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. 2021 Dec 1;24(1):4.
doi: 10.1208/s12248-021-00649-y.

Anti-drug Antibody Validation Testing and Reporting Harmonization

Heather Myler  1 , João Pedras-Vasconcelos  2 , Kelli Phillips  3 , Charles Scott Hottenstein  4 , Paul Chamberlain  5 , Viswanath Devanaryan  6 , Carol Gleason  7 , Joanne Goodman  8 , Marta Starcevic Manning  9 , Shobha Purushothama  10 , Susan Richards  11 , Honglue Shen  12 , Jad Zoghbi  11 , Lakshmi Amaravadi  13 , Troy Barger  9 , Steven Bowen  2 , Ronald R Bowsher  14 , Adrienne Clements-Egan  15 , Dong Geng  16 , Theresa J Goletz  17 , George R Gunn  4 , William Hallett  2 , Michael E Hodsdon  18 , Brian M Janelsins  2 , Vibha Jawa  19 , Szilard Kamondi  20 , Susan Kirshner  2 , Daniel Kramer  21 , Meina Liang  22 , Kathryn Lindley  23 , Susana Liu  24 , ZhenZhen Liu  2 , Jim McNally  23 , Alvydas Mikulskis  25 , Robert Nelson  26 , Mohsen Rajabi Ahbari  27 , Qiang Qu  28 , Jane Ruppel  29 , Veerle Snoeck  30 , An Song  31 , Haoheng Yan  2 , Mark Ware  15
Affiliations

Anti-drug Antibody Validation Testing and Reporting Harmonization

Heather Myler et al. AAPS J. .

Abstract

Evolving immunogenicity assay performance expectations and a lack of harmonized anti-drug antibody validation testing and reporting tools have resulted in significant time spent by health authorities and sponsors on resolving filing queries. Following debate at the American Association of Pharmaceutical Sciences National Biotechnology Conference, a group was formed to address these gaps. Over the last 3 years, 44 members from 29 organizations (including 5 members from Europe and 10 members from FDA) discussed gaps in understanding immunogenicity assay requirements and have developed harmonization tools for use by industry scientists to facilitate filings to health authorities. Herein, this team provides testing and reporting strategies and tools for the following assessments: (1) pre-study validation cut point; (2) in-study cut points, including procedures for applying cut points to mixed populations; (3) system suitability control criteria for in-study plate acceptance; (4) assay sensitivity, including the selection of an appropriate low positive control; (5) specificity, including drug and target tolerance; (6) sample stability that reflects sample storage and handling conditions; (7) assay selectivity to matrix components, including hemolytic, lipemic, and disease state matrices; (8) domain specificity for multi-domain therapeutics; (9) and minimum required dilution and extraction-based sample processing for titer reporting.

Keywords: Anti-drug antibodies (ADA); FDA; Immunogenicity; Neutralizing antibodies (NAb); Regulatory guidance; Validation.

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Figures

Figure 1
Figure 1
Pre-study validation normal healthy (NH) and in-study disease state (DS) screening sample RLU/NC RLU ratios with the means significantly different and variances not significantly different. Applying the validation screening cut point factor (SCPF) of 1.09 results in the in-study false positive rate of 10%. As this is within a 2 to 11% criteria, the validation SCPF can be used for testing the in-study samples. RLU indicates relative light unit. NC indicates negative control
Figure 2
Figure 2
Pre-study validation NH and in-study DS screening sample RLU/NC RLU ratios with means not significantly different and variances significantly different. Applying the validation screening cut point factor (SCPF) of 1.50 results in the in-study false positive rate of 0%, thus requiring the application of an in-study cut point. RLU indicates relative light unit. NC indicates negative control
Figure 3
Figure 3
Comparison of in-study baseline samples from multiple disease states (DS) sample RLU/NC RLU ratios. SCPF indicates screening cut point factor. RLU indicates relative light unit. NC indicates negative control
See this image and copyright information in PMC

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