A Cell-Based Reporter Gene Assay for TNF-α Neutralization: Analytical Qualification and Application to Adalimumab and Its Biosimilars

A Cell-Based Reporter Gene Assay for TNF-α Neutralization: Analytical Qualification and Application to Adalimumab and Its Biosimilars | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Cell-Based Reporter Gene Assay for TNF-α Neutralization: Analytical Qualification and Application to Adalimumab and Its Biosimilars Baolin Zhang, Christelle Anne F. Ancajas, Shen Luo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8273462/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To qualify a mechanism‑of‑action (MoA)–reflective reporter gene assay (RGA) for measuring the biological activity of adalimumab (Humira) and its biosimilars, supporting assessment of product quality, comparability, and functional consistency across the product lifecycle. Methods: The assay evaluates TNF‑α neutralization by monitoring inhibition of NF‑κB signaling in a reporter system. Qualification focused on key performance attributes, including system suitability, working range, reproducibility, and intermediate precision, to confirm fitness for routine use. Results: The RGA yielded MoA‑relevant readouts of NF‑κB pathway inhibition in the presence of adalimumab, demonstrating strong system suitability, a broad working range, high reproducibility, and consistent intermediate precision across repeated measures. These characteristics support reliable measurement of functional activity among adalimumab products and biosimilars. Conclusions: The qualified, MoA‑reflective RGA provides a robust tool for lifecycle management of adalimumab products, enabling quality assessment, comparability exercises, and monitoring of functional consistency across indications in which adalimumab is broadly used (e.g., rheumatoid arthritis, Crohn’s disease, psoriasis). Analytical Biochemistry Biochemical Research Methods Drug Discovery, Design, & Development Biotechnology and Bioengineering Cell Communication and Signaling Allergy & Immune Disorders Immunology Translational Medicine adalimumab (Humira) TNF-α neutralization reporter gene assay bioassay qualification Figures Figure 1 Figure 2 Figure 3 Introduction Adalimumab (Humira®) is a fully human monoclonal antibody that targets tumor necrosis factor-alpha (TNF-α), a pro-inflammatory cytokine central to the pathogenesis of various autoimmune and chronic inflammatory diseases ( 1 , 2 ). Since its initial approval, Humira has become one of the most widely prescribed biologics worldwide, with approved indications that include rheumatoid arthritis, Crohn’s disease, ulcerative colitis, psoriasis, and ankylosing spondylitis ( 3 ). Following the expiration of market exclusivity, development of adalimumab biosimilars has accelerated to expand patient access and reduce treatment costs ( 4 – 8 ). As of July 2025, the U.S. Food and Drug Administration (FDA) has approved ten adalimumab biosimilars: Amjevita® (adalimumab-atto), Cyltezo® (adalimumab-adbm), Hyrimoz® (adalimumab-adaz), Hadlima® (adalimumab-bwwd), Abrilada® (adalimumab-afzb), Hulio® (adalimumab-fkjp), Yusimry® (adalimumab-aqvh), Idacio® (adalimumab-aacf), Yuflyma® (adalimumab-aaty), and Simlandi® (adalimumab-ryvk), with additional candidates in development. Regulatory approval of biosimilars requires a rigorous demonstration of analytical comparability to the reference product across physicochemical, structural ( 9 ), and functional attributes ( 10 – 14 ). Among the functional assays for anti-TNF-α monoclonal antibodies, cell-based TNF-α neutralization assays are widely used for lot release and stability testing. A collaborative effort to establish the first international bioactivity standard for adalimumab highlighted the diversity of binding and functional assays employed across laboratories, including our group at the FDA ( 15 ). Binding has been evaluated by direct ELISAs using immobilized TNF-α with detection via HRP-conjugated anti-IgG (Fc-specific), anti-IgG1, or anti-kappa chain antibodies; alternative platforms included electrochemiluminescence (ECL), fluorescence resonance energy transfer (FRET), bio-layer interferometry (BLI), surface plasmon resonance (SPR), and flow cytometry using CHO cells expressing a membrane-bound, non-cleavable form of TNF-α ( 16 ). TNF-α neutralization was commonly measured as inhibition of TNF-α-induced cytotoxicity in murine fibroblast (L929) ( 10 ) or fibrosarcoma (WEHI-164 and WEHI-13) ( 17 ) cell lines. Other approaches included reporter gene assays (RGAs) using HEK-293 cells transfected with NF-κB-responsive reporters (luciferase or SEAP) and apoptosis assays quantifying TNF-α driven caspase activation in U937 cells, wherein neutralizing antibodies reduced the apoptotic signal ( 18 ). While no single assay addresses all characterization needs, RGAs are particularly valuable for evaluating the biological activity and consistency of anti-TNF-α antibodies, including adalimumab ( 19 ). By directly measuring NF-κB activation in response to TNF-α and its inhibition by therapeutic antibodies, RGAs provide a sensitive, and MoA-reflective readout suited to lot release, stability monitoring, and biosimilar comparability studies. In this study, we qualified a NF-κB reporter gene assay to measure the neutralizing activity of adalimumab and its biosimilars. The assay was evaluated for working range, specificity, precision (repeatability and intermediate precision), reproducibility, and system suitability, in concordance with USP chapters ( 20 ) and ( 21 ), as well as ICH Q2(R2) ( 22 ) on bioassay design, data analysis, and method validation/qualification. We further demonstrated the assay’s ability to quantify activity and support similarity assessments between reference adalimumab and its biosimilars. Materials and Methods Reagents, Materials, and Instrumentation The PathHunter® Adalimumab Bioassay, 2-plate format kit (Eurofins; catalog #93-0538B15-00131) was used as the cell-based reporter gene assay (RGA). The kit contained cryopreserved, assay-ready A549-IκB cells (passage 4), a tissue culture-treated plate, lyophilized TNF-α (10 ug per vial), reconstitution buffer, cell culture media, detection reagents for β-galactosidase enzyme fragment complementation, and a PBS-based buffer. All buffers and reconstituted TNF-α were prepared and stored per the manufacturer’s instructions (temperatures, concentrations, and volume). Therapeutic monoclonal antibodies were procured via a pharmaceutical procurement contract from commercial sources: Humira® (adalimumab) and two biosimilars, Yusimry® (adalimumab-aqvh), and Hadlima® (adalimumab-bwwd) pre-filled syringes or injector pens. Products in pre-filled syringes or pens were stored at 4°C until use. For clarity, Humira® is designated as the Reference adalimumab (Ref), Yusimry® as Biosimilar 1 (BS1), and Hadlima® as Biosimilar 2 (BS2). Luminescence was measured on a SpectraMax iD3 multimode microplate reader (Molecular Devices) and acquired with SoftMax Pro v7.3.1 using the assay-specified luminescence settings. Data processing and curve fitting were performed in GraphPad Prism v10.4.2. Reporter Gene Assay (TNF-α Neutralization) Cell seeding. Assay-ready A549-IkB cells were thawed and seeded into sterile, tissue culture treated 96-well plates at 9,600 − 10,000 cells/well and incubated at 37°C with 5% CO 2 for 48 hours prior to assay. Antibody and TNF-α preparation. On the assay day, serial dilutions of adalimumab were prepared in a separate 96-well dilution plate (two replicate rows per article). A fixed concentration of TNF-α (3.0 ng/mL) was added to each adalimumab dilution and pre-incubated for 30 minutes at room temperature. In parallel, a TNF-α activity curve was prepared by serially diluting TNF-α from 200 to 1.9x10 − 4 ng/mL using a 1:3 scheme. Assay Execution and Detection. Using a multi-channel pipette, 20 µL from each well of the dilution plate was transferred to the assay plate containing A549-IkB cells. Plates were incubated for 2-hours at room temperature. Detection reagents containing the complementary β-galactosidase fragment were added and incubated for 15 min, followed by addition of the β-galactosidase substrate and a 1-hour incubation to generate luminescence from the reconstituted active enzyme. Luminescence (RLU) was immediately read on the microplate reader (Molecular Devices) in the luminescence mode, reading for all wavelengths, at the endpoint read type, and analyzed with SoftMax Pro (v. 7.3.1) software. Experimental Design Each microplate constituted one assay run and was analyzed independently. For neutralization curves, adalimumab was tested at 11 concentrations spanning 10 µg/mL to 0.00051 µg/mL in the presence of 3.0 ng/mL TNF-α. Plate layouts included two replicate rows of serial dilutions for the Reference adalimumab, and two replicate rows for each test article, yielding pseudo-replicates at each concentration. Negative control wells contained 3.0 ng/mL TNF-α without adalimumab. Experiments were conducted in triplicate assay runs. Model Fitting Within each plate, responses from pseudo-replicate wells at the same concentration were averaged prior to model fitting. Concentrations were log 10− transformed, and averaged responses were fitted to a four-parameter logistic (4PL) model in GraphPad Prism (version 10.4.2). Outliers among within-run replicates were identified using the Grubbs test (two-sided, α = 0.05). Curve quality was evaluated by the coefficient of determination (R²) values. For TNF-α activity controls, 4PL fits of the TNF-α concentration-response curves were used to calculate the EC80 – the TNF-α concentration eliciting 80% of the maximal response) for each run; EC80 values were trended as a surrogate of TNF-α activity and general system suitability for that run. Negative control wells were prepared without the addition of TNF-α. Parallelism Assessment and Relative Potency. Parallelism between the Reference adalimumab and test samples within the same run was assessed by comparing