAs for the detection of low-abundant proteins and endogenous biomarker levels in healthy subjects, thus hampering statistical analysis among study groups. By adapting an ELISA workflow, SMC^® technology achieves improved signal-to-noise ratios over traditional immunoassay technologies, thus providing quantification at both low and high levels of expression in one complete system. Digital counting of fluorescent events improves the assay sensitivity and extends the assay dynamic range beyond what can be achieved with traditional immunoassays.

Because SMC^® immunoassay technology can reach fg/mL sensitivity ranges, this platform offers the ability to dilute pre-clinical samples, when only low sample volumes are available.

Users are fully supported by onsite Immunoassay Field Application Scientists and Specialists, as well as dedicated technical support teams.

We understand the SMC^® platform is an important investment for research labs and is committed to ensuring the success of its users. Regardless of the types of assays being used, all SMC^® users are fully supported by onsite Immunoassay Field Application Scientists and Specialists who have experience working with researchers from a broad range of lab types, including academic, government, biotech, pharma, CRO, and regulated labs.

The SMC^® platform is a versatile system that can be used in multiple study types, including biomarker assessment, bioanalytical work such as pharmacokinetic and pharmacodynamic studies, and immunogenicity testing.

Complimenting a menu of off-the-shelf, verified assay kits, the SMC^® Custom Assay and Sample Testing team can be contracted to perform custom assay development, verification services, and sample testing at their site in St. Louis, MO.

SMC^® assays are available, or can be developed, in both plate-based and bead-based formats.

The proprietary SMC^® technology allows scientists to measure proteins with increased precision, enabling unparalleled quantification at low and high abundance levels of expression. The flexible SMC^® immunoassay system acquires data from both plate-based assays and bead-based assays, providing a choice of format depending on budget and quantification requirements.

The SMC^® assay read plate is a 384-well plate and the entire plate can be read in less than three hours. This high-throughput platform allows researchers to perform an entire SMC^® assay run from sample prep through data analysis in one day.

SMCxPRO^® system can be integrated with a Hamilton Microlab^® STARlet liquid handing system, increasing assay throughput.

In certain environments, automation of SMC^® immunoassays is desirable so that researchers can focus on other high-value activities to increase overall efficiency. The Hamilton Microlab^® STARlet liquid handling workstation offers a hands-free option providing a robust, reproducible SMC^® workflow eliminating sources of error and variability. This technology is routinely used by the Custom Assay and Sample Testing team.

Both data acquisition and analysis are performed within a single software package.

The SMCxPRO^® software package was developed in-house, thus affording full transparency to data processing algorithms. The software is user-friendly and allows end-users to set up the instrument, read the plate, and analyze results quickly and easily. The software enables easy data curation, including manual outlier removal.

For labs operating in a regulated environment, the SMCxPRO^® instrument generates one signal data stream that can be imported into Laboratory Information Management Systems, such as WATSON, or other software. 21 CFR Part 11 compliance features can also be enabled.

Request info on SMC^® technology

For Research Use Only. Not For Use In Diagnostic Procedures.

Tips and Tricks for Running SMC^® Assays

Have questions about running SMC^® assays? Check out these articles for helpful tips:

Related Webinars

Publications Using SMC^® Technology

See how researchers are using SMC^® technology in the publications list below organized by research area.

