The AAPS Journal

, 22:1 | Cite as

Phase-Appropriate Application of Analytical Methods to Monitor Subvisible Particles Across the Biotherapeutic Drug Product Life Cycle

  • Roman MathaesEmail author
  • Linda Narhi
  • Andrea Hawe
  • Anja Matter
  • Karoline Bechtold-Peters
  • Sophia Kenrick
  • Sambit Kar
  • Olga Laskina
  • John Carpenter
  • Richard Cavicchi
  • Ellen Koepf
  • E. Neil Lewis
  • Rukman De Silva
  • Dean Ripple
White Paper


The phase-appropriate application of analytical methods to characterize, monitor, and control particles is an important aspect of the development of safe and efficacious biotherapeutics. The AAPS Product Attribute and Biological Consequences (PABC) focus group (which has since transformed into an AAPS community) conducted a survey where participating labs rated their method of choice to analyze protein aggregation/particle formation during the different stages of the product life cycle. The survey confirmed that pharmacopeial methods and SEC are the primary methods currently applied in earlier phases of the development to ensure that a product entering clinical trials is safe and efficacious. In later phases, additional techniques are added including those for non-GMP extended characterization for product and process characterization. Finally, only robust, globally-accepted, and stability-indicating methods are used for GMP quality control purposes. This was also consistent with the feedback during a webinar hosted by the group to discuss the survey results. In this white paper, the team shares the results of the survey and provides guidance on selecting phase-appropriate analytical methods and developing a robust particle control strategy.


subvisible particles protein aggregation control strategy biotech drug product 



American Association of Pharmaceutical Scientists


Affinity-capture self-interaction nanoparticle spectroscopy


Asymmetric flow field flow fractionation


Analytical ultracentrifugation


Circular dichroism


Capillary isoelectric focusing


Critical quality attribute


Dynamic light scattering


Food and Drug Administration


First in Human


Fourier-transform-infrared spectroscopy


Good manufacturing practice


International Conference of Harmonization


Japanese Pharmacopeia


Light obscuration


Multi angle light scattering


Micro differential scanning calorimetry


Nano differential scanning fluorimetry


Nanotracking analysis


Out of specification


Product Attribute and Biological Consequences

Ph. Eur.