unconstrained and constrained 4PL models via an F-test (α = 0.05) in GraphPad Prism. In the unconstrained model, RLU vs log(mAb concentration) was fitted independently for each curve. In the constrained model, the reference and test curves were fitted simultaneously with shared Hill slope, top, and bottom asymptotes, while EC50 (or logEC50) parameters were allowed to differ. A p-value > 0.05 (α = 0.05) from the F-test indicated no statistical differences between the curves, supporting curve parallelism or similarity. Under this condition, only the EC50 (or logEC50) values were allowed to vary, enabling percent relative potency calculation as the ratio of the reference EC50 to the test sample EC50, multiplied by 100. Results Assay Establishment and Readout We adopted the PathHunter® Adalimumab Bioassay to quantify the neutralization of soluble TNF-α by reference adalimumab (Humira®) and biosimilars. The cell-based reporter system uses a β-galactosidase enzyme fragment complementation system in A549 cells overexpressing TNFR1 and IkB fused to a β-gal fragment. TNF-α binding to TNFR1 activates NF-kB triggering IkB degradation and disruption of the complementation complex; anti-TNF-α antibodies preserve IκB, reconstituting active β-gal and generating chemiluminescence proportional to TNF-α neutralization (Fig. 1 ). Method qualification emphasized working range, precision, and robustness, following ICH Q2(R2) and USP chapters and . Working Range and Specificity An 11-point, serial dilution of reference adalimumab (6 replicate curves per run) produced a sigmoidal dose-response curve (DRC) well fit by a four-parameter logistic (4PL) model (R² = 0.9839), with a Hill slope of 1.45 and EC50 of 57.55 ng/mL (Fig. 1 b). The response curves encompassed ≥ 3 points on the slope and ≥ 4 points across the asymptotes. TNF-α-only wells (3 ng/mL) consistently exhibited low relative light units (RLU), aligning with the no-antibody asymptote (Fig. 1 b). To standardize neutralization, TNF-α was fixed at 3 ng/mL in all antibody-containing wells, and each run included a TNF-α control curve. The TNF-α control (log-dosed) yielded a sigmoidal, negatively sloped 4PL fit (R² = 0.9928) with decreasing luminescence at higher TNF-α (Fig. 1 c). Signal-to-background (S/B) ratios were comparable for anti-TNF-α and TNF-α control curves (9.57 vs 9.55, respectively). Specificity of the assay was demonstrated from the lack of apparent dose response curve from buffer and control wells. No DRC was observed for the buffer plus TNF-α wells (Fig. 1 b), and for buffer-only wells that lacked TNF-α and anti-TNF-α (Fig. 1 c). Precision Precision was assessed as repeatability (intra-assay) and intermediate precision (inter-assay). Intra-assay %CV, calculated from n = 3 replicate EC50 values within a plate/run, ranged from 3% to 12% across runs. Intermediate precision, assessed across 3 independent runs and 2 instruments, showed %CVs of 19% and 13%, (Table 1 ), indicating high between-run reproducibility. Table 1 Precision of the reporter gene assay (RGA) and comparison of 4PL parameter estimates and coefficients of variation between two plate readers. EC 50 , Hillslope, and S/B are based on validated data from three independent runs ( n = 3) per instrument, with each run comprising three technical replicate ( n = 3) dose–response curves, comparing assay performance and parameter consistency across instruments. Percent coefficient of variation (%CV) for EC₅₀ values were assessed at both intra-assay (repeatability) and inter-assay (intermediate precision) levels. Plate Reader Parameter assessed EC50 Hillslope S/B R 2 Independent run (Plate) mean (ng/mL) Intra-assay %CV Inter-assay %CV mean Intra-assay %CV Inter-assay %CV mean Intra-assay % CV Inter-assay %CV PR 1 P1 56.21 12% 19% 1.53 13% 5% 6.89 6% 17% 0.988 P2 58.34 3% 1.46 10% 7.39 10% 0.975 P3 40.28 7% 1.39 8% 9.41 10% 0.989 PR 2 P1 41.88 3% 13% 1.62 4% 3% 9.24 5% 7% 0.985 P2 43.37 6% 1.60 9% 9.69 12% 0.969 P3 52.67 9% 1.53 3% 8.42 4% 0.979 Inter-instrument %CV 16% Inter-instrument %CV 6% Inter-instrument %CV 14% System Suitability System suitability (SST) criteria for reference adalimumab were established from n = 20 independent runs (Table 2 ). EC50 values spanned 36.78 to 63.22 ng/mL with a mean of 50.91 ± 9.14 ng/mL; acceptance limits were set at ± 2 SD (32.63–69.19 ng/mL). Additional SST requirements were RLU %CV ≤ 25%, S/B between 5.0 and 11.0, and Hill slope 1.0 to 1.8. Assay runs were considered valid only if all 4PL fitting parameters met these criteria; runs failing to meet these thresholds were excluded from further analysis. Table 2 System suitability and acceptance criteria. Summary of key parameters and predefined limits used to ensure assay reliability prior to relative potency determination for TNF-α neutralizing activity. Characteristic Parameter Description Historical Results Range Historical Results Mean ± SD Acceptance criteria Precision inter-well %CV RLU CVs between replicate wells 2.4% − 24.8% - CV ≤ 25% in the adalimumab range of 10,000–0.51 ng/mL inter-assay %CV EC50 CVs 5–19% - ≤ 20% 4PL parameter Hillslope DRC Sigmoidal shape 1.1–1.9 1.53 ± 0.24 1.0–1.9 EC 50 Potency 36.78–63.22 50.91 ± 9.14 32.62–69.19 ng/mL (mean ± 2xSD) S/B Top asymptote signal/bottom signal 5.0–10.8 8.34 ± 2.02 5.0–11.0 R 2 Correlation coefficient of constrained 4PL curve 0.945–0.993 - ≥ 0.94 Robustness Minor procedural variations were introduced to test robustness. Conditions tested were varying the TNF-α pre-incubation times (30min ± 15min) and a second plate reader instrument. Three independent runs were prepared wherein each run included two pseudo replicate rows of the 15-, 30-, and 45-min pre-incubated TNF-α and anti-TNF-α solution on the same plate. The pre-incubation times of 15, 30, or 45 minutes generated sigmoidal curves (Fig. 2 a–c) with no overall statistical differences by F-test (p > 0.05; Supplementary Table S1). Nevertheless, all 15-min EC50 values fell outside the EC50 acceptance window, and two 15-min curves had R² < 0.94. The 15-min condition also showed elevated variability in hillslope and S/B (%CV = 41% and 29%, respectively; Fig. 2 d), indicating reduced reliability at shorter pre-incubation. In contrast, 30- and 45-min conditions met SST criteria. Performance on an alternate plate reader also met all SST limits; inter-instrument %CVs were 16% for EC50, 6% for Hill slope, and 14% for S/B (all ≤ 20%; Table 1 ). Applications to Adalimumab Biosimilars Two adalimumab biosimilars, BS1 and BS2, were evaluated using the validated bioassay. Three independent runs included two pseudo replicate rows of the reference product, BS1, and BS2 for each run on the same plate. Both biosimilars produced robust sigmoidal 4PL fits with unconstrained models (R² ≥ 0.94; Fig. 3 ). Parallelism to the reference product was confirmed using constrained models sharing hillslope and asymptotes. F-tests revealed no statistical difference (p > 0.05 for all comparisons; Supplementary Table S2). Relative potencies were 103% (BS1) and 96% (BS2) compared to the reference adalimumab, both within the predefined acceptance interval for this reporter gene assay. Discussion Bioassays are central to the quality control of therapeutic proteins because they quantify biological function in a MOA–relevant context, complementing physicochemical tests that probe isolated attributes. Reporter gene assays (RGAs) are particularly well suited to TNF inhibitors, as engineered cells convert TNF-α–driven signaling into a sensitive luminescent output that integrate ligand binding, pathway modulation, and downstream response in a single measurement (Fig. 1 ). In this study, we established and partially validated a β-galactosidase enzyme-fragment complementation RGA using A549-TNFR1/IκB-β-gal cells to measure neutralization of soluble TNF-α by adalimumab and its biosimilars, following ICH Q2(R2) and USP /. The assay demonstrated an excellent working range, with 4PL fits capturing multiple informative points along the slope and asymptotes (Fig. 1 b, c). Inclusion of a TNF-α control curve in every run standardized the neutralization context (fixed TNF-α at 3 ng/mL), verified reagent activity, and anchored the upper signal ceiling (TNF-α–negative wells), which can vary with cell density and run-to-run factors. Collectively, these design features support reliable quantitation across the expected potency range. Precision performance was robust across study tiers. Repeatability (%CV) and intermediate precision (average %CV) confirmed stable EC50 estimates within and across plates and days (Table 1 ). Inter-instrument assessments further showed that EC50 and S/B parameters had %CV values of ≤ 20% (Table 1 ), underscoring the method’s portability. Such precision meets expectations for quantitative cell-based assays intended for routine use and reduces the likelihood of false trends during product life-cycle monitoring. SST anchored day-to-day assay governance to historical performance. From n = 20 runs, the reference adalimumab EC50 distribution (mean ≈ 50.9 ng/mL) defined acceptance limits at ± 2 SD (32.6–69.2 ng/mL), complemented by criteria for RLU %CV ≤ 25%, S/B between 5.0 and 11.0, and Hill slope 1.0–1.8 (Table 2 ). Although the coefficient of determination (R²) was not a formal SST criterion, it was monitored as a quality indicator. Runs with low R² typically coincided with out-of-window EC50 or atypical slope and were excluded, demonstrating the value of multiple, orthogonal SST elements. This framework provides operational resilience while avoiding over-constraint that could otherwise reject biologically acceptable runs. Robustness tests defined practical boundaries for execution. Varying the TNF-α pre-incubation duration showed that 30–45 min maintained EC50 values within SST limits and yielded consistent 4PL fits, whereas 15 min introduced excessive variability (%CVs increased in slope and S/B; Fig. 2 ; Supplementary Table S1). These findings support a ≥ 30-min pre-incubation as the recommended