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Valentine JL, Dengler A, Zhao A, Truong T, McAfee S, Hassanein M, Irvin SC, Chen J, Meng X, Yan H, Torri A, Sumner G, Andisik MD, Paccaly A, Partridge MA. Immunogenicity of Cemiplimab: Low Incidence of Antidrug Antibodies and Cut-Point Suitability Across Tumor Types. J Clin Pharmacol 2024; 64:125-136. [PMID: 37656820 DOI: 10.1002/jcph.2340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 08/24/2023] [Indexed: 09/03/2023]
Abstract
The immunogenicity of cemiplimab, a fully human immunoglobulin G4 monoclonal antibody directed against programmed cell death 1, was assessed in patients across multiple tumor types. The development of antidrug antibodies (ADAs) against cemiplimab was monitored using a validated bridging immunoassay. To identify ADA-positive samples in the assay, statistically determined cut points were established by analyzing baseline clinical study samples from a mixed population of different tumor types, and this validation cut point was used to assess immunogenicity in all subsequent studies. Regulatory guidance requires that ADA assay cut points be verified for appropriateness in different patient populations. Thus, for the cemiplimab ADA assay, we evaluated whether each new oncology population was comparable with the validation population used to set the cut point. Assay responses from 2393 individual serum samples from 8 different tumor types were compared with the validation population, using established statistical methods for cut-point determination and comparison, with no significant differences observed. Across tumor types, the immunogenicity of cemiplimab was low, with an overall treatment-emergent ADA incidence rate of 1.9% and 2.5% at intravenous dose regimens of 3 mg/kg every 2 weeks and 350 mg every 3 weeks, respectively. Moreover, no neutralizing antibodies to cemiplimab were detected in patients with ADA-positive samples, and there was no observed impact of cemiplimab ADAs on pharmacokinetics. Study-specific cut points may be required in some diseases, such as immune and inflammatory diseases; however, based on this analysis, in-study cut points are not required for each new oncology disease indication for cemiplimab.
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Affiliation(s)
- Jenny L Valentine
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Andrew Dengler
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - An Zhao
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Tiffany Truong
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Sean McAfee
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Mohamed Hassanein
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Susan C Irvin
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Jihua Chen
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Xiao Meng
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Hong Yan
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Albert Torri
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Giane Sumner
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Matthew D Andisik
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Anne Paccaly
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Michael A Partridge
- Bioanalytical Sciences and Pharmacometrics, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
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Garlits J, McAfee S, Taylor JA, Shum E, Yang Q, Nunez E, Kameron K, Fenech K, Rodriguez J, Torri A, Chen J, Sumner G, Partridge MA. Statistical Approaches for Establishing Appropriate Immunogenicity Assay Cut Points: Impact of Sample Distribution, Sample Size, and Outlier Removal. AAPS J 2023; 25:37. [PMID: 37016171 DOI: 10.1208/s12248-023-00806-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 03/23/2023] [Indexed: 04/06/2023] Open
Abstract
The statistical assessments needed to establish anti-drug antibody (ADA) assay cut points (CPs) can be challenging for bioanalytical scientists. Poorly established CPs that are too high could potentially miss treatment emergent ADA or, when set too low, result in detection of responses that may have no clinical relevance. We evaluated 16 validation CP datasets generated with ADA assays at Regeneron's bioanalytical laboratory and compared results obtained from different CP calculation tools. We systematically evaluated the impact of various factors on CP determination including biological and analytical variability, number of samples for capturing biological variability, outlier removal methods, and the use of parametric vs. non-parametric CP determination. In every study, biological factors were the major component of assay response variability, far outweighing the contribution from analytical variability. Non-parametric CP estimations resulted in screening positivity in drug-naïve samples closer to the targeted rate (5%) and were less impacted by skewness. Outlier removal using the boxplot method with an interquartile range (IQR) factor of 3.0 resulted in screening positivity close to the 5% targeted rate when applied to entire drug-naïve dataset. In silico analysis of CPs calculated using different sample sizes showed that using larger numbers of individuals resulted in CP estimates closer to the CP of the entire population, indicating a larger sample size (~ 150) for CP determination better represents the diversity of the study population. Finally, simpler CP calculations, such as the boxplot method performed in Excel, resulted in CPs similar to those determined using complex methods, such as random-effects ANOVA.