Neurology

Increased levels of the synaptic proteins PSD-95, SNAP-25, and Neurogranin in the cerebrospinal fluid of patients with Alzheimer’s Disease. Kivisäkk P, Carlyle BC, Sweeney T, Quinn JP, Ramirez CE, Trombetta BA, Mendes M, Brock M, Rubel C, Czerkowicz J, et al. 2022 Feb 23. doi:10.21203/rs.3.rs-1366881/v1.
A study of the longitudinal changes in multiple cerebrospinal fluid and volumetric magnetic resonance imaging biomarkers on converter and non‐converter Alzheimer’s disease subjects with consideration for their amyloid beta status. Morar U, Izquierdo W, Martin H, Forouzannezhad P, Zarafshan E, Unger E, Bursac Z, Cabrerizo M, Barreto A, Vaillancourt DE, et al. 2022. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring. 14(1). doi:10.1002/dad2.12258.
The prognostic utility of CSF neurogranin in predicting future cognitive decline in the Alzheimer’s disease continuum: A systematic review and meta-analysis with narrative synthesis. Yoong SQ, Lu J, Xing H, Gyanwali B, Tan YQ, Wu XV. 2021. Ageing Research Reviews. 72:101491. doi:10.1016/j.arr.2021.101491.
Biomarkers in Huntington’s. Killoran A. 2021 Oct 16. Neurodegenerative Diseases Biomarkers.:235–262. doi:10.1007/978-1-0716-1712-0_10.
An ultra‐sensitive immunoassay detects and quantifies soluble Aβ oligomers in human plasma. Liu L, Kwak H, Lawton TL, Jin S, Meunier AL, Dang Y, Ostaszewski B, Pietras AC, Stern AM, Selkoe DJ. 2021 Sep 22. Alzheimer’s & Dementia. doi:10.1002/alz.12457.
BIOM-15. SERUM AMYLOID-β42 AS A NONINVASIVE BIOMARKER FOR PROGNOSIS AND HISTOLOGIC FEATURES OF GLIOMA. Hwang K, Noh M, Park J, Ji SY, Han JH, Ahn KS, Kim C-Y. 2021. Neuro-Oncology. 23(Supplement_6):vi13–vi13. doi:10.1093/neuonc/noab196.046.
Recent Technological Developments in the Diagnosis and Treatment of Cerebral Edema. Deshmukh KP, Rahmani Dabbagh S, Jiang N, Tasoglu S, Yetisen AK. 2021. Advanced NanoBiomed Research. 1(11):2100001. doi:10.1002/anbr.202100001.
Widespread and sustained target engagement in Huntington’s disease minipigs upon intrastriatal microRNA-based gene therapy. Vallès A, Evers MM, Stam A, Sogorb-Gonzalez M, Brouwers C, Vendrell-Tornero C, Acar-Broekmans S, Paerels L, Klima J, Bohuslavova B, et al. 2021. Science Translational Medicine. 13(588). doi:10.1126/scitranslmed.abb8920.
Quantifying misfolded protein oligomers as drug targets and biomarkers in Alzheimer and Parkinson diseases. Kulenkampff K, Wolf Perez Adriana-M, Sormanni P, Habchi J, Vendruscolo M. 2021. Nature Reviews Chemistry. 5(4):277–294. doi:10.1038/s41570-021-00254-9.
Cognitively normal APOE ε4 carriers have specific elevation of CSF SNAP-25. Butt OH, Long JM, Henson RL, Herries E, Sutphen CL, Fagan AM, Cruchaga C, Ladenson JH, Holtzman DM, Morris JC, et al. 2021. Neurobiology of Aging. 102:64–72. doi:10.1016/j.neurobiolaging.2021.02.008.
Exogenous IGF-1 improves tau pathology and neuronal pyroptosis in high-fat diet mice with cognitive impairment. Sui G, Wang L, Yang C, Guo M, Xiong X, Chen Z, Wang F. 2021 Feb 11. doi:10.21203/rs.3.rs-158607/v1.
Intrastriatal Administration of AAV5-miHTT in Non-Human Primates and Rats Is Well Tolerated and Results in miHTT Transgene Expression in Key Areas of Huntington Disease Pathology. Spronck EA, Vallès A, Lampen MH, Montenegro-Miranda PS, Keskin S, Heijink L, Evers MM, Petry H, Deventer SJ van, Konstantinova P, et al. 2021. Brain Sciences. 11(2):129. doi:10.3390/brainsci11020129.
Identification of Mild Cognitive Impairment Subtypes Predicting Conversion to Alzheimer’s Disease Using a Heterogeneous Mixture Learning. Kikuchi M, Kobayashi K, Itoh S, Kasuga K, Miyashita A, Ikeuchi T, Yumoto E, Fushimi Y, Takeda T, Manabe S, et al. 2020 Dec 17. doi:10.21203/rs.3.rs-129455/v1.
TBK1 phosphorylates mutant Huntingtin and suppresses its aggregation and toxicity in Huntington’s disease models. Hegde RN, Chiki A, Petricca L, Martufi P, Arbez N, Mouchiroud L, Auwerx J, Landles C, Bates GP, Singh‐Bains MK, et al. 2020. The EMBO Journal. 39(17). doi:10.15252/embj.2020104671.
