Editorial Revisado por pares

Matrix effect in ligand-binding assay: the importance of evaluating emerging technologies

2014; Future Science Ltd; Volume: 6; Issue: 8 Linguagem: Inglês

10.4155/bio.14.39

ISSN

1757-6199

Autores

Rebecca M Crisino, Linlin Luo, Brian Geist, Jad Zoghbi, Franklin Spriggs,

Tópico(s)

Monoclonal and Polyclonal Antibodies Research

Resumo

BioanalysisVol. 6, No. 8 EditorialFree AccessMatrix effect in ligand-binding assay: the importance of evaluating emerging technologiesRebecca M Crisino, Linlin Luo, Brian Geist, Jad Zoghbi & Franklin SpriggsRebecca M Crisino* Author for correspondenceJanssen R&D, L.L.C., 200 Great Valley Parkway, Malvern, PA, USA. , Linlin LuoBristol Myers Squibb, Lawrenceville, NJ, USA, Brian GeistJanssen R&D, L.L.C., Spring House, PA, USA, Jad ZoghbiSanofi, Framingham, MA, USA & Franklin SpriggsPfizer, Andover, MA, USAPublished Online:16 May 2014https://doi.org/10.4155/bio.14.39AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInRedditEmail Keywords: emerging technologyimmunogenicityinnovationligand-binding assaymatrix effectmatrix interferencepharmacokinetictechnology evaluationThe Emergent Technologies Action Program Committee (ETAPC) is a group that was founded out of the Ligand Binding Assay Bioanalytical Focus Group. The ETAPC is comprised of experts from both North American and European bioanalytical companies, CROs, technology vendors and government agencies. The ETAPC's mission is to focus on identification and evaluation of new emerging technologies for biologics or novel approaches to existing technologies that will allow for a competitive advantage [1]. The Assay Interference team is one of the four working groups that make up the ETAPC and focuses its efforts on evaluating emerging technologies and new applications of existing technologies that will enable us to overcome specific and nonspecific interferences from matrix components to allow for the quantification of a biologic therapeutic, biomarkers and the detection of antidrug antibodies. The goal of this Editorial is to highlight the interferences that matrix can have on a PK or antidrug–antibody (ADA) assay, as well as give insight into a few technologies that have the potential to aid in reducing those interferences.Matrix effectsAddressing matrix effect issues is important during assay development of ligand-binding assays (LBAs). The 2001 US FDA Guidance for Industry: Bioanalytical Method Validation defined matrix effects as the "direct or indirect alteration or interference in response due to the presence of unintended analytes (for analysis) or other interfering substances in the sample" [2]. Matrix effects in LBAs are mainly caused by factors other than those intended to interact with the analyte of interest, such as lipids, ionic strength, pH, cations, viscosity, serum proteins, anticoagulants, proteases, binding proteins, autoantibodies and heterophilic antibodies [3]. The interaction of these biological components with reagents used in the assay poses challenges to accurately measure the analyte of interest, leading to misinterpretation of the PK, PD (biomarkers) and ADA profile. Due to the complexity and wide range of concentrations of biological components in sample matrix, there are no specific one-size-fits-all methods to overcome the matrix effect related issues.In PK and PD immunoassays, matrix interferences, such as nonspecific binding, may result in poor recovery of the true analyte concentrations. Among the many interfering biological components, endogenous proteins and pre-existing antibody interferences [4,5] have been well described. Specifically in the cases of heterophilic antibodies and autoantibodies, such as rheumatoid factors [6,7].Administration of biologic therapeutics may lead to development of ADAs. The existence of ADAs in matrix can impact the quantification of the therapeutic by forming ADA–drug immune complexes in immunoassays and results in underestimation of drug levels [8,9]. Therefore, ADA data should always be taken into consideration while evaluating the PK profile.Bridging ADA assays have been widely applied for immunogenicity assessment since they are generally sensitive, highly specific and relatively drug-tolerant methods. However, many factors can interfere with the reagents used in the bridging assay and lead to false negative or false positive ADA results. One