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Affiliation(s)
- John Garlits
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Sean McAfee
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Jessica-Ann Taylor
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Enoch Shum
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Qi Yang
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
- Kriya Therapeutics, 4105 Hopson Rd, Durham, North Carolina, 27713, USA
| | - Emily Nunez
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Kristina Kameron
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Keilah Fenech
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Jacqueline Rodriguez
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Albert Torri
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Jihua Chen
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Giane Sumner
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA
| | - Michael A Partridge
- Regeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Rd, Tarrytown, New York, 10591, USA.
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Rahul K, Banyal RK. k-Means Clustering with Optimal Centroid: An Optimization Insisted Model for Removing Outliers. INT J PATTERN RECOGN 2022. [DOI: 10.1142/s0218001422590078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
In data cleaning, the process of detecting and correcting corrupt, inaccurate or irrelevant records from the record set is a tedious task. Particularly, the process of “outlier detection” occupies a significant role in data cleaning that removes or eliminates the outlier’s that exist in data. Traditionally, more efforts have been taken to remove the outliers, and one of the promising ways is customizing clustering models. In this manner, this paper intends to propose a new outlier detection model via enhanced k-means with outlier removal (E-KMOR), which assigns all outliers into a group naturally during the clustering process. For assigning the point to be outliers, a new intra-cluster based distance evaluation is employed. The main contribution of this paper is to select cluster centroid optimally through a newly proposed hybrid optimization algorithm termed particle updated lion algorithm (PU-LA), which hybrids the concepts of LA and particle swarm optimization (PSO), respectively. Thereby, the proposed work is named as E-KMOR-PU-LA. Finally, the efficacy of the proposed E-KMOR-PU-LA model is proved through a comparative analysis over conventional models by concerning runtime and accuracy.
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Affiliation(s)
- Kumar Rahul
- Department of Basic and Applied Science, NIFTEM, Sonipat 131028, Haryana, India
| | - Rohitash Kumar Banyal
- Department of Computer Science and Engineering, Rajasthan Technical University, Kota 324010, Rajasthan, India
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2021 White Paper on Recent Issues in Bioanalysis: TAb/NAb, Viral Vector CDx, Shedding Assays; CRISPR/Cas9 & CAR-T Immunogenicity; PCR & Vaccine Assay Performance; ADA Assay Comparability & Cut Point Appropriateness ( Part 3 - Recommendations on Gene Therapy, Cell Therapy, Vaccine Assays; Immunogenicity of Biotherapeutics and Novel Modalities; Integrated Summary of Immunogenicity Harmonization). Bioanalysis 2022; 14:737-793. [PMID: 35578991 DOI: 10.4155/bio-2022-0081] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The 15th edition of the Workshop on Recent Issues in Bioanalysis (15th WRIB) was held on 27 September to 1 October 2021. Even with a last-minute move from in-person to virtual, an overwhelmingly high number of nearly 900 professionals representing pharma and biotech companies, contract research organizations (CROs), and multiple regulatory agencies still eagerly convened to actively discuss the most current topics of interest in bioanalysis. The 15th WRIB included 3 Main Workshops and 7 Specialized Workshops that together spanned 1 week in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccines. Moreover, in-depth workshops on biomarker assay development and validation (BAV) (focused on clarifying the confusion created by the increased use of the term "Context of Use - COU"); mass spectrometry of proteins (therapeutic, biomarker and transgene); state-of-the-art cytometry innovation and validation; and, critical reagent and positive control generation were the special features of the 15th edition. This 2021 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop, and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2021 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 3) covers the recommendations on TAb/NAb, Viral Vector CDx, Shedding Assays; CRISPR/Cas9 & CAR-T Immunogenicity; PCR & Vaccine Assay Performance; ADA Assay Comparability & Cut Point Appropriateness. Part 1A (Endogenous Compounds, Small Molecules, Complex Methods, Regulated Mass Spec of Large Molecules, Small Molecule, PoC), Part 1B (Regulatory Agencies' Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine) and Part 2 (ISR for Biomarkers, Liquid Biopsies, Spectral Cytometry, Inhalation/Oral & Multispecific Biotherapeutics, Accuracy/LLOQ for Flow Cytometry) are published in volume 14 of Bioanalysis, issues 9 and 10 (2022), respectively.
