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Interference in immunoassays to support therapeutic antibody development in preclinical and clinical studies
During preclinical and clinical studies, immunoassays are used to measure the concentration of the therapeutic antibody, anti-drug antibodies and soluble protein biomarkers. The reliability of these assays is crucial since the results are routinely used for safety assessment and dose selection. Furthermore, soluble protein biomarkers can provide information about target engagement, proof of mechanism, proof of principle and prediction of response. Study samples mostly consist of complex matrices that can exhibit considerable interference, resulting in inaccurate measurements. This perspective discusses the source of interference and strategies to mitigate or eliminate interference in immunoassays used during preclinical and clinical drug development of drugs with a focus on the development of therapeutic antibodies.
Therapeutic antibodies represent a large proportion of approved biotherapeutics. Since the first approval of the murine antibody muronomab-CD3 in 1986 to the glyco engineered humanized obinutuzumab in 2013, 36 therapeutic antibodies were approved for use in humans. An essential part of therapeutic antibody development is the characterization of the toxicokinetics/ pharmacokinetics (PK), pharmacodynamics (PD) and immunogenicity. PK and PD results from animal studies can be incorporated into PK/PD models and used to guide first-in-human dose selection. Then an iterative PK/PD modeling and simulation process begins to refine the dose from early to late phase of clinical development. Reliable PK and PD data is a prerequisite for successful PK/PD modeling and simulation. Immunogenicity can influence PK to a large degree and, in the clinic, is an important part of safety assessment. In addition, accurate assessment of appropriate biomarkers in clinical studies can provide valuable information for target engagement, proof-of-mechanism and proof-of-principle, as well as for selecting the patient population who is most likely to respond to a therapy. Immunoassay is a commonly used assay format to measure thera-
10.4155/BIO.14.127 © 2014 Future Science Ltd
Martin Schwickart*,1, Inna Vainshtein1, Rozanne Lee1, Amy Schneider1 & Meina Liang1 1 Department of Clinical Pharmacology & DMPK, MedImmune, 319 North Bernardo Avenue, Mountain View, CA 94043, USA *Author for correspondence: Tel.: +1 510 265 5443 Fax: +1 510 265 5402 [email protected]
peutic antibody, anti-drug antibody (ADA) and soluble protein biomarkers. Biological samples for these assessments are complex matrices and contain various components that can significantly impact the accuracy of analyte quantification. Interference has been discussed previously in excellent reviews with a focus on the clinical laboratory setting [1–3] . Many assays used during drug development are custom developed and less characterized. This perspective will focus on interferences encountered in immunoassays used for the measurement of therapeutic antibody concentration, ADA and soluble protein biomarkers, including free and total target assays, as well as mitigation strategies for interferences. What is interference? Definitions of interference have been proposed previously [1] as “the effect of a substance present in the sample that alters the correct value of the result, usually expressed as concentration or activity, for an analyte”. Interference can be distinguished by analyte-dependent and analyte-independent interference. Analyte-dependent interference includes all factors that directly affect detection of the analyte. Analyte-independent interference can cause signals in absence of
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Key Terms Interference: Leads to observed values being different from actual values. Interference can originate from substances, assay procedures, reagents and sample collection/processing. Matrix interference: Any matrix constituent that leads to the observed analyte concentration being different from the actual analyte concentration. The molecular identity of matrix interference is often not known.
analyte or inhibits the assay reagents directly. Interference can lead to both artificially increased or decreased results. Matrix interference is often referred to as ‘unspecific’. Assays are designed to detect a certain analyte and any component generating a signal or inhibiting the analyte signal can be defined as unspecific. However, often, after critical review of the assay and the biology of the analyte, it becomes clear that the observed interference is not at all surprising and is caused by a defined biomolecule. It is therefore imperative for the bioanalytical scientist to critically review existing literature, previous studies and specificity of the reagents to define the specificity of the assay accordingly. Interference and specificity are related, and an absolute specific assay should not be susceptible to any matrix interference. However, biological matrices are complex. Extensive knowledge of the assay system and the analyte biology are not always sufficient to prevent the occurrence of interference. Similarly to western blots that rarely detect only one band, most immunoassays are not always specific to one analyte. Figure 1 illustrates different types of interference. Often, the molecular nature of interference remains unknown. The most used method to mitigate interference is dilution of the sample. This method is so widely used that most analytical scientists tend to dilute all samples and would not trust values from undiluted samples. A type of interference that deserves special attention are antibodies in the sample [3] . Heterophilic antibodies have in general broad reactivity and low affinity and are able to crosslink capture and detection antibody leading to falsely high results [4] . Human-anti-animal antibodies, are not uncommon and are assumed to be of higher affinity [5] . As many assay reagents contain mouse monoclonal antibodies, human anti-mouse antibodies are of special relevance. Clinical assays used today are still somewhat susceptible to heterophilic antibodies and clinician should consider strategies to the potential damage caused by incorrect results from immunoassays [6] . Rheumatoid factor, human antibodies against the Fc region of human IgG has a similar effect and can inhibit binding of the analyte or crosslink assay reagents, especially if the assay reagents are of human origin (e.g., ADA assays with therapeutic antibodies as assay reagents).
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Interference can also originate from a change or even from degradation of the analyte or assay reagents, which leads to a decrease in assay signal. An increase in assay signal occurs when assay reagents can bind to the surface of the assay plate or similar surfaces in other assay platforms and increase the assay signal artificially. Lastly, the analyte itself can interfere when either the sample collection or the sample procession procedure introduces additional analyte that is not reflective of the analyte concentration in the biofluid of interest (see Figure 1 for illustration). Similarly, very high concentration of analyte can inhibit the assay signal through the so-called hook effect. Manifestations of matrix interference during assay development & in-study results In immunoassays developed to support preclinical and clinical studies, most assay interference can be evaluated before study samples are tested, and this process of analyzing and mitigating interference is an integral part of assay development. The presence of interference is typically revealed by a few simple experiments. Parallelism/linearity & recovery of spiked analyte
Interference is often revealed by testing serial dilution of sample. [7] . Here, interference will most likely cause a change in the dilution-adjusted concentration between different sample dilutions. In most assays, this so-called lack of parallelism often disappears at higher dilutions, indicating that interference was caused by a matrix component. In case non-parallelism persists at high dilutions, interference is most likely due to a high concentration of interfering matrix component, the matrix component binding with high affinity or a difference between the standard curve material and the endogenous analyte. Strictly speaking, the latter case is not interference, but rather indicates that the standard curve material is not suitable to quantitate the endogenous analyte, in such case, the assay is quasi-quantitative [8] . When a defined amount of analyte is spiked into the sample, an assay without interference should be able to quantify the amount that was spiked. Matrix interference often leads to under-recovery of the spiked amount. In case the endogenous analyte is different from the spiked analyte (i.e., recombinant vs endogenous protein), recovery by itself can only serve as an indication of interference. Blocking of interference & specific interaction
If the assay signal changes after addition of blocking reagents (e.g., blocking buffers or heterophile blocking reagent), matrix interference originating from the interaction of assay reagents with each other or solid support is likely to be present. Blocking reagents
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Interference resulting in assay signal decrease Binding protein masking epitope for capture reagent (or detection) reagent
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Interference resulting in assay signal increase Detection reagent binding to surface
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Figure 1. Matrix interference in immunoassay. HAMA: Human antimouse antibodies; Int.: Interfering molecule; RF: Rheumatoid factor.