Identification of distinct conformations associated with monomers and fibril assemblies of mutant huntingtin. Ko J, Isas JM, Sabbaugh A, Yoo JH, Pandey NK, Chongtham A, Ladinsky M, Wu W-L, Rohweder H, Weiss A, et al. 2018. Human Molecular Genetics. 27(13):2330–2343. doi:10.1093/hmg/ddy141.
0453 INFILTRATION OF VRC01 INTO THE CEREBROSPINAL FLUID IN HUMANS IN THE RV397 STUDY. Conference on Retroviruses and Opportunistic Infections Boston USA March 8-11, 2020. Madhuu Prabhakaran, Sandeep Narpala, Lucio Gama, Donn J. Colby, Phillip Chan, Carlo Sacdalan, Khunthalee Benjapornpong, Jintanat Ananworanich, Nittaya Phanupak, Suteeraporn Pinyakorn, Trevor A. Crowell, Serena Spudich, Adrian B McDermott on behalf of the RV397 study team
Advances in amyloid beta oligomer detection applications in Alzheimer’s disease. Jamerlan A, An SSA, Hulme J. 2020. TrAC Trends in Analytical Chemistry. 129:115919. doi:10.1016/j.trac.2020.115919.
Ultrasensitive quantitative measurement of huntingtin phosphorylation at residue S13. Cariulo C, Verani M, Martufi P, Ingenito R, Finotto M, Deguire SM, Lavery DJ, Toledo-Sherman L, Lee R, Doherty EM, et al. 2020. Biochemical and Biophysical Research Communications. 521(3):549–554. doi:10.1016/j.bbrc.2019.09.097.
Target engagement in an alzheimer trial: Crenezumab lowers amyloid β oligomers in cerebrospinal fluid. Yang T, Dang Y, Ostaszewski B, Mengel D, Steffen V, Rabe C, Bittner T, Walsh DM, Selkoe DJ. 2019. Annals of Neurology. 86(2):215–224. doi:10.1002/ana.25513.
Emerging cerebrospinal fluid biomarkers in autosomal dominant Alzheimer’s disease. Schindler SE, Li Y, Todd KW, Herries EM, Henson RL, Gray JD, Wang G, Graham DL, Shaw LM, Trojanowski JQ, et al. 2019. Alzheimer’s & Dementia. 15(5):655–665. doi:10.1016/j.jalz.2018.12.019.
D06 Quantitative assays to monitor huntingtin changes in pre-clinical and clinical hd samples. Kuhlbrodt K, Baldo B, Reindl W, Carty N, Tillack K, Berson N, Mack V, Bazenet C, Herrmann F, vanderKam E, et al. 2018 Sep. Wet biomarkers. doi:10.1136/jnnp-2018-ehdn.88.
Decoding the synaptic dysfunction of bioactive human AD brain soluble Aβ to inspire novel therapeutic avenues for Alzheimer’s disease. Li S, Jin M, Liu L, Dang Y, Ostaszewski BL, Selkoe DJ. 2018. Acta Neuropathologica Communications. 6(1). doi:10.1186/s40478-018-0626-x.
APOE ε4 is associated with higher levels of CSF SNAP-25 in prodromal Alzheimer’s disease. Wang S, Zhang J, Pan T. 2018. Neuroscience Letters. 685:109–113. doi:10.1016/j.neulet.2018.08.029.
AAV5-miHTT Gene Therapy Demonstrates Broad Distribution and Strong Human Mutant Huntingtin Lowering in a Huntington’s Disease Minipig Model. Evers MM, Miniarikova J, Juhas S, Vallès A, Bohuslavova B, Juhasova J, Skalnikova HK, Vodicka P, Valekova I, Brouwers C, et al. 2018. Molecular Therapy. 26(9):2163–2177. doi:10.1016/j.ymthe.2018.06.021.
Neurogranin as Cerebrospinal Fluid Biomarker for Alzheimer Disease: An Assay Comparison Study. Willemse EAJ, De Vos A, Herries EM, Andreasson U, Engelborghs S, van der Flier WM, Scheltens P, Crimmins D, Ladenson JH, Vanmechelen E, et al. 2018. Clinical Chemistry. 64(6):927–937. doi:10.1373/clinchem.2017.283028.
Longitudinal decreases in multiple cerebrospinal fluid biomarkers of neuronal injury in symptomatic late onset Alzheimer’s disease. Sutphen CL, McCue L, Herries EM, Xiong C, Ladenson JH, Holtzman DM, Fagan AM. 2018. Alzheimer’s & Dementia. 14(7):869–879. doi:10.1016/j.jalz.2018.01.012.
A highly sensitive novel immunoassay specifically detects low levels of soluble Aβ oligomers in human cerebrospinal fluid. Yang T, O’Malley TT, Kanmert D, Jerecic J, Zieske LR, Zetterberg H, Hyman BT, Walsh DM, Selkoe DJ. 2015. Alzheimer’s Research & Therapy. 7(1):14. doi:10.1186/s13195-015-0100-y.
Interleukin 17F Level and Interferon Beta Response in Patients With Multiple Sclerosis. Hartung H-P, Steinman L, Goodin DS, Comi G, Cook S, Filippi M, O’Connor P, Jeffery DR, Kappos L, Axtell R, et al. 2013. JAMA Neurology. 70(8):1017. doi:10.1001/jamaneurol.2013.192.