European Pharmacopeia


Quality control


Resonant mass measurement


Reversed-phase high-pressure liquid chromatography


Subvisible particles


Size exclusion chromatography


Scanning electron microscopy–energy dispersive X-ray


Static light scattering


Thermal denaturation assay


Transmission electron microscopy


Time-of-flight secondary ion mass spectroscopy


United States Pharmacopeia


Visible particles



  1. 1.
    Corvari V, et al. Subvisible (2–100 μm) particle analysis during biotherapeutic drug product development: part 2, experience with the application of subvisible particle analysis. Biologicals. 2015;43(6):457–73.CrossRefPubMedGoogle Scholar
  2. 2.
    Singh SK, et al. An industry perspective on the monitoring of subvisible particles as a quality attribute for protein therapeutics. J Pharm Sci. 2010;99(8):3302–21.CrossRefPubMedGoogle Scholar
  3. 3.
    Narhi LO, et al. A critical review of analytical methods for subvisible and visible particles. Curr Pharm Biotechnol. 2009;10(4):373–81.CrossRefPubMedGoogle Scholar
  4. 4.
    Zölls S, et al. Particles in therapeutic protein formulations, part 1: overview of analytical methods. J Pharm Sci. 2012;101(3):914–35.CrossRefPubMedGoogle Scholar
  5. 5.
    Joubert MK, et al. Classification and characterization of therapeutic antibody aggregates. J Biol Chem. 2011: p. jbc;M110:160457.Google Scholar
  6. 6.
    Roberts CJ. Protein aggregation and its impact on product quality. Curr Opin Biotechnol. 2014;30:p211–7.CrossRefGoogle Scholar
  7. 7.
    Filipe V, et al. Transient molten globules and metastable aggregates induced by brief exposure of a monoclonal IgG to low pH. J Pharm Sci. 2012;101(7):2327–39.CrossRefPubMedGoogle Scholar
  8. 8.
    Bhirde AA, et al. High-throughput in-use and stress size stability screening of protein therapeutics using algorithm-driven dynamic light scattering. J Pharm Sci. 2018 Aug;107(8):2055–62.CrossRefPubMedGoogle Scholar
  9. 9.
    Menzen T, Friess W. High-throughput melting-temperature analysis of a monoclonal antibody by differential scanning fluorimetry in the presence of surfactants. J Pharm Sci. 2013;102(2):415–28.CrossRefPubMedGoogle Scholar
  10. 10.
    Koepf E, et al. The missing piece in the puzzle: prediction of aggregation via the protein-protein interaction parameter A∗ 2. Eur J Pharm Biopharm. 2018;128:200–9.CrossRefPubMedGoogle Scholar
  11. 11.
    Zidar M, et al. High throughput prediction approach for monoclonal antibody aggregation at high concentration. Pharm Res. 2017;34(9):1831–9.CrossRefPubMedGoogle Scholar
  12. 12.
    Geoghegan JC, et al. Mitigation of reversible self-association and viscosity in a human IgG1 monoclonal antibody by rational, structure-guided Fv engineering. in MAbs. 2016. Taylor & Francis.Google Scholar
  13. 13.
    DeSilva R. USP workshop on visible and subvisible particulate matter in biologics. 2017.Google Scholar
  14. 14.
    Harris, R., Prologue: prior knowledge and smart risks. AAPS PharmSci360, 2018.Google Scholar
  15. 15.
    Guideline, I.H.T. Validation of analytical procedures: text and methodology Q2 (R1). in International conference on harmonization, Geneva, Switzerland. 2005.Google Scholar
  16. 16.
    ICH, Q. Pharmaceutical Development, International Conference on Harmonisation. 2009.Google Scholar
  17. 17.
    Harazono A, et al. Interlaboratory comparison about feasibility of insoluble particulate matter test for injections with reduced test volume in light obscuration method. Biologicals. 2019;57:46–9.CrossRefPubMedGoogle Scholar
  18. 18.
    Quiroz AR, et al. Factors governing the precision of subvisible particle measurement methods–a case study with a low-concentration therapeutic protein product in a prefilled syringe. Pharm Res. 2016;33(2):450–61.CrossRefGoogle Scholar
  19. 19.
    Quiroz AR, et al. Factors governing the accuracy of subvisible particle counting methods. J Pharm Sci. 2016;105(7):2042–52.CrossRefGoogle Scholar
  20. 20.
    Kiyoshi M, et al. Collaborative study for analysis of subvisible particles using flow imaging and light obscuration: experiences in Japanese biopharmaceutical consortium. J Pharm Sci. 2019;108(2):832–41.CrossRefPubMedGoogle Scholar
  21. 21.
    Kirshner S. Regulatory expectations for analysis of aggregates and particles. in Talk at workshop on protein aggregation and immunogenicity. 2014. Breckenridge Colorado.Google Scholar
  22. 22.
    Ripple DC, Hu Z. Correcting the relative bias of light obscuration and flow imaging particle counters. Pharm Res. 2016;33(3):653–72.CrossRefPubMedGoogle Scholar
  23. 23.
    Mathonet S, et al. A biopharmaceutical industry perspective on the control of visible particles in biotechnology-derived injectable drug products. PDA J Pharm Sci Technol. 2016;70(4):392–408.CrossRefPubMedGoogle Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2019

Authors and Affiliations

  • Roman Mathaes
    • 1
    Email author
  • Linda Narhi
    • 2
  • Andrea Hawe
    • 3
  • Anja Matter
    • 1
  • Karoline Bechtold-Peters
    • 4
  • Sophia Kenrick
    • 5
  • Sambit Kar
    • 6
  • Olga Laskina
    • 7
  • John Carpenter
    • 8
  • Richard Cavicchi
    • 9
  • Ellen Koepf
    • 10
  • E. Neil Lewis
    • 11
  • Rukman De Silva
    • 12
  • Dean Ripple
    • 9
  1. 1.Lonza Drug Product ServicesBaselSwitzerland
  2. 2.Amgen, IncThousand OaksUSA
  3. 3.Coriolis PharmaMartinsriedGermany
  4. 4.NovartisBaselSwitzerland
  5. 5.Wyatt Technology CorporationSanta BarbaraUSA
  6. 6.Molecular and Analytical DevelopmentBristol-Myers SquibbPenningtonUSA
  7. 7.West Pharmaceutical Services, Inc.ExtonUSA
  8. 8.University of ColoradoDenverUSA
  9. 9.National Institute of Standards and TechnologyGaithersburgUSA
  10. 10.Commercial Product Support, Innovation and Investments, Pharmaceutical Development & SuppliesPTD Biologics Europe. F. Hoffmann-La Roche LtdBaselSwitzerland
  11. 11.Mettler-Toledo, Autochem, Inc.RedmondUSA
  12. 12.U.S. Food and Drug AdministrationSilver SpringUSA

Personalised recommendations