together with dilution studies has been used to screen for interference [9] . Unspecific signal might be revealed by blocking the analyte with specific reagents which should lead to complete loss of specific assay signal. If the assay signal or a portion still persists after blocking the analyte, interference is present. Evaluation of study results
Even after careful assay development, interference can occur in study samples, sometimes caused by changes
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in the matrix induced by administration of the thera peutic antibody or co-medication. Indicators of interference are results inconsistent with the expected effect of drug administration, especially when comparing PK, PD and immunogenicity data in individuals during the course of a study. Discordant results between related measurements are also a strong indicator of interference. However, conclusions about the validity of study results should be drawn with much caution. Unexpected results might very well be
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Perspective Schwickart, Vainshtein, Lee, Schneider & Liang valid. It is always prudent to experimentally confirm suspected interference in study results. In the following section, we will discuss interference observed in soluble protein biomarker assays, therapeutic antibody assays and ADA assays. Soluble protein biomarkers Assays to quantitate soluble protein biomarkers have become a cornerstone of drug development and provide important information for assessment of safety, efficacy, PD and of the mechanism of action of the drug in development. Soluble proteins in circulation (blood) or urine are easily accessible and are routinely measured in diagnostic assays in the clinic, or to predict patient response to a drug (e.g., periostin [10]). Interference in diagnostic assays is acknowledged in the field, and reliance on only one test result can lead to misdiagnosis. Prominently, false-positive results caused most likely by heterophilic antibody interference in a diagnostic human chorionic gonadotropin assay led to unnecessary therapeutic intervention, including surgery and chemotherapy [11] . The focus and depth of assay development for assays used for study support are dependent on the intended purpose, which led to the term ‘fit-for-purpose method development’. The publication of general guidelines for biomarker assay development and validation has helped tremendously to structure biomarker assay development and validation [8,12,13] . We focus here on interference that can influence results to large degrees and might or might not become apparent when following the published experimental guidelines. Processing & collection
Nonspecific release of analyte from blood cells can occur during collection or processing of samples involving blood-derived matrices. If this occurs with the soluble protein biomarker, it can cause falsely elevated levels of the analyte as well as increased variability of results. For example, when measuring growth factors, such as PDGF or VEGF, care should be taken in selecting the most appropriate sample type in order to avoid nonspecific activation of platelets and release of protein into the sample during processing [14,15] . For these analytes, plasma instead of serum is a more appropriate sample matrix. Similarly, it has been shown that room temperature storage of samples during pre-analytical processing can significantly alter IL-8 concentrations in the blood sample. Incubation at room temperature causes additional IL-8 production, resulting in falsely increased results for IL-8 in blood lysate samples. Keeping samples on ice, rather than at room temperature, immediately after sample collection reduces this effect [16] . Partial lysis of red blood cells (hemolysis) is not
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uncommon in serum or plasma samples, and consequently causes measurement of false values for analytes that are present at high concentrations in red blood cells (e.g., aspartate transaminase) [17] . Protein conformation can impact detection by assay reagents, and this can be induced by components in the assay buffer. For example, chelation of calcium from plasma samples has been shown to impact measurement of the calcium-binding protein S100A12 [18] . Interferences like these could be mitigated by selection of assay reagents that detect the analyte independently of cation binding, or spiking the sample with cations, or selection of sample preparation that does not cause metal chelation (e.g., sodium heparin plasma or serum). In some cases, the physical properties of the sample can make pipetting difficult or introduce interference during testing. For example, sputum is of such high viscosity that accurate pipetting is close to impossible. Sputum is routinely treated with the mucoly tic agent dithiothreitol to decrease overall viscosity; consideration must also be given to the dithiothreitol concentration and potential effect on the integrity of the immunoassay reagents and the analyte. Likewise, high turbidity caused by insoluble precipitates in some plasma or urine samples can introduce interference or high background. Precipitates can be reduced by centrifugation or filtration. Approaches such as these can reduce matrix interferences and minimize inaccuracies introduced by mechanical errors. Specificity
As mentioned before, misinterpretation of the assay specificity is a major cause of matrix interference. A soluble protein biomarker can have different highly homologous family members, isoforms or precursor proteins. If the protein, structurally related to the actual analyte, is recognized by both the capture and detection reagents in the immunoassay system, it will cause falsely high results of the soluble protein biomarker (e.g., a commercially available assay to PDGF-BB detected also PDGF-AB at 10% of its nominal concentration. Periostin, a biomarker of eosinophilic airway inflammation, has multiple isoforms and specificity towards the isoforms was clearly defined during assay development, illustrating a careful investigation of assay specificity [19] . Some calcitonin assays, which are used for diagnosis of medullary thyroid carcinoma, seem to partially detect also pro-calcitonin, which has no diagnostic value for medullary thyroid carcinoma [20] . If only the capture reagent (or detection reagent in homogenous assays) binds to the analyte-related protein, this can result in falsely low measurement of the analyte. Interference in this case
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can be understood and managed by knowing the biological system (i.e., identity of potential cross-reacting factors and their relative concentration and affinity), selecting reagents that are as specific as possible to the analyte of interest; and dilution of samples to possibly reduce levels of the related proteins below the detection limit of the assay. Another possible approach is depletion or neutralization of interfering isoforms or family member protein(s) in the system by addition of a specific reagent, which only suppresses the related protein but not the analyte. Binding proteins
The presence of a soluble receptor or other proteins that bind directly to the analyte can cause alteration of the assay signal as they may prevent or enhance interaction with the capture or detection reagent in the immunoassay. For example, IL-6 can form a complex with IL-6R and gp130 [21] , and depending on assay reagents, different fractions of IL-6 can be detected. Interference caused by soluble receptors or binding proteins can be reduced by selection of immunoassay reagents that bind to the analyte at sites that do not compete with interfering proteins in the sample. Dilution can reduce interference especially if the interfering interaction is of low affinity. If not feasible, other approaches may involve disruption of the analyte and binding proteins or soluble receptor by, for example, acid-dissociation, as demonstrated in an assay that dissociated insulin-like growth factor from insulinlike growth factor binding protein [22] . Addition of an inhibitor of the binding protein before neutralization might further minimize the interference. The pH in the sample can be adjusted to dissociate the binding proteins from the analyte. Such sample pretreatments should be critically evaluated regarding their impact on the immunoassay reagents or the epitopes of the analyte. Because this type of matrix interference might be difficult to completely eliminate, it is most important to know the specificity of the immunoassay reagents, as well as the various complexes of the analyte being measured in order to interpret results accordingly. Endogenous antibodies
As discussed earlier, heterophilic and anti-animal antibodies can bind to the assay reagents that are mostly antibodies from animal origin and either lead to artificially high or low results. Human anti-mouse antibodies, the most common type of human anti-animal antibodies, can bind to capture and/or detection reagents in a sandwich immunoassay, depending on the reagent species. Binding to both reagents can lead to bridging of reagents and false-positive results for the specific analyte being measured; binding to one of the
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two reagents may disrupt analyte binding and cause false-negative results. The most common approach for reducing interference from heterophilic antibodies or human anti-animal antibodies is addition of animal immunoglobulin (purified or in normal animal sera) or other commercially available reagents (e.g., hetero phile blocking reagent), which have specific activity to heterophilic antibodies [2,4] . Also antibodies to protein biomarkers (autoantibodies) can lead to falsely low or high signals. For example, autoantibodies to thyroid hormone, present in diseases such as Hashimoto’s thyroiditis, bound to the fluorescein-T4 (thyroid hormone) tracer in a competitive immunoassay for thyroxine, leading to falsely low thyroxine measurements [23] . Homogenous assays might be more amenable to this type of interference than sequential assays. Selection of two different species reagents for capture and detection antibodies in the immunoassay may also be useful to minimize possible bridging affects with human antianimal antibodies. Another approach is to apply sufficient dilution of the sample to remove interference. Removal of antibodies by, for example, protein G [24] or disruption of heterophilic antibody interactions by detergent [25] , has also been reported. These and other sample-altering procedures may be problematic in that they could result in unintended removal of analyte, or affect the assay reagent. Other sample constituents
Historically, clinical methods measuring absorbance or light scattering were affected by samples with high levels of lipids (lipidemia) or bilirubin (icterus) [17] . Immunoassays are considered to be generally unaffected. However, b-human chorionic gonadotropin and IgG measurements by a commercial assay system were found to be decreased by bilirubin [26] . Interference can originate from unsuspected sources. For example, proteases in pancreatic cyst fluid were found to degrade both the analyte and reagent antibodies [27] . Proteases were also suspected to be responsible for interference with IL-5 detection in sputum samples since addition of protease inhibitor led to increased detection of IL-5 [28] . Interestingly, after therapeutic doses, biotin in the sample was found to lead to massive interference in several assays [29] . Free soluble target & total soluble target assays Free and total target measurement is the most commonly used target engagement biomarkers for therapeutic antibodies targeting soluble antigens. Both readouts can also be used as a surrogate target engagement biomarker for antibodies targeting membrane antigen if a soluble form of target is shed into circulation or sol-
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Key Term Free soluble target assay: Assay to measure target engagement. This assay is particularly impacted by interference from the assay procedure itself since the dynamic equilibrium between free- and drug-bound target changes during sample incubation.
uble isoforms of the membrane-bound target might be present in circulation. Suppression of free target by antibody drugs is a direct measurement of target engagement. Total target is often accumulated in circulation following antibody treatment due to decrease in target clearance upon binding to therapeutic antibody. Due to this relationship between target binding and clearance, total target indirectly demonstrates target engagement. Furthermore, the free target suppression profile can be derived by PK/PD simulation from the total target accumulation results. Free target assays and total target assays present unique challenges in addition to the challenges discussed for soluble protein biomarkers. Free soluble target assays
Most free soluble target assays are based on the principle that the capture reagent competes with the thera peutic antibody for binding to the target. The captured target is then detected with a labeled detection reagent. Determination of specificity of the assay and knowledge about the biology of the target is crucial to develop reliable free target assays. The expected interference in this type of assay is identical to the previously discussed biomarker assays. In addition, free target assays are subject to interference related to specificity of the assay, dilution of the sample, unintentional dissociation of the therapeutic antibody/target complex, incubation time and capture reagent concentration. In free target assays, the target might not only bind to the therapeutic antibody but also interact with endogenous soluble receptors or binding proteins, which can, in some cases, bind to the target with affinities similar to the therapeutic antibody. Furthermore, different isoforms of the target might or might not bind to the therapeutic antibody or be detected by the assay. It is crucial to define which fraction of target is detected by the assay. It can either be the therapeutic antibody-unbound or the binding protein- and therapeutic antibody-unbound fraction. In both cases, it might be necessary to evaluate changes in level of the binding protein during the study to interpret data appropriately. Furthermore, it is crucial to know whether the binding protein inhibits the target and whether the binding protein competes with the drug for binding to the target. As some targets have multiple binding proteins, it is useful to use in vitro binding experiments to focus on binding proteins with impact on free target results.