Immunology/Inflammation/Virology

Efficacy, Safety, and Pharmacodynamic Effects of the Bruton’s Tyrosine Kinase Inhibitor Fenebrutinib (GDC‐0853) in Systemic Lupus Erythematosus: Results of a Phase II, Randomized, Double‐Blind, Placebo‐Controlled Trial. Isenberg D, Furie R, Jones NS, Guibord P, Galanter J, Lee C, McGregor A, Toth B, Rae J, Hwang O, et al. 2021. Arthritis & Rheumatology. 73(10):1835–1846. doi:10.1002/art.41811.
Proteomic signatures of inflammatory skin diseases: a focus on atopic dermatitis. Mikhaylov D, Del Duca E, Guttman-Yassky E. 2021. Expert Review of Proteomics. 18(5):345–361. doi:10.1080/14789450.2021.1935247.
Cardiovascular biomarkers in patients with COVID-19. Mueller C, Giannitsis E, Jaffe AS, Huber K, Mair J, Cullen L, Hammarsten O, Mills NL, Möckel M, Krychtiuk K, et al. 2021. European Heart Journal Acute Cardiovascular Care. 10(3):310–319. doi:10.1093/ehjacc/zuab009.
A sensitive method to quantify HIV-1 antibodies in mucosal samples. Prabhakaran M, Narpala S, Andrews SF, O’Connell S, Lin CL, Coates EE, Flach B, Ledgerwood JE, McDermott AB. 2021. Journal of Immunological Methods. 491:112995. doi:10.1016/j.jim.2021.112995.
Pharmacodynamic analysis of apremilast in Japanese patients with moderate to severe psoriasis: Results from a phase 2b randomized trial. Imafuku S, Nemoto O, Okubo Y, Komine M, Schafer P, Petric R, Ohtsuki M. 2020. The Journal of Dermatology. 48(1):80–84. doi:10.1111/1346-8138.15596.
P273 Ustekinumab and guselkumab treatment results in differences in serum IL-17A, IL-17F and CRP levels in PsA patients: a comparison from ustekinumab Phase 3 and guselkumab Phase 2 programmes. Siebert S, Loza MJ, Song Q, Gorecki PC, McInnes IB, Sweet K. 2020. Rheumatology. 59(Supplement_2). doi:10.1093/rheumatology/keaa111.266.
Upadacitinib Treatment Induces Significant Improvements in Th2 (Eosinophil Count, Serum CCL17/18/26) and Th22 (IL-22) Levels in Atopic Dermatitis That Are Associated With Improvements in Itch and Clinical Severity. Presented at the Revolutionizing Atopic Dermatitis (RAD) 2020 Virtual Congress, April 5, 2020, Chicago, Illinois. Emma Guttman-Yassky, Ana B. Pavel, Jonathan I. Silverberg, Stephan Weidinger, Julie Parmentier, Henrique D. Teixeira, Feng Hong, Lisa A. Beck.
Early Quantification of Systemic Inflammatory Proteins Predicts Long-Term Treatment Response to Tofacitinib and Etanercept. Tomalin LE, Kim J, Correa da Rosa J, Lee J, Fitz LJ, Berstein G, Valdez H, Wolk R, Krueger JG, Suárez-Fariñas M. 2020. Journal of Investigative Dermatology. 140(5):1026–1034. doi:10.1016/j.jid.2019.09.023.
Apremilast mechanism of efficacy in systemic-naive patients with moderate plaque psoriasis: Pharmacodynamic results from the UNVEIL study. Strober B, Alikhan A, Lockshin B, Shi R, Cirulli J, Schafer P. 2019. Journal of Dermatological Science. 96(3):126–133. doi:10.1016/j.jdermsci.2019.09.003.
Guselkumab Efficacy after Withdrawal Is Associated with Suppression of Serum IL-23-Regulated IL-17 and IL-22 in Psoriasis: VOYAGE 2 Study. Gordon KB, Armstrong AW, Foley P, Song M, Shen Y-K, Li S, Muñoz-Elías EJ, Branigan P, Liu X, Reich K. 2019. Journal of Investigative Dermatology. 139(12):2437-2446.e1. doi:10.1016/j.jid.2019.05.016.
Secukinumab Treatment Does Not Alter the Pharmacokinetics of the Cytochrome P450 3A4 Substrate Midazolam in Patients With Moderate to Severe Psoriasis. Bruin G, Hasselberg A, Koroleva I, Milojevic J, Calonder C, Soon R, Woessner R, Pariser DM, Boutouyrie‐Dumont B. 2019. Clinical Pharmacology & Therapeutics. 106(6):1380–1388. doi:10.1002/cpt.1558.
Impact of high‐altitude therapy on type‐2 immune responses in asthma patients. Boonpiyathad T, Capova G, Duchna H, Croxford AL, Farine H, Dreher A, Clozel M, Schreiber J, Kubena P, Lunjani N, et al. 2019. Allergy. 75(1):84–94. doi:10.1111/all.13967.
Combining single molecule counting with bead-based multiplexing to quantify biological inflammation time course following skeletal muscle injury. Tanner EA, Gary MA, Davis AA, McFarlin BK. 2019. Methods. 158:77–80. doi:10.1016/j.ymeth.2018.11.013.