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Jordan G, Staack RF. An Alternative Data Transformation Approach for ADA Cut Point Determination: Why Not Use a Weibull Transformation? AAPS JOURNAL 2021; 23:97. [PMID: 34389881 PMCID: PMC8363525 DOI: 10.1208/s12248-021-00625-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 07/12/2021] [Indexed: 11/30/2022]
Abstract
The testing of protein drug candidates for inducing the generation of anti-drug antibodies (ADA) plays a fundamental role in drug development. The basis of the testing strategy includes a screening assay followed by a confirmatory test. Screening assay cut points (CP) are calculated mainly based on two approaches, either non-parametric, when the data set does not appear normally distributed, or parametric, in the case of a normal distribution. A normal distribution of data is preferred and may be achieved after outlier exclusion and, if necessary, transformation of the data. The authors present a Weibull transformation and a comparison with a decision tree-based approach that was tested on 10 data sets (healthy human volunteer matrix, different projects). Emphasis is placed on a transformation calculation that can be easily reproduced to make it accessible to non-mathematicians. The cut point value and the effect on the false positive rate as well as the number of excluded samples of both methods are compared.
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Affiliation(s)
- Gregor Jordan
- Roche Pharma Research & Early Development (pRED), Pharmaceutical Sciences, Bioanalytical R&D, Roche Innovation Center Munich, Roche Diagnostics GmbH, Nonnenwald 2, 82377, Penzberg, Germany.
| | - Roland F Staack
- Roche Pharma Research & Early Development (pRED), Pharmaceutical Sciences, Bioanalytical R&D, Roche Innovation Center Munich, Roche Diagnostics GmbH, Nonnenwald 2, 82377, Penzberg, Germany
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2020 White Paper on Recent Issues in Bioanalysis: Vaccine Assay Validation, qPCR Assay Validation, QC for CAR-T Flow Cytometry, NAb Assay Harmonization and ELISpot Validation ( Part 3 - Recommendations on Immunogenicity Assay Strategies, NAb Assays, Biosimilars and FDA/EMA Immunogenicity Guidance/Guideline, Gene & Cell Therapy and Vaccine Assays). Bioanalysis 2021; 13:415-463. [PMID: 33533276 DOI: 10.4155/bio-2021-0007] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The 14th edition of the Workshop on Recent Issues in Bioanalysis (14th WRIB) was held virtually on June 15-29, 2020 with an attendance of over 1000 representatives from pharmaceutical/biopharmaceutical companies, biotechnology companies, contract research organizations, and regulatory agencies worldwide. The 14th WRIB included three Main Workshops, seven Specialized Workshops that together spanned 11 days in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy and vaccine. Moreover, a comprehensive vaccine assays track; an enhanced cytometry track and updated Industry/Regulators consensus on BMV of biotherapeutics by LCMS were special features in 2020. As in previous years, this year's WRIB continued to gather a wide diversity of international industry opinion leaders and regulatory authority experts working on both small and large molecules to facilitate sharing and discussions focused on improving quality, increasing regulatory compliance and achieving scientific excellence on bioanalytical issues. This 2020 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop and is aimed to provide the Global Bioanalytical Community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2020 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 3) covers the recommendations on Vaccine, Gene/Cell Therapy, NAb Harmonization and Immunogenicity). Part 1 (Innovation in Small Molecules, Hybrid LBA/LCMS & Regulated Bioanalysis), Part 2A (BAV, PK LBA, Flow Cytometry Validation and Cytometry Innovation) and Part 2B (Regulatory Input) are published in volume 13 of Bioanalysis, issues 4 and 5 (2020), respectively.