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Many immunoassays rely on dilution of the sample to minimize matrix interference from unknown sources. In the case of free target assays, sample dilution changes the dynamic equilibrium between free target, target bound to the drug and also target bound to circulating binding proteins or soluble receptors. There are two solutions to this issue: • Development of an assay that does not require sample dilution; • Sample dilution and appropriate reporting of results. Quantification of free target in undiluted samples is always preferred, if feasible. It is a difficult task to eliminate matrix interference in undiluted samples. Biological matrices are complex and plasma and serum have very high total protein concentrations [30] . One way to measure undiluted samples is to use a buffer for the standard curve that is similar to the sample matrix. This would result in the same matrix effect to both standard curve and sample and thus results would not be affected by matrix. This approach is only successful if the matrix interference is relatively constant between individual samples. The most accurate way to generate such assay matrix is to deplete the sample matrix of analyte. This is limited by the technical challenge to deplete all analyte and to avoid leakage of the depleting reagent into the matrix. The use of serum or plasma from other species (e.g., fetal bovine serum) is often sufficient if analyte orthologs do not interfere due to binding to the capture reagent or also to the detection reagent in homogenous assays. From an operational perspective, undiluted serum or plasma samples are viscous and need to be pipetted and diluted with extra care to ensure accuracy and precision of the assay. However, it is also possible to report free analyte concentrations accurately from diluted samples. In a twocomponent system where affinity of the therapeutic antibody and abundance of therapeutic antibody and target are known, one can estimate the expected influence on concentration in the diluted sample. The influence of equilibrium perturbation has been studied in much detail for free hormone assays [31,32] . Figure 2 shows a simple simulation of sample dilution for different target/therapeutic antibody ratios. For a typical antibody with an affinity of 0.1 nM and a target concentration of 5 nM, reporting of the non-dilution-adjusted concentration is quite accurate for target/therapeutic antibody binding site (complementarity determining regions) ratios of 1:3 or higher. Higher dilutions have little effect on the non-dilution-adjusted concentration for samples with a high ratio between the complementarity determining region and target. This simple simulation can be
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Free target (% of total target)
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1:100 1:30 1:10 1:3 1:1
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Sample dilution factor Figure 2. Effect of sample dilution on the concentration of free target at different target-antibody ratios. Assumptions: dissociation constant (KD) = 0.1 nM, analyte concentration in the sample is at 5 nM, and the complementarity determining region of the therapeutic antibody is present at equimolar, three-, ten-, 30- or 100-fold molar excess over the target.
performed for any therapeutic antibody and should provide a good guide on how to report diluted samples. The reporting strategy can be validated with in vitro experiments to mimic different scenarios. However, non-dilution-adjusted reporting will not be accurate for samples collected at the end of the wash-out period when the concentration of antibody and target become similar. In our example, at a molar ratio to 1:1, non-dilution adjusted reporting is not accurate. In studies, objective criteria have to be defined to limit non-dilution adjusted reporting to time points where reporting of non-dilution adjusted concentrations is adequate. Furthermore, the assay reagents introduce an error as the dynamic equilibrium between free and bound target is shifted due to the presence of an additional binding partner: the capture reagent. This so-called observer effect explains the physical principle that the act of observing will alter the phenomenon that is being observed. This principle, although universally applicable, has little relevance for soluble protein biomarker assays but applies very much to free target assays. Here, the effect leads to over-estimation of free target and is especially relevant for samples with high total target concentrations and low concentration of free target.
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Total target often accumulates in circulation following antibody treatment due to decrease in target clearance upon binding to antibody. For example, several assays exist to detect free IgE after therapy with the anti-IgE therapeutic antibody omalizumab and clinical decision are based on the concentration of free IgE. Some assays appear to overestimate free IgE which may be partially attributable to the effects described above [33] . The optimal free assay would be constructed with minimal capture reagent and a short incubation time to minimize the perturbation of the equilibrium. However, this approach decreases precision, robustness and dynamic range of the assay. It is therefore advisable to investigate the extent of the observer effect and find a healthy balance between accuracy of free target determination and assay practicality. ADA interferes with free target assays if the capture reagent is identical or very similar to the therapeutic antibody. ADA in this case not only binds to the thera peutic antibody but also binds and blocks the capture reagent so that little or no free target can bind to the capture reagent, leading to significant under-estimation of free target concentrations. This effect can lead to the false impression that target is suppressed even in
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Perspective Schwickart, Vainshtein, Lee, Schneider & Liang absence of therapeutic antibody. For this reason, using the therapeutic antibody as capture reagent should be avoided. However, especially early in development, appropriate reagents might not be available. A free assay with therapeutic antibody capture might suffice if the therapeutic antibody has a very low incidence of immunogenicity or the assay is used for a single-dose study where the therapeutic antibody is washed out before the immune systems starts producing ADA. Alternatively, free target data from ADA-positive individuals might be excluded from analysis. Also, in preclinical studies, sample can be depleted of animal antibodies including potential ADA. As most modern therapeutic antibodies are fully human, they would not be depleted. Total soluble target assays
The therapeutic antibody interferes frequently with assays measuring the total soluble target. Even if the epitope of neither capture- nor detection-antibody overlaps with the epitope of the therapeutic antibody, interference is still frequently observed. The therapeutic antibody might either change the conformation of the target or crosslink two target molecules, resulting in an over- or under-estimation of total target concentration. To circumvent this effect, excess therapeutic antibody can be added to samples to convert all free soluble targets to drug–target complexes. The addition of excess drug also allows using a target–drug complex assay system to measure total target. In such case, ADA might interfere by binding to the therapeutic antibody and inhibit detection or amplify the specific signal by forming multimeric complexes. Salimi-Moosavi et al. demonstrated that either alkaline or acid/guanidine treatment of study samples can irreversible denaturate the therapeutic antibody, while the target regains immunoreactivity after neutralization [34] . This sample pretreatment effectively eliminated all interference from the therapeutic antibody; it would be interesting to see if this approach is broadly applicable for other protein targets and therapeutic antibodies. Another elegant approach only used one noncompeting antibody and the therapeutic antibody as reagents [35] . Here, the noncompeting antibody was used to capture the target, free or bound to therapeutic antibody. The target together with bound therapeutic antibodies where then eluted with acid, neutralized and coated onto a polystyrene plate. The coated target was then detected with a labeled therapeutic antibody. Therapeutic antibody assays Immunoassays are commonly used for quantification of therapeutic antibody concentrations in biological
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matrices. Depending on the format, the assay can measure concentrations of either free drug or total drug. Free drug refers to therapeutic antibody not bound to the target. Total drug refers to free plus target-bound drug; for a review, see [36] . As the PK data is of central importance, regulatory guidelines [37] and industry consensus publications [38–40] have contributed recommendation regarding assay validation including some aspects of assay interference. Measurement of free therapeutic antibody typically uses antigen or neutralizing anti-idiotypic antibody (anti-ID) as capture. The detection antibody can be neutralizing anti-ID, non-neutralizing anti-ID, anti-human IgG, anti-human antibody to a specific isotype (e.g., anti-human IgG2 specific) or anti-framework mutations of the therapeutic antibody. Total therapeutic antibody can be captured and detected by non-neutralizing anti-ID, anti-human IgG, anti-human antibody to a specific isotype or anti-framework mutations of the therapeutic antibody. Non-neutralizing anti-IDs are rarely available since anti-ID campaigns most often yield many neutralizing anti-IDs but few if any non-neutralizing anti-IDs. Free therapeutic antibody quantification is technically challenging [41] , especially when soluble targets are present at high levels in the sample. Many matrix components can significantly alter the levels of the soluble target or affect the binding of drug to the soluble target, resulting in an observed change in the free drug concentration. While these components are much more likely to interfere with the quantification of soluble target discussed earlier, it may also introduce inaccuracy in free therapeutic antibody measurement if the target levels are high. Preparation of the sample is of special significance when quantifying antibody–drug conjugates (ADCs), since ADCs can undergo biotransformation in the collected samples or in vivo, complicating the already complex ADC bioanalysis [42] . Even monoclonal antibody assays can be affected by the sample preparation method. For example, the use of EDTA as anti-coagulant will chelate cations, such as Ca 2+ and Mg2+, and thus will impact accurate determination of free therapeutic antibody concentrations if these cations are necessary for drug–target binding. Suboptimal procedures (as discussed earlier in the biomarker section) can cause release of soluble target from cells during sample collection and preparation, leading to artificially high level of target in the sample and thus underestimation of free therapeutic antibody levels. To mitigate these potential assay interferences, sample collection procedures and assay conditions should be optimized for every therapeutic antibody assay. As
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discussed earlier, serum preparation can lead to release of proteins stored in platelets which is avoided by the use of plasma. In addition, stabilizing condition, such as temperature, can be implemented to minimize protein release from cells during sample collection. Acid dissociation treatment followed by neutralization in presence of assays reagents or maintaining the sample mildly acidic during the assay procedure has shown to be effective in reducing interference originating from the target [43,44] . For free therapeutic antibody assays, assay conditions, such as incubation time, capture reagent concentration and minimal required dilution, should be optimized in order to minimize the dissociation of drug from its target. This is especially important for the drugs that have relatively low affinity for its target and that soluble target concentration in circulation is relatively high. Dilution linearity and sample stability should be evaluated in the study population to account for the impact of changes in drug target level on the accuracy of free drug assessment. When antigen capture is used, high levels of binding protein or soluble receptor can saturate the capture reagents, resulting in underestimation of free drug concentration. The use of neutralizing anti-ID instead of drug target as a capture minimizes this concern. ADA in the sample is a source of matrix interference. ADA that competes with the capture antibody (or also detection antibody in homogenous assays) for binding to the drug will result in underestimation of therapeutic antibody concentration. Noncompeting ADA can crosslink therapeutic antibody molecules to form large complexes, which could also impact the accurate determination of the drug levels. A comparative evaluation of PK, PD and ADA will reveal if this interference occurs in a study and results can be interpreted accordingly. Similarly to biomarker assays, heterophilic antibodies and human anti-animal antibodies in the matrices are common sources of interferences for immunoassays and can be mitigated with the same methods described earlier. Human immunoglobulins in human matrices can cause significant background if anti-human antibody is used as capture or detection. Isotype-specific anti-human antibody can be used to replace pan anti-human antibody and to reduce the interference. It is even more effective to use antibodies against mutations on antibody framework of the drug molecule if present. ADA assays Biopharmaceuticals and even fully human thera peutic antibodies have the potential to generate ADA (also called anti-therapeutic antibodies) that can cause undesired effects ranging from loss of drug exposure, loss of efficacy, to serious adverse events [45,46] .