Profiling Immune Expression to Consider Repurposing Therapeutics for the Ichthyoses. Paller AS. 2019. Journal of Investigative Dermatology. 139(3):535–540. doi:10.1016/j.jid.2018.08.027.
Clinical utility of circulating interleukin-6 concentrations in the detection of functionally relevant coronary artery disease. Walter J, Tanglay Y, du Fay de Lavallaz J, Strebel I, Boeddinghaus J, Twerenbold R, Doerflinger S, Puelacher C, Nestelberger T, Wussler D, et al. 2019. International Journal of Cardiology. 275:20–25. doi:10.1016/j.ijcard.2018.10.029.
Synergistic cytokine effects as apremilast response predictors in patients with psoriasis. Garcet S, Nograles K, Correa da Rosa J, Schafer PH, Krueger JG. 2018. Journal of Allergy and Clinical Immunology. 142(3):1010-1013.e6. doi:10.1016/j.jaci.2018.05.039.
An integrated model of alopecia areata biomarkers highlights both TH1 and TH2 upregulation. Song T, Pavel AB, Wen H-C, Malik K, Estrada Y, Gonzalez J, Hashim PW, Nia JK, Baum D, Kimmel G, et al. 2018. Journal of Allergy and Clinical Immunology. 142(5):1631-1634.e13. doi:10.1016/j.jaci.2018.06.029.
Ichthyosis molecular fingerprinting shows profound TH17 skewing and a unique barrier genomic signature. Malik K, He H, Huynh TN, Tran G, Mueller K, Doytcheva K, Renert-Yuval Y, Czarnowicki T, Magidi S, Chou M, et al. 2019. Journal of Allergy and Clinical Immunology. 143(2):604–618. doi:10.1016/j.jaci.2018.03.021.
Association between serum interleukin-17A and clinical response to tofacitinib and etanercept in moderate to severe psoriasis. Fitz L, Zhang W, Soderstrom C, Fraser S, Lee J, Quazi A, Wolk R, Mebus CA, Valdez H, Berstein G. 2018. Clinical and Experimental Dermatology. 43(7):790–797. doi:10.1111/ced.13561.
The NET-effect of combining rituximab with belimumab in severe systemic lupus erythematosus. Kraaij T, Kamerling SWA, de Rooij ENM, van Daele PLA, Bredewold OW, Bakker JA, Bajema IM, Scherer HU, Toes REM, Huizinga TJW, et al. 2018. Journal of Autoimmunity. 91:45–54. doi:10.1016/j.jaut.2018.03.003.
Serum from Asian patients with atopic dermatitis is characterized by T H 2/T H 22 activation, which is highly correlated with nonlesional skin measures. Wen H-C, Czarnowicki T, Noda S, Malik K, Pavel AB, Nakajima S, Honda T, Shin JU, Lee H, Chou M, et al. 2018. Journal of Allergy and Clinical Immunology. 142(1):324-328.e11. doi:10.1016/j.jaci.2018.02.047.
Evaluation of highly sensitive immunoassay technologies for quantitative measurements of sub-pg/mL levels of cytokines in human serum. Yeung D, Ciotti S, Purushothama S, Gharakhani E, Kuesters G, Schlain B, Shen C, Donaldson D, Mikulskis A. 2016. Journal of Immunological Methods. 437:53–63. doi:10.1016/j.jim.2016.08.003.
Due diligence in the characterization of matrix effects in a total IL-13 Singulex^® method. Fraser S, Soderstrom C. 2014. Bioanalysis. 6(8):1123–1129. doi:10.4155/bio.14.42.
Reference range and short- and long-term biological variation of interleukin (IL)-6, IL-17A and tissue necrosis factor-alpha using high sensitivity assays. Todd J, Simpson P, Estis J, Torres V, Wub AHB. 2013. Cytokine. 64(3):660–665. doi:10.1016/j.cyto.2013.09.018.
Interleukin 17F Level and Interferon Beta Response in Patients With Multiple Sclerosis. Hartung H-P, Steinman L, Goodin DS, Comi G, Cook S, Filippi M, O’Connor P, Jeffery DR, Kappos L, Axtell R, et al. 2013. JAMA Neurology. 70(8):1017. doi:10.1001/jamaneurol.2013.192.
Quantitative determination of human interleukin 22 (IL-22) in serum using Singulex^®-Erenna^® Technology. Shukla R, Santoro J, Bender FC, Laterza OF. 2013. Journal of Immunological Methods. 390(1-2):30–34. doi:10.1016/j.jim.2013.01.002.
Analytical validation of a highly sensitive microparticle-based immunoassay for the quantitation of IL-13 in human serum using the Erenna^® immunoassay system. St. Ledger K, Agee SJ, Kasaian MT, Forlow SB, Durn BL, Minyard J, Lu QA, Todd J, Vesterqvist O, Burczynski ME. 2009. Journal of Immunological Methods. 350(1-2):161–170. doi:10.1016/j.jim.2009.08.012.