such important factor present in dosed sample matrix is the circulating therapeutic as it can significantly interfere with ADA assays, potentially causing ADA false negatives. Thus, implementation of assays that can tolerate therapeutic drug concentrations is essential to reliably detect ADA [10]. One of the more effectively used methods to improve drug tolerance of ADA assays includes acid dissociation and a SPE with acid dissociation, but it could be time-consuming to develop and execute as well as introduce variability due to multiple steps [11–13]. Many other factors in sample matrix could generate false positive signals such as endogenous IgG or multimeric soluble targets [14–16]. Different strategies have been used to eliminate the high ADA false positive rates caused by soluble target proteins. For instance, monoclonal antibodies that specifically bind to the targets (but at a different site from the drug) and prevent therapeutic–target binding were used and successfully inhibited the target interference, while preserving the detection of ADAs [17,18]. Sample ultracentrifugation and solid-phase immunodepletion were also able to remove target interference without affecting the true ADA detection when the soluble target is present on cellular membrane fragments [18] or in circulation [19].Emerging technological solutionsThere are multiple ways to eliminate or reduce matrix interference; the most common method is to dilute the samples to a minimum required dilution using sample diluent while attempting to preserve needed sensitivity. Analyte extraction can also be used before analysis in the immunoassay [20]; however, sample dilution may result in loss of sensitivity and analyte extraction is not always practical for biologic therapeutics, making neither, suitable for certain assays. Therefore, it is essential to continuously identify and evaluate emerging technologies, or look to novel approaches of existing technologies that can alleviate interference problems. A variety of applications have shown promise for various LBA attributes, such as sensitivity or throughput, but few have tackled the issue of matrix effects.The technologies highlighted in this publication need to be investigated further in the context of interference. Their selection is based on vendor claims regarding the technology or platform of having proprietary components or general functionality that make them more tolerant to interferences. Following is a brief description of each of these emerging technologies: ▪ The Singulex® Erenna® platform, although not known for its high sample throughput, offers absolute sensitivity. Immunoassays on this platform are commonly used to detect low levels (pg/ml or fg/ml) of analyte, in most cases an improvement over other LBA formats. The technology uses magnetic micro particles to increase binding surface area, a proprietary elution and concentration step and an advanced fluorescent digital detection [21];▪ Quanterix's proprietary SiMoa™ technology (single molecule array) is based upon the isolation of individual immune complexes on paramagnetic beads using standard ELISA reagents and has the ability to trap single molecules in femtoliter-sized wells, allowing for a 'digital' readout of each individual bead. The manufacturer claims that the improved and maintained sensitivity observed in various matrices supports the specificity of the platform and lack of interference [22];▪ ANP Technologies' NPX4000 Nanoparticles have the ability to reduce interfering matrix components through the process of extraction with gold nanoparticles. The NPX4000 nanoparticles can be used for a variety of capture functions, including endogenous target, soluble target or other interfering factor [23];▪ SQI Diagnostic's Ig PLEX™ and Genalyte's Maverick™ technology both utilized a multiplexed approach whereby an analyte or immunoglobulin isotype is spotted in multiple locations on an array. The Ig PLEX system utilizes differentially flourophore-labeled secondary antibodies to quantitate the isotype or immunoglobulin class [24];▪ The Maverick detection system is a lab-on-a-chip design that uses the absence of specific color light waves to detect the binding of proteins to the sensor, which is functionalized with the antibody or antigen of your choice [25].Both the Ig PLEX and Maverick technologies were designed to allow for real-time measurement of