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Immuno genicity assessment is an important part of the safety assessment during clinical studies and ADA is typically tested in a tiered approach to detect, confirm and characterize ADA [47] . ADA assays are semi-quantitative, as these assays lack a standard calibrator. Positivity is defined by an assay signal above the assay cut point, determined by statistical analysis of drug naive negative samples [48] . Detailed regulatory recommendation on immunogenicity assay development were published [49] . ADA to therapeutic antibodies are mostly measured with immunoassays, although other methods, such as surface plasmon resonance by BIAcore [50,51] or homogenous mobility shift assays [52] have been used for ADA determinations. The majority of ADA immunoassays employ a bridging assay format, where ADA crosslink (bridge) two drug molecules conjugated with two different labels, one binds to a solid phase, while the other is conjugated to a tag that generates a signal (e.g., HRP). Direct binding immunoassays, where the therapeutic antibody is the capture reagent and the detection reagent detects the Fc-portion of the ADA, are used less frequently for antibody therapeutics [53] . The most common interference for ADA detection is the therapeutic antibody itself. Drug in the sample binds to ADA and prevents ADA to form complex with assay reagents. The ability of the assay to detect ADA in presence of drug, called drug tolerance, is recommended by regulators to be addressed during assay validation of clinical and nonclinical ADA assays [45] . Drug interference can be mitigated by collecting samples for ADA testing at time points when concentration of the therapeutic is expected to be low, for example, during the drug wash-out phase. In some cases, drug tolerance can be improved by acid dissociation of the drug–ADA complex, followed by neutralization in presence of the assay reagents [54–56] . Sample dilution and use of an assay with high sensitivity are effective to enhance the drug tolerance. Direct binding immunoassay that capture ADA with the drug and detect the ADA via its Fc-region might be less susceptible to drug interference. In this format ADA can be detected if one arm is available for binding to the drug capture, whereas binding to both arms is required to detect ADA in a bridging format. Wu et al. described a drug-tolerant assay using such direct binding format for detection of drug-specific ADAs of the IgE isotype [57] . Drug interference might be completely eliminated with assays that extract total antibody and then detect copurified biotherapeutics in order to quantitate ADA. Neubert et al. have demonstrated the feasibility of this approach with protein G extraction following by detection of the copurified therapeutic with LC–MS [58] .
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Perspective Schwickart, Vainshtein, Lee, Schneider & Liang Drug–target present in sample matrix may also interfere with ADA detection and lead to either false-positive or -negative results. False-positive results can arise in the presence of multimeric soluble target that bridges capture and detection reagents. Interestingly, cell membrane fragments containing CD20 were reported to cause matrix interference in an ADA assay for of atumumab [59] . False-negative results can be due to binding of the soluble target to the capture and/or detection antibody and thereby preventing detection of neutralizing ADA. Pretreatment with blocking antibodies to the target or blocking with target-binding proteins as well as immunodepletion of the target can eliminate this type of interference as demonstrated during development of an ADA assay for ranibizumab [60] . A high-affinity antitarget antibody in the ADA assay for the anti-angiopoitin peptibody AMG386 enabled sensitive detection of ADA in presence of high target concentrations [61,62] . Other methods, such as BIAcore, can be even more susceptible to target interference. Klakamp et al. [51] showed false-negative readouts from ADA-containing samples tested using surface-immobilized drug in the presence of the circulating target which could be mitigated by a noncompeting antitarget antibody. Although one would expect that drug-naive individuals are free of ADA, pre-existing antibodies are detected sometimes before dosing [63] . It is important to point out that pre-existing antibodies are not interference and might bind anywhere on the therapeutic antibody. For example, pre-existing neutralizing ADA to panitumumab was detected and confirmed [64] . Authors reported that these cross-reactive antibodies altered neither PK of the drug nor its safety profile. Still, the presence of pre-existing ADA always complicates the assay and interpretation of results. The determination of titer and specificity helps to understand the contribution of pre-existing antibodies to the post-dose ADA incidence. The clinical relevance of pre-existing antibodies is illustrated by cetuximab, where pre-existing IgE antibodies were associated with severe hypersensitivity reactions [65] . Pre-existing ADAs might be expected when a therapeutic protein contains an immunogenic domain of a naturally occurring protein, to which majority of human individuals might be previously exposed. Pre-existing ADA were observed in clinical studies of recombinant therapeutic immunotoxins, anti-CD3-diptheria toxin [66] and anti-CD22 Pseudomonas exotoxin A [67] . Rheumatoid factor (RF), common in rheumatoid arthritis patients, is antibodies against the Fc region of IgG, mostly of the IgM isotype [68] . RF binds with low affinity and is not expected to produce a positive signal in ADA testing. However, therapeutic antibodies with engineered Fc might cause in a higher affinity to RF, resulting in positive signals in ADA assays. Araujo et al.
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demonstrated that RF caused a positive signal at predose and, pretreatment of the samples with anti-human IgM antibodies decreased the effect from RF [69] . As this approach, might compromise the detection of ADA of the IgM isotype, the authors screened samples with and without anti-IgM antibodies and monitored increase in titers during treatment. Conclusion & future perspective The bioanalysis of soluble protein biomarkers, therapeutic antibodies, and ADA is an integral part of drug development, and each analyte has its own challenges. The most effective method to avoid matrix interference is a solid knowledge of target biology and the analyte itself with a focus on specificity of the assay. Technology may also play a major role to prevent or mitigate assay interference. Dilution is in many cases an effective tool to minimize interference, and the highest feasible dilution is limited by the sensitivity of the assay. High-sensitivity platforms can help to work with higher dilutions, providing an effective tool to minimize interference originating from the matrix. Improvement in separation and purification technologies might be quite effective to separate the analyte from interfering factors. In ADA assay, for example, effective quantitative separation of the ADA from the therapeutic antibody would solve the issue of drug tolerance. MS in combination with LC has become a powerful quantitative method that finds more and more application in bioanalysis of therapeutic proteins (especially antibody–drug conjugates) and biomarkers. Interference appears to be of much less concern compared with immunoassays. However, MS is extremely specific. While this can be extremely helpful in completely eliminating interference, it may also tremendously complicate bioanalysis if the analytes are biologically identical. There might be many cases where MS detects a mix of many slightly different chemical analytes whereas an immunoassay only detects one analyte. We expect MS, and especially LC–MS/MS to become more and more important for bioanalysis. We are curious how the tremendous specificity of MS methods will limit or accelerate its adoption in the analysis of different biological analytes. Financial & competing interest disclosure All authors are employees of MedImmune and own stock in AstraZeneca. The authors have no other 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 apart from those disclosed. No writing assistance was utilized in the production of this manuscript.
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Executive summary What is interference in immunoassays? • Misinterpretation of assay specificity is often a source of observed interference. The specificity of the assay needs to be critically reviewed to define the actual assay analyte correctly. • Matrix interference leads to a decrease or increase in observed concentration when matrix components interact with the assay reagents. In addition, matrix components can degrade the assay reagents.
Manifestations of matrix interference during assay development & in-study results. • Parallelism/linearity experiments, recovery of spiked analyte and specificity evaluation will reveal most of the analyte-dependent interference. • Discordant individual pharmacokinetics, anti-drug antibodies (ADA) and biomarker results reveals interference after review of study results.
Soluble protein biomarkers • Sample processing and collection can change the analyte concentration. For example, some growth factors are released from platelets during serum preparation. Collection of plasma instead prevents this type of interference. • Isoforms, precursors, related proteins and binding proteins can lead to over-or under-estimation of analyte concentration. Determination of correct assay specificity as well as depletion or blocking of interfering components can mitigate unexpected results. • Endogenous antibodies can lead to falsely high results by crosslinking assay reagent or to falsely low results by blocking the analyte. Selection of assay reagents, dilution, depletion and blocking can minimize interference.
Free soluble target assays • Dissociation of target form the therapeutic antibody–target complex during sample preparation and assay procedure leads to intrinsic interference that can only be minimized but not entirely eliminated. • Assay reagent concentration, assay reagent affinity and incubation time need to be optimized to minimize dissociation of drug-bound target and thus to build an accurate free target assay. • Although dilution is in principle detrimental to the accuracy of free target assays, results from diluted samples can be accurate determined by applying reporting criteria.
Therapeutic antibody assays (pharmacokinetic & toxicokinetic assays) • Free and total therapeutic antibody assays are similar unless the level of soluble target is high. • Accurate free therapeutic antibody assays are technically challenging.
ADA assays • The therapeutic itself will always interfere with the assay, and ‘drug tolerance’ needs to be established during validation. • Target in the sample can lead to false-positive and -negative results and can be blocked with binding proteins or with specific antibodies to the target. • Pre-existing antibodies are not interference but can mask ADA emerging during the study.
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Interference in immunoassays to support therapeutic antibody development in preclinical and clinical studies
During preclinical and clinical studies, immunoassays are used to measure the concentration of the therapeutic antibody, anti-drug antibodies and soluble protein biomarkers. The reliability of these assays is crucial since the results are routinely used for safety assessment and dose selection. Furthermore, soluble protein biomarkers can provide information about target engagement, proof of mechanism, proof of principle and prediction of response. Study samples mostly consist of complex matrices that can exhibit considerable interference, resulting in inaccurate measurements. This perspective discusses the source of interference and strategies to mitigate or eliminate interference in immunoassays used during preclinical and clinical drug development of drugs with a focus on the development of therapeutic antibodies.