Cardiovascular

Comparison of Point-of-Care and Highly Sensitive Laboratory Troponin Testing in Patients Suspicious of Acute Myocardial Infarction and Its Efficacy in Clinical Outcome. Mohammadzadeh S, Matani N, Soleimani N, Bazrafshan drissi H. 2022. Severino P, editor. Cardiology Research and Practice. 2022:1–7. doi:10.1155/2022/6914979.
A 0/1h-algorithm using cardiac myosin-binding protein C for early diagnosis of myocardial infarction. Kaier TE, Twerenbold R, Lopez-Ayala P, Nestelberger T, Boeddinghaus J, Alaour B, Huber I-M, Zhi Y, Koechlin L, Wussler D, et al. 2022 Feb 12. European Heart Journal Acute Cardiovascular Care. doi:10.1093/ehjacc/zuac007.
Biological variation of cardiac myosin-binding protein C in healthy individuals. Alaour B, Omland T, Torsvik J, Kaier TE, Sylte MS, Strand H, Quraishi J, McGrath S, Williams L, Meex S, et al. 2021. Clinical Chemistry and Laboratory Medicine (CCLM). 60(4):576–583. doi:10.1515/cclm-2021-0306.
Cardiovascular biomarkers in patients with COVID-19. Mueller C, Giannitsis E, Jaffe AS, Huber K, Mair J, Cullen L, Hammarsten O, Mills NL, Möckel M, Krychtiuk K, et al. 2021. European Heart Journal Acute Cardiovascular Care. 10(3):310–319. doi:10.1093/ehjacc/zuab009.
Interleukin-6 and Outcomes in Acute Heart Failure: An ASCEND-HF Substudy. Perez AL, GRODIN JL, CHAIKIJURAJAI T, WU Y, HERNANDEZ AF, BUTLER J, METRA M, FELKER GM, VOORS AA, MCMURRAY JJ, et al. 2021.Journal of Cardiac Failure. 27(6):670–676. doi:10.1016/j.cardfail.2021.01.006.
Clinical relevance of biological variation of cardiac troponins. Clerico A, Padoan A, Zaninotto M, Passino C, Plebani M. 2020. Clinical Chemistry and Laboratory Medicine (CCLM). 59(4):641–652. doi:10.1515/cclm-2020-1433.
Biological Variation of Cardiac Troponins in Health and Disease: A Systematic Review and Meta-analysis. Diaz-Garzon J, Fernandez-Calle P, Sandberg S, Özcürümez M, Bartlett WA, Coskun A, Carobene A, Perich C, Simon M, Marques F, et al. 2021. Clinical Chemistry. 67(1):256–264. doi:10.1093/clinchem/hvaa261.
Early Rule-Out Strategies in the Emergency Department Utilizing High-Sensitivity Cardiac Troponin Assays. Lopez-Ayala P, Boeddinghaus J, Koechlin L, Nestelberger T, Mueller C. 2020. Clinical Chemistry. 67(1):114–123. doi:10.1093/clinchem/hvaa226.
Differential associations of cardiac troponin T and cardiac troponin I with coronary artery pathology and dynamics in response to short-duration exercise. Tveit SH, Cwikiel J, Myhre PL, Omland T, Berge E, Seljeflot I, Flaa A. 2021. Clinical Biochemistry. 88:23–29. doi:10.1016/j.clinbiochem.2020.11.005.
Advances in point-of-care testing for cardiovascular diseases. Regan B, O’Kennedy R, Collins D. 2021. Advances in Clinical Chemistry.:1–70. doi:10.1016/bs.acc.2020.09.001.
Cardiac Myosin‐Binding Protein C to Diagnose Acute Myocardial Infarction in the Pre‐Hospital Setting. Kaier TE, Stengaard C, Marjot J, Sørensen JT, Alaour B, Stavropoulou‐Tatla S, Terkelsen CJ, Williams L, Thygesen K, Weber E, et al. 2019. Journal of the American Heart Association. 8(15). doi:10.1161/jaha.119.013152.
Clinical determinants of plasma cardiac biomarkers in patients with stable chest pain. Bing R, Henderson J, Hunter A, Williams MC, Moss AJ, Shah ASV, McAllister DA, Dweck MR, Newby DE, Mills NL, et al. 2019. Heart. 105(22):1748–1754. doi:10.1136/heartjnl-2019-314892.
Droplet digital PCR of serum miR-499, miR-21 and miR-208a for the detection of functionally relevant coronary artery disease. Hortmann M, Walter JE, Benning L, Follo M, Mayr RM, Honegger U, Robinson S, Stallmann D, Duerschmied D, Twerenbold R, et al. 2019. International Journal of Cardiology. 275:129–135. doi:10.1016/j.ijcard.2018.08.031.
High-sensitivity cardiac troponin T increases after stress echocardiography. Samaha E, Brown J, Brown F, Martinez SC, Scott M, Jaffe AS, Davila-Roman VG, Nagele P. 2019. Clinical Biochemistry. 63:18–23. doi:10.1016/j.clinbiochem.2018.11.013.
Clinical utility of circulating interleukin-6 concentrations in the detection of functionally relevant coronary artery disease. Walter J, Tanglay Y, du Fay de Lavallaz J, Strebel I, Boeddinghaus J, Twerenbold R, Doerflinger S, Puelacher C, Nestelberger T, Wussler D, et al. 2019. International Journal of Cardiology. 275:20–25. doi:10.1016/j.ijcard.2018.10.029.
DT‐02‐03: TARGET ENGAGEMENT IN AN AD TRIAL: CRENEZUMAB LOWERS Aβ OLIGOMER LEVELS IN CSF. Yang T, Dang Y, Ostaszewski B, Mengel D, Steffen V, Rabe C, Bittner T, Walsh DM, Selkoe DJ. 2006. Alzheimer’s & Dementia. 14(7S_Part_31). doi:10.1016/j.jalz.2018.07.012.
1086Derivation and validation of a 0/1h-algorithm to diagnose myocardial infarction using cardiac myosin-binding protein c - direct comparison to hs-cTnI. Kaier TE, Twerenbold R, Alaour B, Badertscher P, Puelacher C, Marjot J, Boeddinghaus J, Nestelberger T, Wildi K, Wussler D, et al. 2018. European Heart Journal. 39(suppl_1). doi:10.1093/eurheartj/ehy565.1086.
Screening for Cardiac Disease with Genetic Risk Scoring, Advanced ECG, Echocardiography, Protein Biomarkers and Metabolomics. Gladding P, Dugo C, Wynne Y, Semple H, Smith K, Shepherd P, Zarate E, Larsen P, Vilas-Boas S. 2018. Heart, Lung and Circulation. 27:S8. doi:10.1016/j.hlc.2018.05.117.
