Optimization of an indirect ELISA to assess the unwanted immunogenicity of Heberprot-P®
Keywords:
ELISA, full factorial design, Heberprot-P®, optimizationAbstract
Introduction: Despite its wide use in clinical practice, the immunogenicity of Heberprot-P® and its influence on the efficacy and safety of this drug is unknown. To obtain this information, an immunoassay that detects physiologically relevant levels of specific antibodies needs to be optimized.
Objective: To optimize, by means of a complete factorial design, step by step, a semi- quantitative indirect ELISA, to evaluate the undesired immunogenicity against Heberprot-P® in serum of treated patients.
Method: From an initial ELISA, different factors and levels were evaluated, using complete factorial designs, in four steps of the assay: plate coating, binding of antigen-antibody, antibody-conjugate, and enzyme-substrate. The best combination of factors and levels in a step was incorporated to optimize the next one. The experimental design conceived a simple statistical processing.
Results: The optimized ELISA demonstrated the specificity of the assay and achieved antibody detectability 17 times higher than the initial one.
Conclusions: The step-by-step optimization of the ELISA, through a complete factorial design, and the successive incorporation into the protocol of the best combination of factors and levels, allows obtaining a specific immunoassay with greater detectability of specific antibodies. The experimental design linked to a simple statistical processing facilitates the interpretation of the results, especially in those laboratories where there is no qualified statistical advice.
Downloads
References
1. Immunogenicity Testing of Therapeutic Protein Products —Developing and Validating Assays for Anti-Drug Antibody Detection. Guidance for Industry. U.S. Department of Health and Human Services. Food and Drug Administration, 2019. [citado 5 Jun 2023]. Disponible en: https://www.fda.gov/media/119788/download
2. Bioanalytical Method Validation. Guidance for Industry. US Department of Health and Human Services. Food and Drug Administration, 2018. [citado 5 Jun 2023]. Disponible en: https://www.fda.gov/files/drugs/published/Bioanalytical-Method-Validation-Guidance-for-Industry.pdf
3. Fernández-Montequín JI, Valenzuela-Silva CM, Díaz OG, Savigne W, Sancho-Soutelo N, Rivero-Fernández F, et al. Cuban Diabetic Foot Study Group. Intra-lesional injections of recombinant human epidermal growth factor promote granulation and healing in advanced diabetic foot ulcers: multicenter, randomised, placebo-controlled, double-blind study. Int Wound J 2009; 6(6):432-443. http://dx.doi.org/10.1111/j.1742-481X.2009.00641.x
4. Bui TQ, Bui QVP, Németh D, Hegyi P, Szakács Z, Rumbus Z, et al. Epidermal Growth Factor is Effective in the Treatment of Diabetic Foot Ulcers: Meta-Analysis and Systematic Review. Int J Environ Res Public Health 2019; 16(14):2584. http://dx.doi.org/10.3390/ijerph16142584
5. Minic R, Zivkovic I. Optimization, validation and standardization of ELISA. Norovirus 2020; 9-28.
6. Cowan KJ, Erickson R, Sue B, Delarosa R, Gunter B, Coleman DA, et al. Utilizing design of experiments to characterize assay robustness. Bioanalysis 2012; 4(17):2127-2139. http://dx.doi.org/10.4155/bio.12.199
7. Shah K, Maghsoudlou P. Enzyme-linked immunosorbent assay (ELISA): the basics. Br J Hosp Med (Lond) 2016; 77(7):98-101. http://dx.doi.org/10.12968/hmed.2016.77.7.C98
8. Augustine SAJ, Simmons KJ, Eason TN, Griffin SM, Curioso CL, Wymer LJ, et al. Statistical approaches to developing a multiplex immunoassay for determining human exposure to environmental pathogens. J Immunol Methods 2015; 425:1-9. http://dx.10.1016/j.jim.2015.06.002
9. Khuri AI, Mukhopadhyay S. Response surface methodology. WIREs Comp Stat 2010; 2:128-149. http://dx.doi.org/10.1002/wics.73
10. Papaneophytou C. Design of experiments as a tool for optimization in recombinant protein biotechnology: from constructs to crystals. Mol Biotechnol 2019; 61(12):873-891. http://dx.doi.org/10.1007/s12033-019-00218-x
11. Ray CA, Patel V, Shih J, Macaraeg C, Wu Y, Thway T, et al. Application of multi-factorial design of experiments to successfully optimize immunoassays for robust measurements of therapeutic proteins. J Pharm Biomed Anal 2009; 49(2):311-318. http://dx.doi.org/10.1016/j.jpba.2008.11.039
12. Hernández CA, Pérez-Bernal M, Abreu D, Valdivia O, Delgado M, Dorta D, et al. Step-by-step full factorial design to optimize a quantitative sandwich ELISA. Anal Biochem 2023; 674, 115195. https://doi.org/10.1016/j.ab.2023.115195
13. Crombet Ramos T, Rodríguez PC, Neninger Vinageras E, Garcia Verdecia B, Lage Davila A. CIMAvax EGF (EGF-P64K) vaccine for the treatment of non-small-cell lung cancer. Expert Rev Vaccines 2015; 14(10):1303-1311. http://dx.doi.org/10.1586/14760584.2015.1079488
14. DeSilva B, Smith W, Weiner R, Kelley M, Smolec J, Lee B, et al. Recommendations for the bioanalytical method validation of ligand-binding assays to support pharmacokinetic assessments of macromolecules. Pharm Res 2003; 20(11):1885-900. http://dx.doi.org/10.1023/b:pham.0000003390.51761.3d
15. Altekar M, Homon CA, Kashem MA, Mason SW, Nelson RM, Patnaude LA, et al. Assay optimization: a statistical design of experiments approach. Clin Lab Med 2007; 27(1):139-54. http://dx.doi.org/10.1016/j.cll.2007.01.001
Downloads
Published
How to Cite
Issue
Section
License
Aquellos autores/as que tengan publicaciones con esta revista, aceptan los términos siguientes: Los autores/as conservarán sus derechos de autor y garantizarán a la revista el derecho de primera publicación de su obra, el cuál estará simultáneamente sujeto a la Licencia de reconocimiento de Creative Commons (CC-BY-NC 4.0) que permite a terceros compartir la obra siempre que se indique su autor y su primera publicación esta revista. Los autores/as podrán adoptar otros acuerdos de licencia no exclusiva de distribución de la versión de la obra publicada (p. ej.: depositarla en un archivo telemático institucional o publicarla en un volumen monográfico) siempre que se indique la publicación inicial en esta revista. Se permite y recomienda a los autores/as difundir su obra a través de Internet (p. ej.: en archivos telemáticos institucionales o en su página web) antes y durante el proceso de envío, lo cual puede producir intercambios interesantes y aumentar las citas de la obra publicada. (Véase El efecto del acceso abierto).
Como Revista Cubana de Investigaciones Biomédicas forma parte de la red SciELO, una vez los artículos sean aceptados para entrar al proceso editorial (revisión), estos pueden ser depositados por parte de los autores, si estan de acuerdo, en SciELO preprints, siendo actualizados por los autores al concluir el proceso de revisión y las pruebas de maquetación.