Therapeutic antibodies represent a large proportion of approved biotherapeutics. Since the first approval of the murine antibody muronomab-CD3 in 1986 to the glyco engineered humanized obinutuzumab in 2013, 36 therapeutic antibodies were approved for use in humans. An essential part of therapeutic antibody development is the characterization of the toxicokinetics/ pharmacokinetics (PK), pharmacodynamics (PD) and immunogenicity. PK and PD results from animal studies can be incorporated into PK/PD models and used to guide first-in-human dose selection. Then an iterative PK/PD modeling and simulation process begins to refine the dose from early to late phase of clinical development. Reliable PK and PD data is a prerequisite for successful PK/PD modeling and simulation. Immunogenicity can influence PK to a large degree and, in the clinic, is an important part of safety assessment. In addition, accurate assessment of appropriate biomarkers in clinical studies can provide valuable information for target engagement, proof-of-mechanism and proof-of-principle, as well as for selecting the patient population who is most likely to respond to a therapy. Immunoassay is a commonly used assay format to measure thera-
10.4155/BIO.14.127 © 2014 Future Science Ltd
Martin Schwickart*,1, Inna Vainshtein1, Rozanne Lee1, Amy Schneider1 & Meina Liang1 1 Department of Clinical Pharmacology & DMPK, MedImmune, 319 North Bernardo Avenue, Mountain View, CA 94043, USA *Author for correspondence: Tel.: +1 510 265 5443 Fax: +1 510 265 5402 [email protected]
peutic antibody, anti-drug antibody (ADA) and soluble protein biomarkers. Biological samples for these assessments are complex matrices and contain various components that can significantly impact the accuracy of analyte quantification. Interference has been discussed previously in excellent reviews with a focus on the clinical laboratory setting [1–3] . Many assays used during drug development are custom developed and less characterized. This perspective will focus on interferences encountered in immunoassays used for the measurement of therapeutic antibody concentration, ADA and soluble protein biomarkers, including free and total target assays, as well as mitigation strategies for interferences. What is interference? Definitions of interference have been proposed previously [1] as “the effect of a substance present in the sample that alters the correct value of the result, usually expressed as concentration or activity, for an analyte”. Interference can be distinguished by analyte-dependent and analyte-independent interference. Analyte-dependent interference includes all factors that directly affect detection of the analyte. Analyte-independent interference can cause signals in absence of
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Key Terms Interference: Leads to observed values being different from actual values. Interference can originate from substances, assay procedures, reagents and sample collection/processing. Matrix interference: Any matrix constituent that leads to the observed analyte concentration being different from the actual analyte concentration. The molecular identity of matrix interference is often not known.
analyte or inhibits the assay reagents directly. Interference can lead to both artificially increased or decreased results. Matrix interference is often referred to as ‘unspecific’. Assays are designed to detect a certain analyte and any component generating a signal or inhibiting the analyte signal can be defined as unspecific. However, often, after critical review of the assay and the biology of the analyte, it becomes clear that the observed interference is not at all surprising and is caused by a defined biomolecule. It is therefore imperative for the bioanalytical scientist to critically review existing literature, previous studies and specificity of the reagents to define the specificity of the assay accordingly. Interference and specificity are related, and an absolute specific assay should not be susceptible to any matrix interference. However, biological matrices are complex. Extensive knowledge of the assay system and the analyte biology are not always sufficient to prevent the occurrence of interference. Similarly to western blots that rarely detect only one band, most immunoassays are not always specific to one analyte. Figure 1 illustrates different types of interference. Often, the molecular nature of interference remains unknown. The most used method to mitigate interference is dilution of the sample. This method is so widely used that most analytical scientists tend to dilute all samples and would not trust values from undiluted samples. A type of interference that deserves special attention are antibodies in the sample [3] . Heterophilic antibodies have in general broad reactivity and low affinity and are able to crosslink capture and detection antibody leading to falsely high results [4] . Human-anti-animal antibodies, are not uncommon and are assumed to be of higher affinity [5] . As many assay reagents contain mouse monoclonal antibodies, human anti-mouse antibodies are of special relevance. Clinical assays used today are still somewhat susceptible to heterophilic antibodies and clinician should consider strategies to the potential damage caused by incorrect results from immunoassays [6] . Rheumatoid factor, human antibodies against the Fc region of human IgG has a similar effect and can inhibit binding of the analyte or crosslink assay reagents, especially if the assay reagents are of human origin (e.g., ADA assays with therapeutic antibodies as assay reagents).
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Interference can also originate from a change or even from degradation of the analyte or assay reagents, which leads to a decrease in assay signal. An increase in assay signal occurs when assay reagents can bind to the surface of the assay plate or similar surfaces in other assay platforms and increase the assay signal artificially. Lastly, the analyte itself can interfere when either the sample collection or the sample procession procedure introduces additional analyte that is not reflective of the analyte concentration in the biofluid of interest (see Figure 1 for illustration). Similarly, very high concentration of analyte can inhibit the assay signal through the so-called hook effect. Manifestations of matrix interference during assay development & in-study results In immunoassays developed to support preclinical and clinical studies, most assay interference can be evaluated before study samples are tested, and this process of analyzing and mitigating interference is an integral part of assay development. The presence of interference is typically revealed by a few simple experiments. Parallelism/linearity & recovery of spiked analyte
Interference is often revealed by testing serial dilution of sample. [7] . Here, interference will most likely cause a change in the dilution-adjusted concentration between different sample dilutions. In most assays, this so-called lack of parallelism often disappears at higher dilutions, indicating that interference was caused by a matrix component. In case non-parallelism persists at high dilutions, interference is most likely due to a high concentration of interfering matrix component, the matrix component binding with high affinity or a difference between the standard curve material and the endogenous analyte. Strictly speaking, the latter case is not interference, but rather indicates that the standard curve material is not suitable to quantitate the endogenous analyte, in such case, the assay is quasi-quantitative [8] . When a defined amount of analyte is spiked into the sample, an assay without interference should be able to quantify the amount that was spiked. Matrix interference often leads to under-recovery of the spiked amount. In case the endogenous analyte is different from the spiked analyte (i.e., recombinant vs endogenous protein), recovery by itself can only serve as an indication of interference. Blocking of interference & specific interaction
If the assay signal changes after addition of blocking reagents (e.g., blocking buffers or heterophile blocking reagent), matrix interference originating from the interaction of assay reagents with each other or solid support is likely to be present. Blocking reagents
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No interference
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Interference resulting in assay signal decrease Binding protein masking epitope for capture reagent (or detection) reagent
Blocking of capture reagent (or detection reagent)
Induction of degradation, modification or conformational change of analyte or reagents
Analyte Analyte
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Int.
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Interference resulting in assay signal increase Detection reagent binding to surface
Matrix component similiar to analyte (e.g., homologs and related proteins)
Antibodies in sample crosslinking capture and detection reagent (e.g., heterophilic antibodies, HAMA, RF)
Contamination with analyte originating from sample collection or sample processing
Int.
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Int. Analyte
Int.
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Figure 1. Matrix interference in immunoassay. HAMA: Human antimouse antibodies; Int.: Interfering molecule; RF: Rheumatoid factor.