multiplexed assays, but a peripheral benefit is the ability of these technologies to reduce matrix interference because of the minute volume of sample that comes into contact with the capture reagent, thus eliminating the opportunity for nonspecific binding. Because the rate of diffusion is shortened due to the small sample volume, the nonspecific binding matrix components simply do not have the opportunity to interfere [24,25].SummaryThe effects of endogenous matrix components on the quantification of therapeutics and biomarkers, and the impact of circulating therapeutics on the detection of ADAs varies significantly for each drug program. While often there are simple remedies to the interference, such as increasing the minimum required dilution or changing the sample dilution buffer, there are a handful of emerging technologies that have the potential to expand beyond the tradition remedies and reduce the impact of matrix interference in LBAs. The ETAPC and the Assay Inference team will continue to evaluate technologies that focus on improving drug tolerance and reducing matrix interferences. All ETAPC sub-teams are working together to draft a series of White Papers to provide recommendations on emerging technologies that would have a positive impact in the areas of assay sensitivity, real-time measurement, high-throughput and multiplexing, and assay interferences. The ETAPC welcomes any feedback with past or current experiences and evaluations on any of these areas.Financial & competing interests disclosureThe authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.References1 Mora J, Fraser S, Garofolo F. Emerging technology evaluation in the biotherapeutics bioanalytical space: a collaborative affair. AAPS Newsmagazine, 14–18 May (2013).Google Scholar2 US Department of Health and Human Services, US FDA, Center for Drug Evaluation and Research. Guidance for Industry: Bioanalytical Method Validation, Draft Guidance. FDA, Rockville, MD, USA (2013).Google Scholar3 Tate J, Ward G. Interferences in immunoassay. Clin. Biochem. Rev.25,105–120 (2004).Medline, Google Scholar4 Li J, Cheadle N, Schantz A, Shankar G. A lateral flow immunochromatographic method for anti-drug antibody detection in human serum. Presented at: 2013 American Association of Pharmaceutical Scientists National Biotechnology Conference. San Diego, CA, USA, 20–22 May 2013.Google Scholar5 Qu Q, Rathi A, Gorovits B et al. Development of a clinical assay for measuring anti-drug antibodies against a monoclonal antibody drug: overcoming soluble target interference. Presented at: 2013 American Association of Pharmaceutical Scientists National Biotechnology Conference. San Diego, CA, USA, 20–22 May 2013.Google Scholar6 Baird CL, Tan R, Fischer CJ, Victry KD, Zangar RC, Rodland KD. Reducing heterophilic antibody interference in immunoassay using single-chain antibodies. Anal. Biochem.419,333–335 (2011).Crossref, Medline, CAS, Google Scholar7 Preissner CM, Dodge LA, O'Kane DJ, Singh RJ, Grebe SK. Prevalence of heterophilic antibody interference in eight automated tumor marker immunoassays. Clin. Chem.51(1),208–210, (2005).Crossref, Medline, CAS, Google Scholar8 Chirmule N, Jawa V, Meibohm B. Immunogenicity to therapeutic proteins: impact on PK/PD and efficacy. AAPS J.14(2),296–302 (2012).Crossref, Medline, CAS, Google Scholar9 Kelley M, Ahene AB, Gorovits B et al. Theoretical considerations and practical approaches to address the effect of anti-drug antibody (ADA) on quantification of biotherapeutics in circulation. AAPS J.15(3),646–658, 2013.Crossref, Medline, Google Scholar10 Wang YM, Fang L, Zhou L, Wang J, Ahn HY. A survey of applications of biological products for drug interference of immunogenicity assays. Pharm. Res.29,3384–3392, (2012).Crossref, Medline, CAS, Google Scholar11 Patton A, Mullenix MC, Swanson SJ, Koren E. An acid dissociation bridging ELISA for detection of antibodies directed against therapeutic proteins in the presence of antigen. J. Immunol. Methods304(1–2),189–195 (2005).Crossref, Medline, CAS, Google Scholar12 Smith HW, Butterfield A, Sun D. Detection of antibodies against therapeutic proteins in the presence of residual therapeutic protein using a solid-phase extraction with acid dissociation (SPEAD) sample treatment prior to ELISA. Regul. Toxicol. Pharmacol.49(3),230–237 (2007).Crossref, Medline, CAS, Google Scholar13 Mikulskis A, Yeung D, Subramanyam M, Amaravadi L. Solution ELISA as a platform of choice for development of robust, drug tolerant immunogenicity assays in support of drug development. J. Immunol. Methods365(1–2),38–49 (2011).Crossref, Medline, CAS, Google Scholar14 Koren E, Smith HW, Shores E et al. Recommendations on risk-based strategies for detection and characterization of antibodies against biotechnology products. J. Immunol. Methods333,1–9 (2008).Crossref, Medline, CAS, Google Scholar15 Araujo J, Zocher M, Wallace K, Peng K, Fisher SK. Increased rheumatoid factor interference observed during immunogenicity assessment of an Fc-engineered therapeutic antibody. J. Pharm. Biomed. Anal.55,1041–1049 (2011).Crossref, Medline, CAS, Google Scholar16 Carrasco-Triguero M, Mahood C, Milojic-Blair M et al. Overcoming soluble target interference in an anti-therapeutic antibody screening assay for an antibody-drug conjugate conjugate therapeutic. Bioanalysis4(16),2013–2026 (2012).Link, CAS, Google Scholar17 Zhong ZD, Dinnogen S, Hokom M, Ray C, Weinreich D, Swanson SJ, Chirmule N. Identificaton and inhibition of drug target interference in immunogenicity assays. J. Immunol. Methods355,21–28 (2010).Crossref, Medline, CAS, Google Scholar18 Chen K, Page JG, Schwartz AM et al. False-positive immunogenicity responses are caused by CD20+ B cell membrane fragments in an anti-ofatumumab antibody bridging assay. J. Immunol. Methods394,22–31 (2013).Crossref, Medline, CAS, Google Scholar19 Qu Q, Raithi A, Gorovits B et al. Development of a clinical assay for measuring anti-drug antibodies against a monoclonal antibody drug: overcoming soluble target interference. Presented at: The 2013 American Association of Pharmaceutical Scientists National Biotech Conference. San Diego, CA, USA, 20–22 May 2013.Google Scholar20 Kelley M, DeSilva B. Key elements of bioanalytical method validation for macromolecules. AAPS J.9,E156–E163 (2007).Crossref, Medline, Google Scholar21 Singluex® Erenna® technology. www.singulex.com/technology.htmlGoogle Scholar22 Quanterix's SiMoA™ technology. www.quanterix.com/technology/simoa-scienceGoogle Scholar23 ANP Technologies, NPX4000 Nanoparticles. http://anptinc.com/index.php?option=com_content&view=article&id=154&Itemid=122Google Scholar24 SQI Diagnostics' IgPLEX™ technology. www.sqidiagnostics.com/technologyGoogle Scholar25 Genalyte's Maverick technology. http://genalyte.com/maverickGoogle ScholarFiguresReferencesRelatedDetailsCited ByA particle-based microfluidic fluorescent lateral flow assay for rapid and sensitive detection of SARS-CoV-2 antibodySensors and Actuators B: Chemical, Vol. 394An effective pre-treatment method for eliminating interference by serum albumin for analysis of anti-rHSA antibodies1 January 2023 | Analytical Methods, Vol. 15, No. 9Nanocellulose aerogel inserts for quantitative lateral flow immunoassaysBiosensors and Bioelectronics, Vol. 192The role of tumor-stroma interactions on desmoplasia and tumorigenicity within a microengineered 3D platformBiomaterials, Vol. 247Application of aptamers as molecular recognition elements in lateral flow assaysAnalytical Biochemistry, Vol. 593Overcoming disease-specific matrix effect in a clinical pharmacokinetic assay using a microfluidic immunoassay technologyKathi Williams, Rich Erickson & Saloumeh Kadkhodayan Fischer2 August 2017 | Bioanalysis, Vol. 9, No. 16A breakthrough novel method to resolve the drug and target interference problem in immunogenicity assaysJournal of Immunological Methods, Vol. 426Automation of ELISAs & evaluation of emerging technologies for high-throughput quantitation of protein impuritiesPharmaceutical Bioprocessing, Vol. 3, No. 7Choosing the right bioanalytical assay platform(s) to support the PK assessment of protein biotherapeutic programsShannon D Chilewski & Hao Jiang5 June 2015 | Bioanalysis, Vol. 7, No. 10Matrix interference in ligand-binding assays: challenge or solution?Binodh DeSilva & Fabio Garofolo16 May 2014 | Bioanalysis, Vol. 6, No. 8 Vol. 6, No. 8 STAY CONNECTED Metrics History Published online 16 May 2014 Published in print April 2014 Information© Future Science LtdKeywordsemerging technologyimmunogenicityinnovationligand-binding assaymatrix effectmatrix interferencepharmacokinetictechnology evaluationFinancial & competing interests disclosureThe authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.PDF download

Referência(s)
Altmetric
PlumX