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Whitehead RD, Ford ND, Mapango C, Ruth LJ, Zhang M, Schleicher RL, Ngalombi S, Halati S, Ahimbisibwe M, Lubowa A, Sheftel J, Tanumihardjo SA, Jefferds MED. Retinol-binding protein, retinol, and modified-relative-dose response in Ugandan children aged 12-23 months and their non-pregnant caregivers. Exp Biol Med (Maywood) 2021; 246:906-915. [PMID: 33467913 DOI: 10.1177/1535370220985473] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Retinol-binding protein (RBP), retinol, and modified-relative-dose response (MRDR) are used to assess vitamin A status. We describe vitamin A status in Ugandan children and women using dried blood spot (DBS) RBP, serum RBP, plasma retinol, and MRDR and compare DBS-RBP, serum RBP, and plasma retinol. Blood was collected from 39 children aged 12-23 months and 28 non-pregnant mothers aged 15-49 years as a subsample from a survey in Amuria district, Uganda, in 2016. DBS RBP was assessed using a commercial enzyme immunoassay kit, serum RBP using an in-house sandwich enzyme-linked immunosorbent assay, and plasma retinol/MRDR test using high-performance liquid chromatography. We examined (a) median concentration or value (Q1, Q3); (b) R2 between DBS-RBP, serum RBP, and plasma retinol; and (c) Bland-Altman plots. Median (Q1, Q3) for children and mothers, respectively, were as follows: DBS-RBP 1.15 µmol/L (0.97, 1.42) and 1.73 (1.52, 1.96), serum RBP 0.95 µmol/L (0.78, 1.18) and 1.47 µmol/L (1.30, 1.79), plasma retinol 0.82 µmol/L (0.67, 0.99) and 1.33 µmol/L (1.22, 1.58), and MRDR 0.025 (0.014, 0.042) and 0.014 (0.009, 0.019). DBS RBP-serum RBP R2 was 0.09 for both children and mothers. The mean biases were -0.19 µmol/L (95% limits of agreement [LOA] 0.62, -0.99) for children and -0.01 µmol/L (95% LOA -1.11, -1.31) for mothers. DBS RBP-plasma retinol R2 was 0.11 for children and 0.13 for mothers. Mean biases were 0.33 µmol/L (95% LOA -0.37, 1.03) for children, and 0.29 µmol/L (95% LOA -0.69, 1.27) for mothers. Serum RBP-plasma retinol R2 was 0.75 for children and 0.55 for mothers, with mean biases of 0.13 µmol/L (95% LOA -0.23, 0.49) for children and 0.18 µmol/L (95% LOA -0.61, 0.96) for mothers. Results varied by indicator and matrix. The serum RBP-retinol R2 for children was moderate (0.75), but poor for other comparisons. Understanding the relationships among vitamin A indicators across contexts and population groups is needed.