together with dilution studies has been used to screen for interference [9] . Unspecific signal might be revealed by blocking the analyte with specific reagents which should lead to complete loss of specific assay signal. If the assay signal or a portion still persists after blocking the analyte, interference is present. Evaluation of study results
Even after careful assay development, interference can occur in study samples, sometimes caused by changes
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in the matrix induced by administration of the thera peutic antibody or co-medication. Indicators of interference are results inconsistent with the expected effect of drug administration, especially when comparing PK, PD and immunogenicity data in individuals during the course of a study. Discordant results between related measurements are also a strong indicator of interference. However, conclusions about the validity of study results should be drawn with much caution. Unexpected results might very well be
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Perspective Schwickart, Vainshtein, Lee, Schneider & Liang valid. It is always prudent to experimentally confirm suspected interference in study results. In the following section, we will discuss interference observed in soluble protein biomarker assays, therapeutic antibody assays and ADA assays. Soluble protein biomarkers Assays to quantitate soluble protein biomarkers have become a cornerstone of drug development and provide important information for assessment of safety, efficacy, PD and of the mechanism of action of the drug in development. Soluble proteins in circulation (blood) or urine are easily accessible and are routinely measured in diagnostic assays in the clinic, or to predict patient response to a drug (e.g., periostin [10]). Interference in diagnostic assays is acknowledged in the field, and reliance on only one test result can lead to misdiagnosis. Prominently, false-positive results caused most likely by heterophilic antibody interference in a diagnostic human chorionic gonadotropin assay led to unnecessary therapeutic intervention, including surgery and chemotherapy [11] . The focus and depth of assay development for assays used for study support are dependent on the intended purpose, which led to the term ‘fit-for-purpose method development’. The publication of general guidelines for biomarker assay development and validation has helped tremendously to structure biomarker assay development and validation [8,12,13] . We focus here on interference that can influence results to large degrees and might or might not become apparent when following the published experimental guidelines. Processing & collection
Nonspecific release of analyte from blood cells can occur during collection or processing of samples involving blood-derived matrices. If this occurs with the soluble protein biomarker, it can cause falsely elevated levels of the analyte as well as increased variability of results. For example, when measuring growth factors, such as PDGF or VEGF, care should be taken in selecting the most appropriate sample type in order to avoid nonspecific activation of platelets and release of protein into the sample during processing [14,15] . For these analytes, plasma instead of serum is a more appropriate sample matrix. Similarly, it has been shown that room temperature storage of samples during pre-analytical processing can significantly alter IL-8 concentrations in the blood sample. Incubation at room temperature causes additional IL-8 production, resulting in falsely increased results for IL-8 in blood lysate samples. Keeping samples on ice, rather than at room temperature, immediately after sample collection reduces this effect [16] . Partial lysis of red blood cells (hemolysis) is not
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uncommon in serum or plasma samples, and consequently causes measurement of false values for analytes that are present at high concentrations in red blood cells (e.g., aspartate transaminase) [17] . Protein conformation can impact detection by assay reagents, and this can be induced by components in the assay buffer. For example, chelation of calcium from plasma samples has been shown to impact measurement of the calcium-binding protein S100A12 [18] . Interferences like these could be mitigated by selection of assay reagents that detect the analyte independently of cation binding, or spiking the sample with cations, or selection of sample preparation that does not cause metal chelation (e.g., sodium heparin plasma or serum). In some cases, the physical properties of the sample can make pipetting difficult or introduce interference during testing. For example, sputum is of such high viscosity that accurate pipetting is close to impossible. Sputum is routinely treated with the mucoly tic agent dithiothreitol to decrease overall viscosity; consideration must also be given to the dithiothreitol concentration and potential effect on the integrity of the immunoassay reagents and the analyte. Likewise, high turbidity caused by insoluble precipitates in some plasma or urine samples can introduce interference or high background. Precipitates can be reduced by centrifugation or filtration. Approaches such as these can reduce matrix interferences and minimize inaccuracies introduced by mechanical errors. Specificity
As mentioned before, misinterpretation of the assay specificity is a major cause of matrix interference. A soluble protein biomarker can have different highly homologous family members, isoforms or precursor proteins. If the protein, structurally related to the actual analyte, is recognized by both the capture and detection reagents in the immunoassay system, it will cause falsely high results of the soluble protein biomarker (e.g., a commercially available assay to PDGF-BB detected also PDGF-AB at 10% of its nominal concentration. Periostin, a biomarker of eosinophilic airway inflammation, has multiple isoforms and specificity towards the isoforms was clearly defined during assay development, illustrating a careful investigation of assay specificity [19] . Some calcitonin assays, which are used for diagnosis of medullary thyroid carcinoma, seem to partially detect also pro-calcitonin, which has no diagnostic value for medullary thyroid carcinoma [20] . If only the capture reagent (or detection reagent in homogenous assays) binds to the analyte-related protein, this can result in falsely low measurement of the analyte. Interference in this case
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Interference in immunoassays to support therapeutic antibody development in preclinical & clinical studies
can be understood and managed by knowing the biological system (i.e., identity of potential cross-reacting factors and their relative concentration and affinity), selecting reagents that are as specific as possible to the analyte of interest; and dilution of samples to possibly reduce levels of the related proteins below the detection limit of the assay. Another possible approach is depletion or neutralization of interfering isoforms or family member protein(s) in the system by addition of a specific reagent, which only suppresses the related protein but not the analyte. Binding proteins
The presence of a soluble receptor or other proteins that bind directly to the analyte can cause alteration of the assay signal as they may prevent or enhance interaction with the capture or detection reagent in the immunoassay. For example, IL-6 can form a complex with IL-6R and gp130 [21] , and depending on assay reagents, different fractions of IL-6 can be detected. Interference caused by soluble receptors or binding proteins can be reduced by selection of immunoassay reagents that bind to the analyte at sites that do not compete with interfering proteins in the sample. Dilution can reduce interference especially if the interfering interaction is of low affinity. If not feasible, other approaches may involve disruption of the analyte and binding proteins or soluble receptor by, for example, acid-dissociation, as demonstrated in an assay that dissociated insulin-like growth factor from insulinlike growth factor binding protein [22] . Addition of an inhibitor of the binding protein before neutralization might further minimize the interference. The pH in the sample can be adjusted to dissociate the binding proteins from the analyte. Such sample pretreatments should be critically evaluated regarding their impact on the immunoassay reagents or the epitopes of the analyte. Because this type of matrix interference might be difficult to completely eliminate, it is most important to know the specificity of the immunoassay reagents, as well as the various complexes of the analyte being measured in order to interpret results accordingly. Endogenous antibodies
As discussed earlier, heterophilic and anti-animal antibodies can bind to the assay reagents that are mostly antibodies from animal origin and either lead to artificially high or low results. Human anti-mouse antibodies, the most common type of human anti-animal antibodies, can bind to capture and/or detection reagents in a sandwich immunoassay, depending on the reagent species. Binding to both reagents can lead to bridging of reagents and false-positive results for the specific analyte being measured; binding to one of the
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Perspective
two reagents may disrupt analyte binding and cause false-negative results. The most common approach for reducing interference from heterophilic antibodies or human anti-animal antibodies is addition of animal immunoglobulin (purified or in normal animal sera) or other commercially available reagents (e.g., hetero phile blocking reagent), which have specific activity to heterophilic antibodies [2,4] . Also antibodies to protein biomarkers (autoantibodies) can lead to falsely low or high signals. For example, autoantibodies to thyroid hormone, present in diseases such as Hashimoto’s thyroiditis, bound to the fluorescein-T4 (thyroid hormone) tracer in a competitive immunoassay for thyroxine, leading to falsely low thyroxine measurements [23] . Homogenous assays might be more amenable to this type of interference than sequential assays. Selection of two different species reagents for capture and detection antibodies in the immunoassay may also be useful to minimize possible bridging affects with human antianimal antibodies. Another approach is to apply sufficient dilution of the sample to remove interference. Removal of antibodies by, for example, protein G [24] or disruption of heterophilic antibody interactions by detergent [25] , has also been reported. These and other sample-altering procedures may be problematic in that they could result in unintended removal of analyte, or affect the assay reagent. Other sample constituents
Historically, clinical methods measuring absorbance or light scattering were affected by samples with high levels of lipids (lipidemia) or bilirubin (icterus) [17] . Immunoassays are considered to be generally unaffected. However, b-human chorionic gonadotropin and IgG measurements by a commercial assay system were found to be decreased by bilirubin [26] . Interference can originate from unsuspected sources. For example, proteases in pancreatic cyst fluid were found to degrade both the analyte and reagent antibodies [27] . Proteases were also suspected to be responsible for interference with IL-5 detection in sputum samples since addition of protease inhibitor led to increased detection of IL-5 [28] . Interestingly, after therapeutic doses, biotin in the sample was found to lead to massive interference in several assays [29] . Free soluble target & total soluble target assays Free and total target measurement is the most commonly used target engagement biomarkers for therapeutic antibodies targeting soluble antigens. Both readouts can also be used as a surrogate target engagement biomarker for antibodies targeting membrane antigen if a soluble form of target is shed into circulation or sol-
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Key Term Free soluble target assay: Assay to measure target engagement. This assay is particularly impacted by interference from the assay procedure itself since the dynamic equilibrium between free- and drug-bound target changes during sample incubation.
uble isoforms of the membrane-bound target might be present in circulation. Suppression of free target by antibody drugs is a direct measurement of target engagement. Total target is often accumulated in circulation following antibody treatment due to decrease in target clearance upon binding to therapeutic antibody. Due to this relationship between target binding and clearance, total target indirectly demonstrates target engagement. Furthermore, the free target suppression profile can be derived by PK/PD simulation from the total target accumulation results. Free target assays and total target assays present unique challenges in addition to the challenges discussed for soluble protein biomarkers. Free soluble target assays
Most free soluble target assays are based on the principle that the capture reagent competes with the thera peutic antibody for binding to the target. The captured target is then detected with a labeled detection reagent. Determination of specificity of the assay and knowledge about the biology of the target is crucial to develop reliable free target assays. The expected interference in this type of assay is identical to the previously discussed biomarker assays. In addition, free target assays are subject to interference related to specificity of the assay, dilution of the sample, unintentional dissociation of the therapeutic antibody/target complex, incubation time and capture reagent concentration. In free target assays, the target might not only bind to the therapeutic antibody but also interact with endogenous soluble receptors or binding proteins, which can, in some cases, bind to the target with affinities similar to the therapeutic antibody. Furthermore, different isoforms of the target might or might not bind to the therapeutic antibody or be detected by the assay. It is crucial to define which fraction of target is detected by the assay. It can either be the therapeutic antibody-unbound or the binding protein- and therapeutic antibody-unbound fraction. In both cases, it might be necessary to evaluate changes in level of the binding protein during the study to interpret data appropriately. Furthermore, it is crucial to know whether the binding protein inhibits the target and whether the binding protein competes with the drug for binding to the target. As some targets have multiple binding proteins, it is useful to use in vitro binding experiments to focus on binding proteins with impact on free target results.
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Many immunoassays rely on dilution of the sample to minimize matrix interference from unknown sources. In the case of free target assays, sample dilution changes the dynamic equilibrium between free target, target bound to the drug and also target bound to circulating binding proteins or soluble receptors. There are two solutions to this issue: • Development of an assay that does not require sample dilution; • Sample dilution and appropriate reporting of results. Quantification of free target in undiluted samples is always preferred, if feasible. It is a difficult task to eliminate matrix interference in undiluted samples. Biological matrices are complex and plasma and serum have very high total protein concentrations [30] . One way to measure undiluted samples is to use a buffer for the standard curve that is similar to the sample matrix. This would result in the same matrix effect to both standard curve and sample and thus results would not be affected by matrix. This approach is only successful if the matrix interference is relatively constant between individual samples. The most accurate way to generate such assay matrix is to deplete the sample matrix of analyte. This is limited by the technical challenge to deplete all analyte and to avoid leakage of the depleting reagent into the matrix. The use of serum or plasma from other species (e.g., fetal bovine serum) is often sufficient if analyte orthologs do not interfere due to binding to the capture reagent or also to the detection reagent in homogenous assays. From an operational perspective, undiluted serum or plasma samples are viscous and need to be pipetted and diluted with extra care to ensure accuracy and precision of the assay. However, it is also possible to report free analyte concentrations accurately from diluted samples. In a twocomponent system where affinity of the therapeutic antibody and abundance of therapeutic antibody and target are known, one can estimate the expected influence on concentration in the diluted sample. The influence of equilibrium perturbation has been studied in much detail for free hormone assays [31,32] . Figure 2 shows a simple simulation of sample dilution for different target/therapeutic antibody ratios. For a typical antibody with an affinity of 0.1 nM and a target concentration of 5 nM, reporting of the non-dilution-adjusted concentration is quite accurate for target/therapeutic antibody binding site (complementarity determining regions) ratios of 1:3 or higher. Higher dilutions have little effect on the non-dilution-adjusted concentration for samples with a high ratio between the complementarity determining region and target. This simple simulation can be
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Interference in immunoassays to support therapeutic antibody development in preclinical & clinical studies
Free target (% of total target)
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1:100 1:30 1:10 1:3 1:1
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Sample dilution factor Figure 2. Effect of sample dilution on the concentration of free target at different target-antibody ratios. Assumptions: dissociation constant (KD) = 0.1 nM, analyte concentration in the sample is at 5 nM, and the complementarity determining region of the therapeutic antibody is present at equimolar, three-, ten-, 30- or 100-fold molar excess over the target.
performed for any therapeutic antibody and should provide a good guide on how to report diluted samples. The reporting strategy can be validated with in vitro experiments to mimic different scenarios. However, non-dilution-adjusted reporting will not be accurate for samples collected at the end of the wash-out period when the concentration of antibody and target become similar. In our example, at a molar ratio to 1:1, non-dilution adjusted reporting is not accurate. In studies, objective criteria have to be defined to limit non-dilution adjusted reporting to time points where reporting of non-dilution adjusted concentrations is adequate. Furthermore, the assay reagents introduce an error as the dynamic equilibrium between free and bound target is shifted due to the presence of an additional binding partner: the capture reagent. This so-called observer effect explains the physical principle that the act of observing will alter the phenomenon that is being observed. This principle, although universally applicable, has little relevance for soluble protein biomarker assays but applies very much to free target assays. Here, the effect leads to over-estimation of free target and is especially relevant for samples with high total target concentrations and low concentration of free target.
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Total target often accumulates in circulation following antibody treatment due to decrease in target clearance upon binding to antibody. For example, several assays exist to detect free IgE after therapy with the anti-IgE therapeutic antibody omalizumab and clinical decision are based on the concentration of free IgE. Some assays appear to overestimate free IgE which may be partially attributable to the effects described above [33] . The optimal free assay would be constructed with minimal capture reagent and a short incubation time to minimize the perturbation of the equilibrium. However, this approach decreases precision, robustness and dynamic range of the assay. It is therefore advisable to investigate the extent of the observer effect and find a healthy balance between accuracy of free target determination and assay practicality. ADA interferes with free target assays if the capture reagent is identical or very similar to the therapeutic antibody. ADA in this case not only binds to the thera peutic antibody but also binds and blocks the capture reagent so that little or no free target can bind to the capture reagent, leading to significant under-estimation of free target concentrations. This effect can lead to the false impression that target is suppressed even in
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Perspective Schwickart, Vainshtein, Lee, Schneider & Liang absence of therapeutic antibody. For this reason, using the therapeutic antibody as capture reagent should be avoided. However, especially early in development, appropriate reagents might not be available. A free assay with therapeutic antibody capture might suffice if the therapeutic antibody has a very low incidence of immunogenicity or the assay is used for a single-dose study where the therapeutic antibody is washed out before the immune systems starts producing ADA. Alternatively, free target data from ADA-positive individuals might be excluded from analysis. Also, in preclinical studies, sample can be depleted of animal antibodies including potential ADA. As most modern therapeutic antibodies are fully human, they would not be depleted. Total soluble target assays
The therapeutic antibody interferes frequently with assays measuring the total soluble target. Even if the epitope of neither capture- nor detection-antibody overlaps with the epitope of the therapeutic antibody, interference is still frequently observed. The therapeutic antibody might either change the conformation of the target or crosslink two target molecules, resulting in an over- or under-estimation of total target concentration. To circumvent this effect, excess therapeutic antibody can be added to samples to convert all free soluble targets to drug–target complexes. The addition of excess drug also allows using a target–drug complex assay system to measure total target. In such case, ADA might interfere by binding to the therapeutic antibody and inhibit detection or amplify the specific signal by forming multimeric complexes. Salimi-Moosavi et al. demonstrated that either alkaline or acid/guanidine treatment of study samples can irreversible denaturate the therapeutic antibody, while the target regains immunoreactivity after neutralization [34] . This sample pretreatment effectively eliminated all interference from the therapeutic antibody; it would be interesting to see if this approach is broadly applicable for other protein targets and therapeutic antibodies. Another elegant approach only used one noncompeting antibody and the therapeutic antibody as reagents [35] . Here, the noncompeting antibody was used to capture the target, free or bound to therapeutic antibody. The target together with bound therapeutic antibodies where then eluted with acid, neutralized and coated onto a polystyrene plate. The coated target was then detected with a labeled therapeutic antibody. Therapeutic antibody assays Immunoassays are commonly used for quantification of therapeutic antibody concentrations in biological
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matrices. Depending on the format, the assay can measure concentrations of either free drug or total drug. Free drug refers to therapeutic antibody not bound to the target. Total drug refers to free plus target-bound drug; for a review, see [36] . As the PK data is of central importance, regulatory guidelines [37] and industry consensus publications [38–40] have contributed recommendation regarding assay validation including some aspects of assay interference. Measurement of free therapeutic antibody typically uses antigen or neutralizing anti-idiotypic antibody (anti-ID) as capture. The detection antibody can be neutralizing anti-ID, non-neutralizing anti-ID, anti-human IgG, anti-human antibody to a specific isotype (e.g., anti-human IgG2 specific) or anti-framework mutations of the therapeutic antibody. Total therapeutic antibody can be captured and detected by non-neutralizing anti-ID, anti-human IgG, anti-human antibody to a specific isotype or anti-framework mutations of the therapeutic antibody. Non-neutralizing anti-IDs are rarely available since anti-ID campaigns most often yield many neutralizing anti-IDs but few if any non-neutralizing anti-IDs. Free therapeutic antibody quantification is technically challenging [41] , especially when soluble targets are present at high levels in the sample. Many matrix components can significantly alter the levels of the soluble target or affect the binding of drug to the soluble target, resulting in an observed change in the free drug concentration. While these components are much more likely to interfere with the quantification of soluble target discussed earlier, it may also introduce inaccuracy in free therapeutic antibody measurement if the target levels are high. Preparation of the sample is of special significance when quantifying antibody–drug conjugates (ADCs), since ADCs can undergo biotransformation in the collected samples or in vivo, complicating the already complex ADC bioanalysis [42] . Even monoclonal antibody assays can be affected by the sample preparation method. For example, the use of EDTA as anti-coagulant will chelate cations, such as Ca 2+ and Mg2+, and thus will impact accurate determination of free therapeutic antibody concentrations if these cations are necessary for drug–target binding. Suboptimal procedures (as discussed earlier in the biomarker section) can cause release of soluble target from cells during sample collection and preparation, leading to artificially high level of target in the sample and thus underestimation of free therapeutic antibody levels. To mitigate these potential assay interferences, sample collection procedures and assay conditions should be optimized for every therapeutic antibody assay. As
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Interference in immunoassays to support therapeutic antibody development in preclinical & clinical studies
discussed earlier, serum preparation can lead to release of proteins stored in platelets which is avoided by the use of plasma. In addition, stabilizing condition, such as temperature, can be implemented to minimize protein release from cells during sample collection. Acid dissociation treatment followed by neutralization in presence of assays reagents or maintaining the sample mildly acidic during the assay procedure has shown to be effective in reducing interference originating from the target [43,44] . For free therapeutic antibody assays, assay conditions, such as incubation time, capture reagent concentration and minimal required dilution, should be optimized in order to minimize the dissociation of drug from its target. This is especially important for the drugs that have relatively low affinity for its target and that soluble target concentration in circulation is relatively high. Dilution linearity and sample stability should be evaluated in the study population to account for the impact of changes in drug target level on the accuracy of free drug assessment. When antigen capture is used, high levels of binding protein or soluble receptor can saturate the capture reagents, resulting in underestimation of free drug concentration. The use of neutralizing anti-ID instead of drug target as a capture minimizes this concern. ADA in the sample is a source of matrix interference. ADA that competes with the capture antibody (or also detection antibody in homogenous assays) for binding to the drug will result in underestimation of therapeutic antibody concentration. Noncompeting ADA can crosslink therapeutic antibody molecules to form large complexes, which could also impact the accurate determination of the drug levels. A comparative evaluation of PK, PD and ADA will reveal if this interference occurs in a study and results can be interpreted accordingly. Similarly to biomarker assays, heterophilic antibodies and human anti-animal antibodies in the matrices are common sources of interferences for immunoassays and can be mitigated with the same methods described earlier. Human immunoglobulins in human matrices can cause significant background if anti-human antibody is used as capture or detection. Isotype-specific anti-human antibody can be used to replace pan anti-human antibody and to reduce the interference. It is even more effective to use antibodies against mutations on antibody framework of the drug molecule if present. ADA assays Biopharmaceuticals and even fully human thera peutic antibodies have the potential to generate ADA (also called anti-therapeutic antibodies) that can cause undesired effects ranging from loss of drug exposure, loss of efficacy, to serious adverse events [45,46] .