High-Sensitivity Cardiac Troponin I and the Diagnosis of Coronary Artery Disease in Patients With Suspected Angina Pectoris. Adamson PD, Hunter A, Madsen DM, Shah ASV, McAllister DA, Pawade TA, Williams MC, Berry C, Boon NA, Flather M, et al. 2018. Circulation: Cardiovascular Quality and Outcomes. 11(2). doi:10.1161/circoutcomes.117.004227.
Single‐Molecule Counting of High‐Sensitivity Troponin I in Patients Referred for Diagnostic Angiography: Results From the CASABLANCA (Catheter Sampled Blood Archive in Cardiovascular Diseases) Study. McCarthy CP, Ibrahim NE, Lyass A, Li Y, Gaggin HK, Simon ML, Mukai R, Gandhi P, Kelly N, Motiwala SR, et al. 2018. Journal of the American Heart Association. 7(6). doi:10.1161/jaha.117.007975.
Ultrasensitive label-free optical microfiber coupler biosensor for detection of cardiac troponin I based on interference turning point effect. Zhou W, Li K, Wei Y, Hao P, Chi M, Liu Y, Wu Y. 2018. Biosensors and Bioelectronics. 106:99–104. doi:10.1016/j.bios.2018.01.061.
CARDIAC TROPONIN I AND SUBCLINICAL CARDIOVASCULAR DISEASE. Joo E, Darabian S, Nozari Y, Vahoumeni R, Sheidaee N, Wade NB, Budoff M. 2018. Journal of the American College of Cardiology. 71(11):A130. doi:10.1016/s0735-1097(18)30671-5.
Prospective Validation of a Biomarker-Based Rule Out Strategy for Functionally Relevant Coronary Artery Disease. Walter JE, Honegger U, Puelacher C, Mueller D, Wagener M, Schaerli N, Strebel I, Twerenbold R, Boeddinghaus J, Nestelberger T, et al. 2018. Clinical Chemistry. 64(2):386–395. doi:10.1373/clinchem.2017.277210.
Comprehensive Age and Sex 99th Percentiles for a High-Sensitivity Cardiac Troponin I Assay. Estis J, Wu AHB, Todd J, Bishop J, Sandlund J, Kavsak PA. 2018. Clinical Chemistry. 64(2):398–399. doi:10.1373/clinchem.2017.276972.
Prevalence, predictors and clinical outcome of residual congestion in acute decompensated heart failure. Rubio-Gracia J, Demissei BG, ter Maaten JM, Cleland JG, O’Connor CM, Metra M, Ponikowski P, Teerlink JR, Cotter G, Davison BA, et al. 2018. International Journal of Cardiology. 258:185–191. doi:10.1016/j.ijcard.2018.01.067.
Quantifying the Release of Biomarkers of Myocardial Necrosis from Cardiac Myocytes and Intact Myocardium. Marjot J, Kaier TE, Martin ED, Reji SS, Copeland O, Iqbal M, Goodson B, Hamren S, Harding SE, Marber MS. 2017. Clinical Chemistry. 63(5):990–996. doi:10.1373/clinchem.2016.264648.
Can a Point-of-Care Troponin I Assay be as Good as a Central Laboratory Assay? A MIDAS Investigation. Peacock WF, Diercks D, Birkhahn R, Singer AJ, Hollander JE, Nowak R, Safdar B, Miller CD, Peberdy M, Counselman F, et al. 2016. Annals of Laboratory Medicine. 36(5):405–412. doi:10.3343/alm.2016.36.5.405.
The development and application of a high-sensitivity immunoassay for cardiac myosin–binding protein C. Marjot J, Liebetrau C, Goodson RJ, Kaier T, Weber E, Heseltine P, Marber MS. 2016. Translational Research. 170:17-25.e5. doi:10.1016/j.trsl.2015.11.008.
Longitudinal studies of cardiac troponin I concentrations in serum from male cynomolgus monkeys: resting values and effects of oral and intravenous dosing on biologic variability. Schultze AE, Anderson JM, Kern TG, Justus RW, Lee H-YC, Zieske LR, Goodson RJ, Florey SH. 2015. Veterinary Clinical Pathology. 44(3):465–471. doi:10.1111/vcp.12272.
Prognostic performance of a high-sensitivity assay for cardiac troponin I after non-ST elevation acute coronary syndrome: Analysis from MERLIN-TIMI 36. Bonaca MP, O’Malley RG, Murphy SA, Jarolim P, Conrad MJ, Braunwald E, Sabatine MS, Morrow DA. 2014. European Heart Journal: Acute Cardiovascular Care. 4(5):431–440. doi:10.1177/2048872614564081.
The utility of serum biomarkers to detect myocardial alterations induced by Imatinib in rats. Herman E, Knapton A, Zhang J, Estis J, Todd J, Lipshultz S. 2014. Pharmacology Research & Perspectives. 2(1). doi:10.1002/prp2.15.
Baseline Serum Cardiac Troponin I Concentrations in Sprague-Dawley, Spontaneous Hypertensive, Wistar, Wistar-Kyoto, and Fisher Rats as Determined with an Ultrasensitive Immunoassay. Herman E, Knapton A, Rosen E, Zhang J, Estis J, Agee SJ, Lu Q-A, Todd JA, Lipshultz SE. 2011. Toxicologic Pathology. 39(4):653–663. doi:10.1177/0192623311406931.
Defining the serum 99th percentile in a normal reference population measured by a high-sensitivity cardiac troponin I assay. Apple FS, Simpson PA, Murakami MM. 2010. Clinical Biochemistry. 43(12):1034–1036. doi:10.1016/j.clinbiochem.2010.05.014.
Assessment of the Toxicity of Hydralazine in the Rat Using an Ultrasensitive Flow-based Cardiac Troponin I Immunoassay.Mikaelian I, Coluccio D, Hirkaler GM, Downing JC, Rasmussen E, Todd J, Estis J, Lu QA, Nicklaus R. 2009. Toxicologic Pathology. 37(7):878–881. doi:10.1177/0192623309351894.
Ultrasensitive Cross-species Measurement of Cardiac Troponin-I Using the Erenna® Immunoassay System. Schultze AE, Konrad RJ, Credille KM, Lu QA, Todd J. 2008. Toxicologic Pathology. 36(6):777–782. doi:10.1177/0192623308322016.