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Affiliation(s)
- Ralph D Whitehead
- Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, 1242Centers for Disease Control and Prevention, Atlanta, GA 30341, USA
| | - Nicole D Ford
- McKing Consulting Corporation, Atlanta, GA 30341, USA
| | - Carine Mapango
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA
| | - Laird J Ruth
- McKing Consulting Corporation, Atlanta, GA 30341, USA
| | - Ming Zhang
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA
| | - Rosemary L Schleicher
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA
| | | | - Siti Halati
- World Food Programme, Kampala, 10101, Uganda
| | | | - Abdelrahman Lubowa
- School of Food Technology, Nutrition and Bioengineering, Makerere University, Kampala, 10101, Uganda
| | - Jesse Sheftel
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Sherry A Tanumihardjo
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Maria Elena D Jefferds
- Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, 1242Centers for Disease Control and Prevention, Atlanta, GA 30341, USA
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A new method for identification of outliers in immunogenicity assay cut point data. J Immunol Methods 2020; 484-485:112817. [DOI: 10.1016/j.jim.2020.112817] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Revised: 06/17/2020] [Accepted: 06/23/2020] [Indexed: 11/30/2022]
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Confirmatory cut point has limited ability to make accurate classifications in immunogenicity assays. Bioanalysis 2020; 12:245-256. [DOI: 10.4155/bio-2019-0283] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Aim: Competitive inhibition with excess unlabeled drug is used to confirm the presence of antidrug antibodies (ADA) in study samples. We evaluated specific and nonspecific responses from both drug-naive and drug-treated subjects to identify conditions required by the confirmatory assay to make accurate ADA classifications. Results: Nonspecific signal measured in drug-naive samples used to determine assay cut points was uniformly low and close to the screening cut point. Confirmatory assays performed on incurred study samples with nonspecific responses significantly above the level observed during cut point determination resulted in incorrect ADA classifications. Conclusion: Intensity of confirmatory response should be proportional to the screening response and therefore, to ensure accurate ADA classifications, the confirmatory responses cannot be considered as independent but need to be evaluated in relation to the screening responses.
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2019 White Paper on Recent Issues in Bioanalysis: FDA Immunogenicity Guidance, Gene Therapy, Critical Reagents, Biomarkers and Flow Cytometry Validation (Part 3 - Recommendations on 2019 FDA Immunogenicity Guidance, Gene Therapy Bioanalytical Challenges, Strategies for Critical Reagent Management, Biomarker Assay Validation, Flow Cytometry Validation & CLSI H62). Bioanalysis 2019; 11:2207-2244. [PMID: 31820675 DOI: 10.4155/bio-2019-0271] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The 2019 13th Workshop on Recent Issues in Bioanalysis (WRIB) took place in New Orleans, LA, USA on April 1-5, 2019 with an attendance of over 1000 representatives from pharmaceutical/biopharmaceutical companies, biotechnology companies, contract research organizations and regulatory agencies worldwide. WRIB was once again a 5-day, week-long event - a full immersion week of bioanalysis, biomarkers, immunogenicity and gene therapy. As usual, it was specifically designed to facilitate sharing, reviewing, discussing and agreeing on approaches to address the most current issues of interest including both small- and large-molecule bioanalysis involving LCMS, hybrid LBA/LCMS, LBA cell-based/flow cytometry assays and qPCR approaches. This 2019 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2019 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 3) covers New Insights in Biomarker Assay Validation, Current & Effective Strategies for Critical Reagent Management, Flow Cytometry Validation in Drug Discovery & Development & CLSI H62, Interpretation of the 2019 FDA Immunogenicity Guidance and Gene Therapy Bioanalytical Challenges. Part 1 (Innovation in Small Molecules and Oligonucleotides & Mass Spectrometry Method Development Strategies for Large Molecule Bioanalysis) and Part 2 (Recommendations on the 2018 FDA BMV Guidance, 2019 ICH M10 BMV Draft Guideline and regulatory agencies' input on bioanalysis, biomarkers, immunogenicity and gene therapy) are published in volume 11 of Bioanalysis, issues 22 and 23 (2019), respectively.
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Gorovits B, Wang Y, Zhu L, Araya M, Kamerud J, Lepsy C. Anti-drug Antibody Assay Conditions Significantly Impact Assay Screen and Confirmatory Cut-Points. AAPS JOURNAL 2019; 21:71. [DOI: 10.1208/s12248-019-0342-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 05/17/2019] [Indexed: 01/12/2023]
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