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Immuno genicity assessment is an important part of the safety assessment during clinical studies and ADA is typically tested in a tiered approach to detect, confirm and characterize ADA [47] . ADA assays are semi-quantitative, as these assays lack a standard calibrator. Positivity is defined by an assay signal above the assay cut point, determined by statistical analysis of drug naive negative samples [48] . Detailed regulatory recommendation on immunogenicity assay development were published [49] . ADA to therapeutic antibodies are mostly measured with immunoassays, although other methods, such as surface plasmon resonance by BIAcore [50,51] or homogenous mobility shift assays [52] have been used for ADA determinations. The majority of ADA immunoassays employ a bridging assay format, where ADA crosslink (bridge) two drug molecules conjugated with two different labels, one binds to a solid phase, while the other is conjugated to a tag that generates a signal (e.g., HRP). Direct binding immunoassays, where the therapeutic antibody is the capture reagent and the detection reagent detects the Fc-portion of the ADA, are used less frequently for antibody therapeutics [53] . The most common interference for ADA detection is the therapeutic antibody itself. Drug in the sample binds to ADA and prevents ADA to form complex with assay reagents. The ability of the assay to detect ADA in presence of drug, called drug tolerance, is recommended by regulators to be addressed during assay validation of clinical and nonclinical ADA assays [45] . Drug interference can be mitigated by collecting samples for ADA testing at time points when concentration of the therapeutic is expected to be low, for example, during the drug wash-out phase. In some cases, drug tolerance can be improved by acid dissociation of the drug–ADA complex, followed by neutralization in presence of the assay reagents [54–56] . Sample dilution and use of an assay with high sensitivity are effective to enhance the drug tolerance. Direct binding immunoassay that capture ADA with the drug and detect the ADA via its Fc-region might be less susceptible to drug interference. In this format ADA can be detected if one arm is available for binding to the drug capture, whereas binding to both arms is required to detect ADA in a bridging format. Wu et al. described a drug-tolerant assay using such direct binding format for detection of drug-specific ADAs of the IgE isotype [57] . Drug interference might be completely eliminated with assays that extract total antibody and then detect copurified biotherapeutics in order to quantitate ADA. Neubert et al. have demonstrated the feasibility of this approach with protein G extraction following by detection of the copurified therapeutic with LC–MS [58] .
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Perspective Schwickart, Vainshtein, Lee, Schneider & Liang Drug–target present in sample matrix may also interfere with ADA detection and lead to either false-positive or -negative results. False-positive results can arise in the presence of multimeric soluble target that bridges capture and detection reagents. Interestingly, cell membrane fragments containing CD20 were reported to cause matrix interference in an ADA assay for of atumumab [59] . False-negative results can be due to binding of the soluble target to the capture and/or detection antibody and thereby preventing detection of neutralizing ADA. Pretreatment with blocking antibodies to the target or blocking with target-binding proteins as well as immunodepletion of the target can eliminate this type of interference as demonstrated during development of an ADA assay for ranibizumab [60] . A high-affinity antitarget antibody in the ADA assay for the anti-angiopoitin peptibody AMG386 enabled sensitive detection of ADA in presence of high target concentrations [61,62] . Other methods, such as BIAcore, can be even more susceptible to target interference. Klakamp et al. [51] showed false-negative readouts from ADA-containing samples tested using surface-immobilized drug in the presence of the circulating target which could be mitigated by a noncompeting antitarget antibody. Although one would expect that drug-naive individuals are free of ADA, pre-existing antibodies are detected sometimes before dosing [63] . It is important to point out that pre-existing antibodies are not interference and might bind anywhere on the therapeutic antibody. For example, pre-existing neutralizing ADA to panitumumab was detected and confirmed [64] . Authors reported that these cross-reactive antibodies altered neither PK of the drug nor its safety profile. Still, the presence of pre-existing ADA always complicates the assay and interpretation of results. The determination of titer and specificity helps to understand the contribution of pre-existing antibodies to the post-dose ADA incidence. The clinical relevance of pre-existing antibodies is illustrated by cetuximab, where pre-existing IgE antibodies were associated with severe hypersensitivity reactions [65] . Pre-existing ADAs might be expected when a therapeutic protein contains an immunogenic domain of a naturally occurring protein, to which majority of human individuals might be previously exposed. Pre-existing ADA were observed in clinical studies of recombinant therapeutic immunotoxins, anti-CD3-diptheria toxin [66] and anti-CD22 Pseudomonas exotoxin A [67] . Rheumatoid factor (RF), common in rheumatoid arthritis patients, is antibodies against the Fc region of IgG, mostly of the IgM isotype [68] . RF binds with low affinity and is not expected to produce a positive signal in ADA testing. However, therapeutic antibodies with engineered Fc might cause in a higher affinity to RF, resulting in positive signals in ADA assays. Araujo et al.
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demonstrated that RF caused a positive signal at predose and, pretreatment of the samples with anti-human IgM antibodies decreased the effect from RF [69] . As this approach, might compromise the detection of ADA of the IgM isotype, the authors screened samples with and without anti-IgM antibodies and monitored increase in titers during treatment. Conclusion & future perspective The bioanalysis of soluble protein biomarkers, therapeutic antibodies, and ADA is an integral part of drug development, and each analyte has its own challenges. The most effective method to avoid matrix interference is a solid knowledge of target biology and the analyte itself with a focus on specificity of the assay. Technology may also play a major role to prevent or mitigate assay interference. Dilution is in many cases an effective tool to minimize interference, and the highest feasible dilution is limited by the sensitivity of the assay. High-sensitivity platforms can help to work with higher dilutions, providing an effective tool to minimize interference originating from the matrix. Improvement in separation and purification technologies might be quite effective to separate the analyte from interfering factors. In ADA assay, for example, effective quantitative separation of the ADA from the therapeutic antibody would solve the issue of drug tolerance. MS in combination with LC has become a powerful quantitative method that finds more and more application in bioanalysis of therapeutic proteins (especially antibody–drug conjugates) and biomarkers. Interference appears to be of much less concern compared with immunoassays. However, MS is extremely specific. While this can be extremely helpful in completely eliminating interference, it may also tremendously complicate bioanalysis if the analytes are biologically identical. There might be many cases where MS detects a mix of many slightly different chemical analytes whereas an immunoassay only detects one analyte. We expect MS, and especially LC–MS/MS to become more and more important for bioanalysis. We are curious how the tremendous specificity of MS methods will limit or accelerate its adoption in the analysis of different biological analytes. Financial & competing interest disclosure All authors are employees of MedImmune and own stock in AstraZeneca. The authors have no other 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 apart from those disclosed. No writing assistance was utilized in the production of this manuscript.
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Interference in immunoassays to support therapeutic antibody development in preclinical & clinical studies
Perspective
Executive summary What is interference in immunoassays? • Misinterpretation of assay specificity is often a source of observed interference. The specificity of the assay needs to be critically reviewed to define the actual assay analyte correctly. • Matrix interference leads to a decrease or increase in observed concentration when matrix components interact with the assay reagents. In addition, matrix components can degrade the assay reagents.
Manifestations of matrix interference during assay development & in-study results. • Parallelism/linearity experiments, recovery of spiked analyte and specificity evaluation will reveal most of the analyte-dependent interference. • Discordant individual pharmacokinetics, anti-drug antibodies (ADA) and biomarker results reveals interference after review of study results.
Soluble protein biomarkers • Sample processing and collection can change the analyte concentration. For example, some growth factors are released from platelets during serum preparation. Collection of plasma instead prevents this type of interference. • Isoforms, precursors, related proteins and binding proteins can lead to over-or under-estimation of analyte concentration. Determination of correct assay specificity as well as depletion or blocking of interfering components can mitigate unexpected results. • Endogenous antibodies can lead to falsely high results by crosslinking assay reagent or to falsely low results by blocking the analyte. Selection of assay reagents, dilution, depletion and blocking can minimize interference.
Free soluble target assays • Dissociation of target form the therapeutic antibody–target complex during sample preparation and assay procedure leads to intrinsic interference that can only be minimized but not entirely eliminated. • Assay reagent concentration, assay reagent affinity and incubation time need to be optimized to minimize dissociation of drug-bound target and thus to build an accurate free target assay. • Although dilution is in principle detrimental to the accuracy of free target assays, results from diluted samples can be accurate determined by applying reporting criteria.
Therapeutic antibody assays (pharmacokinetic & toxicokinetic assays) • Free and total therapeutic antibody assays are similar unless the level of soluble target is high. • Accurate free therapeutic antibody assays are technically challenging.
ADA assays • The therapeutic itself will always interfere with the assay, and ‘drug tolerance’ needs to be established during validation. • Target in the sample can lead to false-positive and -negative results and can be blocked with binding proteins or with specific antibodies to the target. • Pre-existing antibodies are not interference but can mask ADA emerging during the study.
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