condition. Importantly, performance on an alternate plate reader also met all SST criteria (Table 1 ), indicating that the method tolerates reasonable differences in detection systems when governed by SST. Further studies demonstrated the bioassay’s applicability for evaluating biosimilars. Both BS1 and BS2 produced sigmoidal dose–response curves with excellent 4PL fits (R² ≥ 0.94) and satisfied parallelism criteria relative to the reference product using constrained models (shared slope and asymptotes; F-tests p > 0.05; Fig. 3 ; Supplementary Table S2). The relative potencies were 103% (BS1) and 96% (BS2), each within the predefined acceptance interval for this reporter gene assay (80–137%). Although only a limited number of lots were tested, these findings support the utility of the bioassay’s suitability for biosimilar development and warrant further studies to evaluate its stability-indicating capability using stressed samples, such as those exposed to heat or light. The platform’s MOA relevance and modular features suggest adaptability across the TNF inhibitor class. With appropriate qualification such as re-establishing SST limits, verifying parallelism, and confirming TNF-α control behavior, the same cellular backbone and readout can be extended to other TNF-targeted biologics (e.g., infliximab, etanercept, certolizumab pegol, golimumab) and their biosimilars. A unified, mechanism-relevant bioassay strategy may streamline development, facilitate bridging across manufacturing changes, and support regulatory comparability submissions. This work also clarifies the assay’s scope and technical considerations. The readout specifically reflects neutralization of soluble TNF-α via TNFR1-linked NF-κB signaling in A549 cells and does not directly assess interactions with transmembrane TNF or off-pathway mechanisms. Because cell-based assays are inherently sensitive to biological variables such as passage number, plating density, and cytokine lot, rigorous control of cell health, inclusion of TNF-α activity controls, and continuous control charting of EC50, slope, and S/B are essential. In practice, orthogonal methods such as ligand binding or targeted physicochemical analyses, should be integrated into a comprehensive control strategy, with the RGA serving as the primary functional readout. In summary, the qualified RGA is fit-for-purpose to quantify the functional activity of adalimumab and its biosimilars. Its demonstrated precision, robustness to operational variables, and SST-guided performance, combined with strong MOA relevance, support its use for lot release and comparability testing (Figs. 1 – 3 ; Tables 1 – 3 ). When applied alongside orthogonal analytics, this platform strengthens the quality framework for TNF-α inhibitors and enables consistent, clinically relevant potency control throughout the product life cycle. Table 3 Summary of assay parameters tested and acceptance criteria for this reporter gene assay. Parameter Acceptance criteria Pass/Fail Specificity No dose response curve (DRC) must be observed from wells with buffer, with TNF-α, without anti-TNF-α Pass No DRC must be observed from wells with buffer and without TNF-α Pass Precision Repeatability Intra-assay %CV of EC50 values must be less than 15% for each independent run Pass Intermediate Precision Inter-assay %CV of EC50 values must be less than 20% Pass Working Range S/B of the DRC should be between 5.0–11.0 Pass Slope of the DRC should be within 1.0–1.9 Pass The coefficient of correlation (R 2 ) of the DRC when fit to a 4PL model must be > or equal to 0.94 Pass Robustness Assay must perform within SST and precision limits in an alternate plate reader Pass Pre-incubation times of 30–45 min must result in 4PL values within SST limits and %CV range Pass Parallelism The F-test (4PL 3-parameter constrained fitting) comparisons between DRCs must result in a p-value > 0.05 to determine % relative potency N/A System Suitability All assay system suitability criteria are met N/A Abbreviations 4PL Four-Parameter Logistic CV coefficient of variation DRC dose response curve EC50 half maximal effective concentration FDA Food and Drug Administration IκB Inhibitor kappa B MoA mechanism of action NF-κB nuclear factor kappa B RGA reporter gene assay RLU relative luminescence unit RP Relative Potency R 2 coefficient of determination S/B signal-to-background ratio SD standard deviation SST system suitability TNF-α tumor necrosis factor-alpha TNFR1 tumor necrosis factor receptor. Declarations Acknowledgments We thank Drs. David Keire and Sarah Rogstad for critical review of the manuscript. Funding This research was supported by FDA’s intramural research program. Conflicts of Interest No potential conflicts of interest were disclosed. Author Contributions Conceptualization, B.Z.; Data acquisition and analysis, C.F.A.; Sample preparation: C.F.A., S.L.; Writing – Original Draft: B.Z. and C.F.A.; Writing – Review & Editing, all authors; Supervision, B.Z.; All authors have read and approved the final version of the manuscript. Data Availability The data supporting this manuscript are included within the article and its cited references, all of which are publicly available. Disclaimer The views expressed in this article are those of the authors and are based on experimental data and a review of relevant scientific literature. These views should not be construed to represent FDA’s views or policies. References Bain B, Brazil M. Adalimumab. Nat Rev Drug Discov. 2003;2(9):693-94. Croft M, Salek-Ardakani S, Ware CF. Targeting the TNF and TNFR superfamilies in autoimmune disease and cancer. Nat Rev Drug Discov. 2024;23(12):939-61. Burmester GR, Gordon KB, Rosenbaum JT, Arikan D, Lau WL, Li P, et al. Long-Term Safety of Adalimumab in 29,967 Adult Patients From Global Clinical Trials Across Multiple Indications: An Updated Analysis. Advances in Therapy. 2020;37(1):364-80. Lu X, Hu R, Peng L, Liu M, Sun Z. Efficacy and Safety of Adalimumab Biosimilars: Current Critical Clinical Data in Rheumatoid Arthritis. Frontiers in Immunology. 2021;Volume 12 – 2021. Huizinga TWJ, Torii Y, Muniz R. Adalimumab Biosimilars in the Treatment of Rheumatoid Arthritis: A Systematic Review of the Evidence for Biosimilarity. Rheumatol Ther. 2021;8(1):41-61. Ascef BdO, Almeida MO, Medeiros-Ribeiro ACd, Oliveira de Andrade DC, Oliveira Junior HAd, de Soárez PC. Therapeutic Equivalence of Biosimilar and Reference Biologic Drugs in Rheumatoid Arthritis: A Systematic Review and Meta-analysis. JAMA Network Open. 2023;6(5):e2315872-e. Abitbol V, Benkhalifa S, Habauzit C, Marotte H. Navigating adalimumab biosimilars: an expert opinion. J Comp Eff Res. 2023;12(11):e230117. Allegretti JR, Brady JH, Wicker A, Latymer M, Wells A. Relevance of Adalimumab Product Attributes to Patient Experience in the Biosimilar Era: A Narrative Review. Advances in Therapy. 2024;41(5):1775-94. Baldisseri D, Luo S, Ancajas CAF, Ortega-Rodriguez U, Fischer C, Zou G, et al. NMR-based structural integrity analysis of therapeutic monoclonal antibodies: a comparative study of Humira and its biosimilars. mAbs. 2025;17(1):2551208. U.S. Food and Drug Administration Draft Guidance for Industry (2019): Development of Therapeutic Protein Biosimilars: Comparative Analytical Assessment and Other Quality-Related Considerations. Available from: https://www.fda.gov/drugs/drug-safety-and-availability/fda-issues-draft-guidance-industry-design-and-evaluation-comparative-analytical-studies. Nupur N, Joshi S, Gulliarme D, Rathore AS. Analytical Similarity Assessment of Biosimilars: Global Regulatory Landscape, Recent Studies and Major Advancements in Orthogonal Platforms. Frontiers in Bioengineering and Biotechnology. 2022;Volume 10 - 2022. Markus R, McBride HJ, Ramchandani M, Chow V, Liu J, Mytych D, et al. A Review of the Totality of Evidence Supporting the Development of the First Adalimumab Biosimilar ABP 501. Advances in Therapy. 2019;36(8):1833-50. Millán-Martín S, Jakes C, Carillo S, Bones J. Multi-attribute method (MAM) to assess analytical comparability of adalimumab biosimilars. Journal of Pharmaceutical and Biomedical Analysis. 2023;234:115543. Jiang Y, Arora T, Klakamp S, Davis J, Chandrasekher YA, Young G, et al. Demonstration of Physicochemical and Functional Similarity of Biosimilar Adalimumab-aqvh to Adalimumab. Drugs R D. 2023;23(4):377-95. Wadhwa M, Bird C, Atkinson E, Cludts I, Rigsby P. The First WHO International Standard for Adalimumab: Dual Role in Bioactivity and Therapeutic Drug Monitoring. Frontiers in Immunology. 2021;Volume 12 - 2021. Camacho-Sandoval R, Sosa-Grande EN, González-González E, Tenorio-Calvo A, López-Morales CA, Velasco-Velázquez M, et al. Development and validation of a bioassay to evaluate binding of adalimumab to cell membrane-anchored TNFα using flow cytometry detection. Journal of Pharmaceutical and Biomedical Analysis. 2018;155:235-40. Khabar KSA, Siddiqui S, Armstrong JA. WEHI-13VAR: a stable and sensitive variant of WEHI 164 clone 13 fibrosarcoma for tumor necrosis factor bioassay. Immunology Letters. 1995;46(1):107-10. Minafra L, Di Cara G, Albanese NN, Cancemi P. Proteomic differentiation pattern in the U937 cell line. Leukemia Research. 2011;35(2):226-36. Twomey JD, George S, Zhang B. Fc gamma receptor polymorphisms in antibody therapy: implications for bioassay development to enhance product quality. Antib Ther. 2025;8(2):87-98. USP 〈1032〉 Design and Development of Biological Assays. In USP-NF. Rockville, MD: United States Pharmacopeia; DOI: https://doi.usp.org/USPNF/USPNF_M1354_01_01.html USP Analysis of Biological Assays. In USP-NF. Rockville, MD: United States Pharmacopeia; DOI: https://doi.usp.org/USPNF/USPNF_M5677_01_01.html International Conference on Harmonization (ICH) guidelines Q2(R2) Validation of Analytical Procedures, March 2022; https://www.fda.gov/regulatory-information/search-fda-guidance-documents/q2r2-validation-analytical-procedures Additional Declarations The authors declare no competing interests. Supplementary Files SupplementalTable12022025.docx Variation in TNF-α and adalimumab pre-incubation conditions. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8273462","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":554873388,"identity":"8c563a14-c8e4-4cce-aae8-e4d580450f13","order_by":0,"name":"Baolin Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIie2QsWrDMBRFnzAki6GrIKH9BRWBXWMV/4pEQFncfoMnT26y5lM6KmhNmzVrKHRpBo1uydDnmjaTGo+F6gyXuxx0nwACgT8IAyBG9gXAiQiAxmcV+FHISg9VvksUD1HSsTVm/whFOn6yb0LmVzB5sA4+hKo8StZoadQGoqy513kp59fV9FlTstBehZmSGVXDCEvC71pLKlomQBrLvbdsD19KjCXhN9IWqHD3q7LrX6FY+AtIq1BhFFp76VOy1SveUlPGdoeENHI+q3EYVZX2KunFbL1/r0XBtrinlfntshvmjuLMVwPtYtRnFzh1EJE79eMwJRAIBP4Fn0l3WMUXOhTqAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-7859-0843","institution":"United States Food and Drug Administration","correspondingAuthor":true,"prefix":"","firstName":"Baolin","middleName":"","lastName":"Zhang","suffix":""},{"id":554873740,"identity":"7f26374e-fe50-4816-85f3-6264f2c0c4f2","order_by":1,"name":"Christelle Anne F. Ancajas","email":"","orcid":"https://orcid.org/0009-0002-3699-6295","institution":"United States Food and Drug Administration","correspondingAuthor":false,"prefix":"","firstName":"Christelle","middleName":"Anne F.","lastName":"Ancajas","suffix":""},{"id":554873824,"identity":"63d522e8-bdae-4f2f-8c3b-1630cd6ef5b8","order_by":2,"name":"Shen Luo","email":"","orcid":"https://orcid.org/0000-0002-1912-6741","institution":"United States Food and Drug Administration","correspondingAuthor":false,"prefix":"","firstName":"Shen","middleName":"","lastName":"Luo","suffix":""}],"badges":[],"createdAt":"2025-12-03 19:56:34","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8273462/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8273462/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97504600,"identity":"8c9713e4-3ca9-4685-839e-d1ebbfd2400b","added_by":"auto","created_at":"2025-12-05 07:32:21","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":81221,"visible":true,"origin":"","legend":"","description":"","filename":"HumiraRGAbioassay12022025.docx","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/940ec7e349c9a772e174645c.docx"},{"id":97504597,"identity":"22f85588-eddb-49ac-a02a-fe23b8469ede","added_by":"auto","created_at":"2025-12-05 07:32:21","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs8273462.json","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/dc8670ba42df98ad93fa7d92.json"},{"id":97671645,"identity":"e25e1ae5-dc69-4ccf-ab4c-847c0e368f33","added_by":"auto","created_at":"2025-12-08 09:32:52","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":80879,"visible":true,"origin":"","legend":"","description":"","filename":"rs82734621enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/ba373ed7810118e058309542.xml"},{"id":97504598,"identity":"bd12a543-3e04-4c11-9cc4-bcc4f32a8ec1","added_by":"auto","created_at":"2025-12-05 07:32:21","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":79746,"visible":true,"origin":"","legend":"","description":"","filename":"rs82734621structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/29de079ed2e1cb49d38990ff.xml"},{"id":97670130,"identity":"5d7c651f-a9d8-4f2e-9985-937d0490495d","added_by":"auto","created_at":"2025-12-08 09:29:45","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":84556,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/a70ae8b1df949ff722e5be98.html"},{"id":97504604,"identity":"6c4aa746-8052-4c4e-a85e-9fee0c2ffdc1","added_by":"auto","created_at":"2025-12-05 07:32:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":39154608,"visible":true,"origin":"","legend":"\u003cp\u003eReporter gene assay (RGA) design and representative response profiles. (a) Schematic illustration of the RGA reflecting adalimumab’s mechanism of action. Tumor necrosis factor-α (TNF-α) binds TNFR1 to activate NF-κB signaling and induce IκB degradation. Adalimumab neutralizes TNF-α, preventing receptor engagement and stabilizing IκB, which is fused to a β-galactosidase fragment that generates a chemiluminescent signal.\u003cbr\u003e\n(b) Dose-dependent stabilization of IκB by adalimumab in the presence of 3 ng/mL TNF-α, shown as increased relative luminescence units (RLU). Data represent six pseudo replicates from a single assay run. Negative controls contained buffer and TNF-α and lacked anti-TNF-α. (c) Positive-control TNF-α activity curve; negative controls lacked TNF-α. \u003cem\u003eR²\u003c/em\u003e, correlation coefficient; \u003cem\u003eS/B\u003c/em\u003e, signal-to-background ratio.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/64f399daa403b22f860e118e.png"},{"id":97504595,"identity":"6c06bdd5-7fd0-4059-b531-fa3e60e1856c","added_by":"auto","created_at":"2025-12-05 07:32:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90244,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of TNF-α and adalimumab pre-incubation time on dose–response relationships and \u003cem\u003eEC₅₀\u003c/em\u003e estimates.\u003cbr\u003e\n(a–c) Dose–response curves obtained at three pre-incubation durations (30 min ± 15 min) across three independent runs. Each curve represents duplicate responses, with data points showing mean ± SD per dose. For each run, curves were fitted using shared parameters for the Hill slope, top, and bottom asymptotes prior to \u003cem\u003eEC₅₀\u003c/em\u003e ratio analysis.\u003cbr\u003e\n(d) Inter-assay coefficients of variation (CVs) for the four-parameter logistic (4PL) model parameters across the three assay runs for each pre-incubation conditions.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/bf2f5367709164e629c7bcc9.png"},{"id":97504603,"identity":"b41d8241-c21c-4f3d-b172-2c9b3e0acbae","added_by":"auto","created_at":"2025-12-05 07:32:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":24075457,"visible":true,"origin":"","legend":"\u003cp\u003eComparative dose–response analysis of reference adalimumab and biosimilar products.\u003cbr\u003e\n(a, c, e) Reference adalimumab versus BS1; (b, d, f) reference adalimumab versus BS2, each evaluated across three independent assay runs (runs 1–3). Each curve represents duplicate responses per assay run, with data points showing mean ± SD per dose. For each run, curves were fitted using shared Hill slope, top, and bottom asymptotes prior to \u003cem\u003eEC₅₀\u003c/em\u003e ratio analysis.\u003cbr\u003e\n(g) Percent relative potency for BS1 and BS2, shown as mean ± SD across three independent runs (\u003cem\u003en\u003c/em\u003e = 3).\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/fa3c77e5d9e60869a8d5cb75.png"},{"id":98621818,"identity":"c8c8a9f1-a3f0-420c-893d-9384670f1412","added_by":"auto","created_at":"2025-12-19 16:23:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":909812,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/72a54ef7-9ade-4946-b68e-4d8a6e6133ce.pdf"},{"id":97671429,"identity":"34884e71-ba4f-443c-9c8b-f78ea3e207ed","added_by":"auto","created_at":"2025-12-08 09:32:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19755,"visible":true,"origin":"","legend":"\u003cp\u003eVariation in TNF-α and adalimumab pre-incubation conditions.\u003c/p\u003e","description":"","filename":"SupplementalTable12022025.docx","url":"https://assets-eu.researchsquare.com/files/rs-8273462/v1/b409b8f96b3859850ac69567.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eA Cell-Based Reporter Gene Assay for TNF-α Neutralization: Analytical Qualification and Application to Adalimumab and Its Biosimilars\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAdalimumab (Humira\u0026reg;) is a fully human monoclonal antibody that targets tumor necrosis factor-alpha (TNF-α), a pro-inflammatory cytokine central to the pathogenesis of various autoimmune and chronic inflammatory diseases (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Since its initial approval, Humira has become one of the most widely prescribed biologics worldwide, with approved indications that include rheumatoid arthritis, Crohn\u0026rsquo;s disease, ulcerative colitis, psoriasis, and ankylosing spondylitis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Following the expiration of market exclusivity, development of adalimumab biosimilars has accelerated to expand patient access and reduce treatment costs (\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). As of July 2025, the U.S. Food and Drug Administration (FDA) has approved ten adalimumab biosimilars: Amjevita\u0026reg; (adalimumab-atto), Cyltezo\u0026reg; (adalimumab-adbm), Hyrimoz\u0026reg; (adalimumab-adaz), Hadlima\u0026reg; (adalimumab-bwwd), Abrilada\u0026reg; (adalimumab-afzb), Hulio\u0026reg; (adalimumab-fkjp), Yusimry\u0026reg; (adalimumab-aqvh), Idacio\u0026reg; (adalimumab-aacf), Yuflyma\u0026reg; (adalimumab-aaty), and Simlandi\u0026reg; (adalimumab-ryvk), with additional candidates in development.\u003c/p\u003e\u003cp\u003eRegulatory approval of biosimilars requires a rigorous demonstration of analytical comparability to the reference product across physicochemical, structural (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), and functional attributes (\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Among the functional assays for anti-TNF-α monoclonal antibodies, cell-based TNF-α neutralization assays are widely used for lot release and stability testing. A collaborative effort to establish the first international bioactivity standard for adalimumab highlighted the diversity of binding and functional assays employed across laboratories, including our group at the FDA (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Binding has been evaluated by direct ELISAs using immobilized TNF-α with detection via HRP-conjugated anti-IgG (Fc-specific), anti-IgG1, or anti-kappa chain antibodies; alternative platforms included electrochemiluminescence (ECL), fluorescence resonance energy transfer (FRET), bio-layer interferometry (BLI), surface plasmon resonance (SPR), and flow cytometry using CHO cells expressing a membrane-bound, non-cleavable form of TNF-α (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). TNF-α neutralization was commonly measured as inhibition of TNF-α-induced cytotoxicity in murine fibroblast (L929) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) or fibrosarcoma (WEHI-164 and WEHI-13) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) cell lines. Other approaches included reporter gene assays (RGAs) using HEK-293 cells transfected with NF-κB-responsive reporters (luciferase or SEAP) and apoptosis assays quantifying TNF-α driven caspase activation in U937 cells, wherein neutralizing antibodies reduced the apoptotic signal (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile no single assay addresses all characterization needs, RGAs are particularly valuable for evaluating the biological activity and consistency of anti-TNF-α antibodies, including adalimumab (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). By directly measuring NF-κB activation in response to TNF-α and its inhibition by therapeutic antibodies, RGAs provide a sensitive, and MoA-reflective readout suited to lot release, stability monitoring, and biosimilar comparability studies.\u003c/p\u003e\u003cp\u003eIn this study, we qualified a NF-κB reporter gene assay to measure the neutralizing activity of adalimumab and its biosimilars. The assay was evaluated for working range, specificity, precision (repeatability and intermediate precision), reproducibility, and system suitability, in concordance with USP chapters\u0026thinsp;\u0026lt;\u0026thinsp;1032\u0026gt;(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) and \u0026lt;\u0026thinsp;1034\u0026gt;(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), as well as ICH Q2(R2) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) on bioassay design, data analysis, and method validation/qualification. We further demonstrated the assay\u0026rsquo;s ability to quantify activity and support similarity assessments between reference adalimumab and its biosimilars.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eReagents, Materials, and Instrumentation\u003c/h2\u003e\u003cp\u003eThe PathHunter\u0026reg; Adalimumab Bioassay, 2-plate format kit (Eurofins; catalog #93-0538B15-00131) was used as the cell-based reporter gene assay (RGA). The kit contained cryopreserved, assay-ready A549-IκB cells (passage 4), a tissue culture-treated plate, lyophilized TNF-α (10 ug per vial), reconstitution buffer, cell culture media, detection reagents for β-galactosidase enzyme fragment complementation, and a PBS-based buffer. All buffers and reconstituted TNF-α were prepared and stored per the manufacturer\u0026rsquo;s instructions (temperatures, concentrations, and volume).\u003c/p\u003e\u003cp\u003eTherapeutic monoclonal antibodies were procured via a pharmaceutical procurement contract from commercial sources: Humira\u0026reg; (adalimumab) and two biosimilars, Yusimry\u0026reg; (adalimumab-aqvh), and Hadlima\u0026reg; (adalimumab-bwwd) pre-filled syringes or injector pens. Products in pre-filled syringes or pens were stored at 4\u0026deg;C until use. For clarity, Humira\u0026reg; is designated as the Reference adalimumab (Ref), Yusimry\u0026reg; as Biosimilar 1 (BS1), and Hadlima\u0026reg; as Biosimilar 2 (BS2).\u003c/p\u003e\u003cp\u003eLuminescence was measured on a SpectraMax iD3 multimode microplate reader (Molecular Devices) and acquired with SoftMax Pro v7.3.1 using the assay-specified luminescence settings. Data processing and curve fitting were performed in GraphPad Prism v10.4.2.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eReporter Gene Assay (TNF-α Neutralization)\u003c/h3\u003e\n\u003cp\u003e\u003cb\u003eCell seeding.\u003c/b\u003e Assay-ready A549-IkB cells were thawed and seeded into sterile, tissue culture treated 96-well plates at 9,600\u0026thinsp;\u0026minus;\u0026thinsp;10,000 cells/well and incubated at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e for 48 hours prior to assay.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAntibody and TNF-α preparation.\u003c/b\u003e On the assay day, serial dilutions of adalimumab were prepared in a separate 96-well dilution plate (two replicate rows per article). A fixed concentration of TNF-α (3.0 ng/mL) was added to each adalimumab dilution and pre-incubated for 30 minutes at room temperature. In parallel, a TNF-α activity curve was prepared by serially diluting TNF-α from 200 to 1.9x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e ng/mL using a 1:3 scheme.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssay Execution and Detection.\u003c/b\u003e Using a multi-channel pipette, 20 \u0026micro;L from each well of the dilution plate was transferred to the assay plate containing A549-IkB cells. Plates were incubated for 2-hours at room temperature. Detection reagents containing the complementary β-galactosidase fragment were added and incubated for 15 min, followed by addition of the β-galactosidase substrate and a 1-hour incubation to generate luminescence from the reconstituted active enzyme. Luminescence (RLU) was immediately read on the microplate reader (Molecular Devices) in the luminescence mode, reading for all wavelengths, at the endpoint read type, and analyzed with SoftMax Pro (v. 7.3.1) software.\u003c/p\u003e\n\u003ch3\u003eExperimental Design\u003c/h3\u003e\n\u003cp\u003eEach microplate constituted one assay run and was analyzed independently. For neutralization curves, adalimumab was tested at 11 concentrations spanning 10 \u0026micro;g/mL to 0.00051 \u0026micro;g/mL in the presence of 3.0 ng/mL TNF-α. Plate layouts included two replicate rows of serial dilutions for the Reference adalimumab, and two replicate rows for each test article, yielding pseudo-replicates at each concentration. Negative control wells contained 3.0 ng/mL TNF-α without adalimumab. Experiments were conducted in triplicate assay runs.\u003c/p\u003e\n\u003ch3\u003eModel Fitting\u003c/h3\u003e\n\u003cp\u003eWithin each plate, responses from pseudo-replicate wells at the same concentration were averaged prior to model fitting. Concentrations were log\u003csub\u003e10\u0026minus;\u003c/sub\u003etransformed, and averaged responses were fitted to a four-parameter logistic (4PL) model in GraphPad Prism (version 10.4.2). Outliers among within-run replicates were identified using the Grubbs test (two-sided, α\u0026thinsp;=\u0026thinsp;0.05). Curve quality was evaluated by the coefficient of determination (R\u0026sup2;) values.\u003c/p\u003e\u003cp\u003eFor TNF-α activity controls, 4PL fits of the TNF-α concentration-response curves were used to calculate the EC80 \u0026ndash; the TNF-α concentration eliciting 80% of the maximal response) for each run; EC80 values were trended as a surrogate of TNF-α activity and general system suitability for that run. Negative control wells were prepared without the addition of TNF-α.\u003c/p\u003e\u003cp\u003e\u003cb\u003eParallelism Assessment and Relative Potency.\u003c/b\u003e Parallelism between the Reference adalimumab and test samples within the same run was assessed by comparing unconstrained and constrained 4PL models via an F-test (α\u0026thinsp;=\u0026thinsp;0.05) in GraphPad Prism. In the unconstrained model, RLU vs log(mAb concentration) was fitted independently for each curve. In the constrained model, the reference and test curves were fitted simultaneously with shared Hill slope, top, and bottom asymptotes, while EC50 (or logEC50) parameters were allowed to differ. A p-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05 (α\u0026thinsp;=\u0026thinsp;0.05) from the F-test indicated no statistical differences between the curves, supporting curve parallelism or similarity. Under this condition, only the EC50 (or logEC50) values were allowed to vary, enabling percent relative potency calculation as the ratio of the reference EC50 to the test sample EC50, multiplied by 100.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eAssay Establishment and Readout\u003c/h2\u003e\u003cp\u003eWe adopted the PathHunter\u0026reg; Adalimumab Bioassay to quantify the neutralization of soluble TNF-α by reference adalimumab (Humira\u0026reg;) and biosimilars. The cell-based reporter system uses a β-galactosidase enzyme fragment complementation system in A549 cells overexpressing TNFR1 and IkB fused to a β-gal fragment. TNF-α binding to TNFR1 activates NF-kB triggering IkB degradation and disruption of the complementation complex; anti-TNF-α antibodies preserve IκB, reconstituting active β-gal and generating chemiluminescence proportional to TNF-α neutralization (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Method qualification emphasized working range, precision, and robustness, following ICH Q2(R2) and USP chapters\u0026thinsp;\u0026lt;\u0026thinsp;1032\u0026thinsp;\u0026gt;\u0026thinsp;and \u0026lt;\u0026thinsp;1034\u0026gt;.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eWorking Range and Specificity\u003c/h3\u003e\n\u003cp\u003eAn 11-point, serial dilution of reference adalimumab (6 replicate curves per run) produced a sigmoidal dose-response curve (DRC) well fit by a four-parameter logistic (4PL) model (R\u0026sup2; = 0.9839), with a Hill slope of 1.45 and EC50 of 57.55 ng/mL (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The response curves encompassed\u0026thinsp;\u0026ge;\u0026thinsp;3 points on the slope and \u0026ge;\u0026thinsp;4 points across the asymptotes. TNF-α-only wells (3 ng/mL) consistently exhibited low relative light units (RLU), aligning with the no-antibody asymptote (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003eTo standardize neutralization, TNF-α was fixed at 3 ng/mL in all antibody-containing wells, and each run included a TNF-α control curve. The TNF-α control (log-dosed) yielded a sigmoidal, negatively sloped 4PL fit (R\u0026sup2; = 0.9928) with decreasing luminescence at higher TNF-α (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Signal-to-background (S/B) ratios were comparable for anti-TNF-α and TNF-α control curves (9.57 vs 9.55, respectively).\u003c/p\u003e\u003cp\u003eSpecificity of the assay was demonstrated from the lack of apparent dose response curve from buffer and control wells. No DRC was observed for the buffer plus TNF-α wells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), and for buffer-only wells that lacked TNF-α and anti-TNF-α (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec).\u003c/p\u003e\n\u003ch3\u003ePrecision\u003c/h3\u003e\n\u003cp\u003ePrecision was assessed as repeatability (intra-assay) and intermediate precision (inter-assay). Intra-assay %CV, calculated from n\u0026thinsp;=\u0026thinsp;3 replicate EC50 values within a plate/run, ranged from 3% to 12% across runs. Intermediate precision, assessed across 3 independent runs and 2 instruments, showed %CVs of 19% and 13%, (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), indicating high between-run reproducibility.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrecision of the reporter gene assay (RGA) and comparison of 4PL parameter estimates and coefficients of variation between two plate readers. \u003cem\u003eEC\u003c/em\u003e\u003csub\u003e\u003cem\u003e50\u003c/em\u003e\u003c/sub\u003e, Hillslope, and S/B are based on validated data from three independent runs (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) per instrument, with each run comprising three technical replicate (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) dose\u0026ndash;response curves, comparing assay performance and parameter consistency across instruments. Percent coefficient of variation (%CV) for \u003cem\u003eEC₅₀\u003c/em\u003e values were assessed at both intra-assay (repeatability) and inter-assay (intermediate precision) levels.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePlate Reader\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParameter assessed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eEC50\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eHillslope\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003eS/B\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndependent run (Plate)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003emean (ng/mL)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntra-assay %CV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eInter-assay %CV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003emean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eIntra-assay %CV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eInter-assay %CV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003emean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eIntra-assay % CV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eInter-assay %CV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePR 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e19%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e17%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.988\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.975\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e9.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.989\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePR 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e13%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e9.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.985\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e9.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e12%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.969\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e8.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.979\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eInter-instrument %CV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eInter-instrument %CV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003eInter-instrument %CV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSystem Suitability\u003c/h2\u003e\u003cp\u003eSystem suitability (SST) criteria for reference adalimumab were established from n\u0026thinsp;=\u0026thinsp;20 independent runs (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). EC50 values spanned 36.78 to 63.22 ng/mL with a mean of 50.91\u0026thinsp;\u0026plusmn;\u0026thinsp;9.14 ng/mL; acceptance limits were set at \u0026plusmn;\u0026thinsp;2 SD (32.63\u0026ndash;69.19 ng/mL). Additional SST requirements were RLU %CV\u0026thinsp;\u0026le;\u0026thinsp;25%, S/B between 5.0 and 11.0, and Hill slope 1.0 to 1.8. Assay runs were considered valid only if all 4PL fitting parameters met these criteria; runs failing to meet these thresholds were excluded from further analysis.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSystem suitability and acceptance criteria. Summary of key parameters and predefined limits used to ensure assay reliability prior to relative potency determination for TNF-α neutralizing activity.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHistorical Results\u003c/p\u003e\u003cp\u003e\u003cem\u003eRange\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHistorical Results\u003c/p\u003e\u003cp\u003e\u003cem\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAcceptance criteria\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePrecision\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003einter-well\u003c/p\u003e\u003cp\u003e%CV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRLU CVs between replicate wells\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.4% \u0026minus;\u0026thinsp;24.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCV\u0026thinsp;\u0026le;\u0026thinsp;25% in the adalimumab range of 10,000\u0026ndash;0.51 ng/mL\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003einter-assay\u003c/p\u003e\u003cp\u003e%CV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEC50 CVs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u0026ndash;19%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;20%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e4PL parameter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHillslope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDRC Sigmoidal shape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.1\u0026ndash;1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.0\u0026ndash;1.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEC\u003csub\u003e50\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePotency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.78\u0026ndash;63.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50.91\u0026thinsp;\u0026plusmn;\u0026thinsp;9.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32.62\u0026ndash;69.19 ng/mL\u003c/p\u003e\u003cp\u003e(mean\u0026thinsp;\u003cem\u003e\u0026plusmn;\u0026thinsp;2xSD)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eS/B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTop asymptote signal/bottom signal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.0\u0026ndash;10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.34\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.0\u0026ndash;11.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCorrelation coefficient of constrained 4PL curve\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.945\u0026ndash;0.993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;0.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eRobustness\u003c/h2\u003e\u003cp\u003eMinor procedural variations were introduced to test robustness. Conditions tested were varying the TNF-α pre-incubation times (30min\u0026thinsp;\u0026plusmn;\u0026thinsp;15min) and a second plate reader instrument. Three independent runs were prepared wherein each run included two pseudo replicate rows of the 15-, 30-, and 45-min pre-incubated TNF-α and anti-TNF-α solution on the same plate. The pre-incubation times of 15, 30, or 45 minutes generated sigmoidal curves (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u0026ndash;c) with no overall statistical differences by F-test (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Supplementary Table S1). Nevertheless, all 15-min EC50 values fell outside the EC50 acceptance window, and two 15-min curves had R\u0026sup2; \u0026lt; 0.94. The 15-min condition also showed elevated variability in hillslope and S/B (%CV\u0026thinsp;=\u0026thinsp;41% and 29%, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed), indicating reduced reliability at shorter pre-incubation. In contrast, 30- and 45-min conditions met SST criteria. Performance on an alternate plate reader also met all SST limits; inter-instrument %CVs were 16% for EC50, 6% for Hill slope, and 14% for S/B (all \u0026le;\u0026thinsp;20%; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eApplications to Adalimumab Biosimilars\u003c/h2\u003e\u003cp\u003eTwo adalimumab biosimilars, BS1 and BS2, were evaluated using the validated bioassay. Three independent runs included two pseudo replicate rows of the reference product, BS1, and BS2 for each run on the same plate. Both biosimilars produced robust sigmoidal 4PL fits with unconstrained models (R\u0026sup2; \u0026ge; 0.94; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Parallelism to the reference product was confirmed using constrained models sharing hillslope and asymptotes. F-tests revealed no statistical difference (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all comparisons; Supplementary Table S2). Relative potencies were 103% (BS1) and 96% (BS2) compared to the reference adalimumab, both within the predefined acceptance interval for this reporter gene assay.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eBioassays are central to the quality control of therapeutic proteins because they quantify biological function in a MOA\u0026ndash;relevant context, complementing physicochemical tests that probe isolated attributes. Reporter gene assays (RGAs) are particularly well suited to TNF inhibitors, as engineered cells convert TNF-α\u0026ndash;driven signaling into a sensitive luminescent output that integrate ligand binding, pathway modulation, and downstream response in a single measurement (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In this study, we established and partially validated a β-galactosidase enzyme-fragment complementation RGA using A549-TNFR1/IκB-β-gal cells to measure neutralization of soluble TNF-α by adalimumab and its biosimilars, following ICH Q2(R2) and USP\u0026thinsp;\u0026lt;\u0026thinsp;1032\u0026gt;/\u0026lt;1034\u0026gt;.\u003c/p\u003e\u003cp\u003eThe assay demonstrated an excellent working range, with 4PL fits capturing multiple informative points along the slope and asymptotes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, c). Inclusion of a TNF-α control curve in every run standardized the neutralization context (fixed TNF-α at 3 ng/mL), verified reagent activity, and anchored the upper signal ceiling (TNF-α\u0026ndash;negative wells), which can vary with cell density and run-to-run factors. Collectively, these design features support reliable quantitation across the expected potency range.\u003c/p\u003e\u003cp\u003ePrecision performance was robust across study tiers. Repeatability (%CV) and intermediate precision (average %CV) confirmed stable EC50 estimates within and across plates and days (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Inter-instrument assessments further showed that EC50 and S/B parameters had %CV values of \u0026le;\u0026thinsp;20% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), underscoring the method\u0026rsquo;s portability. Such precision meets expectations for quantitative cell-based assays intended for routine use and reduces the likelihood of false trends during product life-cycle monitoring.\u003c/p\u003e\u003cp\u003eSST anchored day-to-day assay governance to historical performance. From \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20 runs, the reference adalimumab EC50 distribution (mean\u0026thinsp;\u0026asymp;\u0026thinsp;50.9 ng/mL) defined acceptance limits at \u0026plusmn;\u0026thinsp;2 SD (32.6\u0026ndash;69.2 ng/mL), complemented by criteria for RLU %CV\u0026thinsp;\u0026le;\u0026thinsp;25%, S/B between 5.0 and 11.0, and Hill slope 1.0\u0026ndash;1.8 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although the coefficient of determination (R\u0026sup2;) was not a formal SST criterion, it was monitored as a quality indicator. Runs with low R\u0026sup2; typically coincided with out-of-window EC50 or atypical slope and were excluded, demonstrating the value of multiple, orthogonal SST elements. This framework provides operational resilience while avoiding over-constraint that could otherwise reject biologically acceptable runs.\u003c/p\u003e\u003cp\u003eRobustness tests defined practical boundaries for execution. Varying the TNF-α pre-incubation duration showed that 30\u0026ndash;45 min maintained EC50 values within SST limits and yielded consistent 4PL fits, whereas 15 min introduced excessive variability (%CVs increased in slope and S/B; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Supplementary Table S1). These findings support a\u0026thinsp;\u0026ge;\u0026thinsp;30-min pre-incubation as the recommended condition. Importantly, performance on an alternate plate reader also met all SST criteria (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), indicating that the method tolerates reasonable differences in detection systems when governed by SST.\u003c/p\u003e\u003cp\u003eFurther studies demonstrated the bioassay\u0026rsquo;s applicability for evaluating biosimilars. Both BS1 and BS2 produced sigmoidal dose\u0026ndash;response curves with excellent 4PL fits (R\u0026sup2; \u0026ge; 0.94) and satisfied parallelism criteria relative to the reference product using constrained models (shared slope and asymptotes; F-tests \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Supplementary Table S2). The relative potencies were 103% (BS1) and 96% (BS2), each within the predefined acceptance interval for this reporter gene assay (80\u0026ndash;137%). Although only a limited number of lots were tested, these findings support the utility of the bioassay\u0026rsquo;s suitability for biosimilar development and warrant further studies to evaluate its stability-indicating capability using stressed samples, such as those exposed to heat or light.\u003c/p\u003e\u003cp\u003eThe platform\u0026rsquo;s MOA relevance and modular features suggest adaptability across the TNF inhibitor class. With appropriate qualification such as re-establishing SST limits, verifying parallelism, and confirming TNF-α control behavior, the same cellular backbone and readout can be extended to other TNF-targeted biologics (e.g., infliximab, etanercept, certolizumab pegol, golimumab) and their biosimilars. A unified, mechanism-relevant bioassay strategy may streamline development, facilitate bridging across manufacturing changes, and support regulatory comparability submissions.\u003c/p\u003e\u003cp\u003eThis work also clarifies the assay\u0026rsquo;s scope and technical considerations. The readout specifically reflects neutralization of soluble TNF-α via TNFR1-linked NF-κB signaling in A549 cells and does not directly assess interactions with transmembrane TNF or off-pathway mechanisms. Because cell-based assays are inherently sensitive to biological variables such as passage number, plating density, and cytokine lot, rigorous control of cell health, inclusion of TNF-α activity controls, and continuous control charting of EC50, slope, and S/B are essential. In practice, orthogonal methods such as ligand binding or targeted physicochemical analyses, should be integrated into a comprehensive control strategy, with the RGA serving as the primary functional readout.\u003c/p\u003e\u003cp\u003eIn summary, the qualified RGA is fit-for-purpose to quantify the functional activity of adalimumab and its biosimilars. Its demonstrated precision, robustness to operational variables, and SST-guided performance, combined with strong MOA relevance, support its use for lot release and comparability testing (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). When applied alongside orthogonal analytics, this platform strengthens the quality framework for TNF-α inhibitors and enables consistent, clinically relevant potency control throughout the product life cycle.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of assay parameters tested and acceptance criteria for this reporter gene assay.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAcceptance criteria\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass/Fail\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eSpecificity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo dose response curve (DRC) must be observed from wells with buffer, with TNF-α, without anti-TNF-α\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo DRC must be observed from wells with buffer and without TNF-α\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePrecision\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRepeatability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIntra-assay %CV of EC50 values must be less than 15% for each independent run\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntermediate Precision\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInter-assay %CV of EC50 values must be less than 20%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e\u003cp\u003eWorking Range\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eS/B of the DRC should be between 5.0\u0026ndash;11.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSlope of the DRC should be within 1.0\u0026ndash;1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe coefficient of correlation (R\u003csup\u003e2\u003c/sup\u003e) of the DRC when fit to a 4PL model must be \u0026gt;\u0026thinsp;or equal to 0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eRobustness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAssay must perform within SST and precision limits in an alternate plate reader\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePre-incubation times of 30\u0026ndash;45 min must result in 4PL values within SST limits and %CV range\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eParallelism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe F-test (4PL 3-parameter constrained fitting) comparisons between DRCs must result in a p-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05 to determine % relative potency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSystem Suitability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAll assay system suitability criteria are met\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e4PL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFour-Parameter Logistic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecoefficient of variation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDRC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003edose response curve\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEC50\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehalf maximal effective concentration\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFDA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFood and Drug Administration\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIκB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInhibitor kappa B\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMoA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emechanism of action\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNF-κB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enuclear factor kappa B\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRGA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ereporter gene assay\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRLU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003erelative luminescence unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRelative Potency\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecoefficient of determination\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eS/B\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003esignal-to-background ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003estandard deviation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSST\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003esystem suitability\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTNF-α\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etumor necrosis factor-alpha\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTNFR1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etumor necrosis factor receptor.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Drs. David Keire and Sarah Rogstad for critical review of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by FDA’s intramural research program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflicts of interest were disclosed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, B.Z.; Data acquisition and analysis, C.F.A.; Sample preparation: C.F.A., S.L.; Writing – Original Draft: B.Z. and C.F.A.; Writing – Review \u0026amp; Editing, all authors; Supervision, B.Z.;\u0026nbsp;All authors have read and approved the final version of the manuscript. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this manuscript are included within the article and its cited references, all of which are publicly available.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclaimer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe views expressed in this article are those of the authors and are based on experimental data and a review of relevant scientific literature. These views should not be construed to represent FDA’s views or policies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBain B, Brazil M. Adalimumab. Nat Rev Drug Discov. 2003;2(9):693-94.\u003c/li\u003e\n \u003cli\u003eCroft M, Salek-Ardakani S, Ware CF. Targeting the TNF and TNFR superfamilies in autoimmune disease and cancer. Nat Rev Drug Discov. 2024;23(12):939-61.\u003c/li\u003e\n \u003cli\u003eBurmester GR, Gordon KB, Rosenbaum JT, Arikan D, Lau WL, Li P, et al. Long-Term Safety of Adalimumab in 29,967 Adult Patients From Global Clinical Trials Across Multiple Indications: An Updated Analysis. Advances in Therapy. 2020;37(1):364-80.\u003c/li\u003e\n \u003cli\u003eLu X, Hu R, Peng L, Liu M, Sun Z. Efficacy and Safety of Adalimumab Biosimilars: Current Critical Clinical Data in Rheumatoid Arthritis. Frontiers in Immunology. 2021;Volume 12 \u0026ndash; 2021.\u003c/li\u003e\n \u003cli\u003eHuizinga TWJ, Torii Y, Muniz R. Adalimumab Biosimilars in the Treatment of Rheumatoid Arthritis: A Systematic Review of the Evidence for Biosimilarity. Rheumatol Ther. 2021;8(1):41-61.\u003c/li\u003e\n \u003cli\u003eAscef BdO, Almeida MO, Medeiros-Ribeiro ACd, Oliveira de Andrade DC, Oliveira Junior HAd, de So\u0026aacute;rez PC. Therapeutic Equivalence of Biosimilar and Reference Biologic Drugs in Rheumatoid Arthritis: A Systematic Review and Meta-analysis. JAMA Network Open. 2023;6(5):e2315872-e.\u003c/li\u003e\n \u003cli\u003eAbitbol V, Benkhalifa S, Habauzit C, Marotte H. Navigating adalimumab biosimilars: an expert opinion. J Comp Eff Res. 2023;12(11):e230117.\u003c/li\u003e\n \u003cli\u003eAllegretti JR, Brady JH, Wicker A, Latymer M, Wells A. Relevance of Adalimumab Product Attributes to Patient Experience in the Biosimilar Era: A Narrative Review. Advances in Therapy. 2024;41(5):1775-94.\u003c/li\u003e\n \u003cli\u003eBaldisseri D, Luo S, Ancajas CAF, Ortega-Rodriguez U, Fischer C, Zou G, et al. NMR-based structural integrity analysis of therapeutic monoclonal antibodies: a comparative study of Humira and its biosimilars. mAbs. 2025;17(1):2551208.\u003c/li\u003e\n \u003cli\u003eU.S. Food and Drug Administration Draft Guidance for Industry (2019): Development of Therapeutic Protein Biosimilars: Comparative Analytical Assessment and Other Quality-Related Considerations. Available from: https://www.fda.gov/drugs/drug-safety-and-availability/fda-issues-draft-guidance-industry-design-and-evaluation-comparative-analytical-studies.\u003c/li\u003e\n \u003cli\u003eNupur N, Joshi S, Gulliarme D, Rathore AS. Analytical Similarity Assessment of Biosimilars: Global Regulatory Landscape, Recent Studies and Major Advancements in Orthogonal Platforms. Frontiers in Bioengineering and Biotechnology. 2022;Volume 10 - 2022.\u003c/li\u003e\n \u003cli\u003eMarkus R, McBride HJ, Ramchandani M, Chow V, Liu J, Mytych D, et al. A Review of the Totality of Evidence Supporting the Development of the First Adalimumab Biosimilar ABP 501. Advances in Therapy. 2019;36(8):1833-50.\u003c/li\u003e\n \u003cli\u003eMill\u0026aacute;n-Mart\u0026iacute;n S, Jakes C, Carillo S, Bones J. Multi-attribute method (MAM) to assess analytical comparability of adalimumab biosimilars. Journal of Pharmaceutical and Biomedical Analysis. 2023;234:115543.\u003c/li\u003e\n \u003cli\u003eJiang Y, Arora T, Klakamp S, Davis J, Chandrasekher YA, Young G, et al. Demonstration of Physicochemical and Functional Similarity of Biosimilar Adalimumab-aqvh to Adalimumab. Drugs R D. 2023;23(4):377-95.\u003c/li\u003e\n \u003cli\u003eWadhwa M, Bird C, Atkinson E, Cludts I, Rigsby P. The First WHO International Standard for Adalimumab: Dual Role in Bioactivity and Therapeutic Drug Monitoring. Frontiers in Immunology. 2021;Volume 12 - 2021.\u003c/li\u003e\n \u003cli\u003eCamacho-Sandoval R, Sosa-Grande EN, Gonz\u0026aacute;lez-Gonz\u0026aacute;lez E, Tenorio-Calvo A, L\u0026oacute;pez-Morales CA, Velasco-Vel\u0026aacute;zquez M, et al. Development and validation of a bioassay to evaluate binding of adalimumab to cell membrane-anchored TNF\u0026alpha; using flow cytometry detection. Journal of Pharmaceutical and Biomedical Analysis. 2018;155:235-40.\u003c/li\u003e\n \u003cli\u003eKhabar KSA, Siddiqui S, Armstrong JA. WEHI-13VAR: a stable and sensitive variant of WEHI 164 clone 13 fibrosarcoma for tumor necrosis factor bioassay. Immunology Letters. 1995;46(1):107-10.\u003c/li\u003e\n \u003cli\u003eMinafra L, Di Cara G, Albanese NN, Cancemi P. Proteomic differentiation pattern in the U937 cell line. Leukemia Research. 2011;35(2):226-36.\u003c/li\u003e\n \u003cli\u003eTwomey JD, George S, Zhang B. Fc gamma receptor polymorphisms in antibody therapy: implications for bioassay development to enhance product quality. Antib Ther. 2025;8(2):87-98.\u003c/li\u003e\n \u003cli\u003eUSP 〈1032〉 Design and Development of Biological Assays. In USP-NF. Rockville, MD: United States Pharmacopeia; DOI: https://doi.usp.org/USPNF/USPNF_M1354_01_01.html\u003c/li\u003e\n \u003cli\u003eUSP \u0026lt;1034\u0026gt; Analysis of Biological Assays. In USP-NF. Rockville, MD: United States Pharmacopeia; DOI: https://doi.usp.org/USPNF/USPNF_M5677_01_01.html\u003c/li\u003e\n \u003cli\u003eInternational Conference on Harmonization (ICH) guidelines Q2(R2) Validation of Analytical Procedures, March 2022; https://www.fda.gov/regulatory-information/search-fda-guidance-documents/q2r2-validation-analytical-procedures\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"United States Food and Drug Administration","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"adalimumab (Humira), TNF-α neutralization, reporter gene assay, bioassay qualification","lastPublishedDoi":"10.21203/rs.3.rs-8273462/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8273462/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e To qualify a mechanism‑of‑action (MoA)–reflective reporter gene assay (RGA) for measuring the biological activity of adalimumab (Humira) and its biosimilars, supporting assessment of product quality, comparability, and functional consistency across the product lifecycle.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The assay evaluates TNF‑α neutralization by monitoring inhibition of NF‑κB signaling in a reporter system. Qualification focused on key performance attributes, including system suitability, working range, reproducibility, and intermediate precision, to confirm fitness for routine use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The RGA yielded MoA‑relevant readouts of NF‑κB pathway inhibition in the presence of adalimumab, demonstrating strong system suitability, a broad working range, high reproducibility, and consistent intermediate precision across repeated measures. These characteristics support reliable measurement of functional activity among adalimumab products and biosimilars.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e The qualified, MoA‑reflective RGA provides a robust tool for lifecycle management of adalimumab products, enabling quality assessment, comparability exercises, and monitoring of functional consistency across indications in which adalimumab is broadly used (e.g., rheumatoid arthritis, Crohn’s disease, psoriasis).\u003c/p\u003e","manuscriptTitle":"A Cell-Based Reporter Gene Assay for TNF-α Neutralization: Analytical Qualification and Application to Adalimumab and Its Biosimilars","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-05 07:32:16","doi":"10.21203/rs.3.rs-8273462/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"72ab251f-40e4-4911-9586-fb91c6b40b5a","owner":[],"postedDate":"December 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59053765,"name":"Analytical Biochemistry"},{"id":59053766,"name":"Biochemical Research Methods"},{"id":59053767,"name":"Drug Discovery, Design, \u0026 Development"},{"id":59053768,"name":"Biotechnology and Bioengineering"},{"id":59053769,"name":"Cell Communication and Signaling"},{"id":59053770,"name":"Allergy \u0026 Immune Disorders"},{"id":59053771,"name":"Immunology"},{"id":59053772,"name":"Translational Medicine"}],"tags":[],"updatedAt":"2025-12-05T07:32:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-05 07:32:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8273462","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8273462","identity":"rs-8273462","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}