General Applications

Ultra-sensitive AAV capsid detection by immunocapture-based qPCR following factor VIII gene transfer. Sandza K, Clark A, Koziol E, Akeefe H, Yang F, Holcomb J, Patton K, Hammon K, Mitchell N, Wong WY, et al. 2021. Gene Therapy. 29(1-2):94–105. doi:10.1038/s41434-021-00287-1.
The role of ligand-binding assay and LC–MS in the bioanalysis of complex protein and oligonucleotide therapeutics. Kotapati S, Deshpande M, Jashnani A, Thakkar D, Xu H, Dollinger G. 2021. Bioanalysis. 13(11):931–954. doi:10.4155/bio-2021-0009.
Quantitation of low abundant soluble biomarkers using high sensitivity Single Molecule Counting technology. Hwang J, Banerjee M, Venable AS, Walden Z, Jolly J, Zimmerman C, Adkisson E, Xiao Q. 2019. Methods. 158:69–76. doi:10.1016/j.ymeth.2018.10.018.
Standardized Immunomonitoring: Separating the Signals from the Noise. Duffy D. 2018. Trends in Biotechnology. 36(11):1107–1115. doi:10.1016/j.tibtech.2018.06.002.
Assay Formats: Recommendation for Best Practices and Harmonization from the Global Bioanalysis Consortium Harmonization Team. Dudal S, Baltrukonis D, Crisino R, Goyal MJ, Joyce A, Österlund K, Smeraglia J, Taniguchi Y, Yang J. 2013. The AAPS Journal. 16(2):194–205. doi:10.1208/s12248-013-9552-9.
Ultrasensitive Flow-based Immunoassays Using Single-Molecule Counting. Todd J, Freese B, Lu A, Held D, Morey J, Livingston R, Goix P. 2007. Clinical Chemistry. 53(11):1990–1995. doi:10.1373/clinchem.2007.091181.

Metabolism/Endocrinology

Removal of Epididymal Visceral Adipose Tissue Prevents Obesity-Induced Multi-organ Insulin Resistance in Male Mice. Franczyk MP, He M, Yoshino J. 2021. Journal of the Endocrine Society. 5(5). doi:10.1210/jendso/bvab024.

Cancer

GDF-15 Neutralization Alleviates Platinum-Based Chemotherapy-Induced Emesis, Anorexia, and Weight Loss in Mice and Nonhuman Primates. Breen DM, Kim H, Bennett D, Calle RA, Collins S, Esquejo RM, He T, Joaquim S, Joyce A, Lambert M, et al. 2020. Cell Metabolism. 32(6):938-950.e6. doi:10.1016/j.cmet.2020.10.023.

Kidney Injury

Variation in renal responses to exercise in the heat with progressive acclimatisation. Omassoli J, Hill NE, Woods DR, Delves SK, Fallowfield JL, Brett SJ, Wilson D, Corbett RW, Allsopp AJ, Stacey MJ. 2019.Journal of Science and Medicine in Sport. 22(9):1004–1009. doi:10.1016/j.jsams.2019.04.010.

What Is Single Molecule Counting (SMC®) Technology?An Overview of Ultrasensitive Immunoassay Technology

What Is SMC® Technology?

SMC® Technology Workflow

The steps in the SMC® Technology Workflow include: