2022 White Paper on Recent Issues in Bioanalysis: Enzyme Assay Validation, BAV for Primary End Points, Vaccine Functional Assays, Cytometry in Tissue, LBA in Rare Matrices, Complex NAb Assays, Spectral Cytometry, Endogenous Analytes, Extracellular Vesicles Part 2 – Recommendations on Biomarkers/CDx, Flow Cytometry, Ligand-Binding Assays Development & Validation; Emerging Technologies; Critical Reagents Deep Characterization

Index Part 2

INTRODUCTION

SECTION 1 – Biomarker & CDx Development & Validation

Hot Topics & Consolidated Questions Collected from the Global Bioanalytical Community

Discussions, Consensus & Conclusions

Recommendations

SECTION 2 – Cytometry Validation & Innovation

Hot Topics & Consolidated Questions Collected from the Global Bioanalytical Community

Discussions, Consensus & Conclusions

Recommendations

SECTION 3 – LBA, Enzyme Assays & Critical Reagents

Hot Topics & Consolidated Questions Collected from the Global Bioanalytical Community

Discussions, Consensus & Conclusions

Recommendations

REFERENCES

Introduction

The 16^th Workshop on Recent Issues in Bioanalysis (16^th WRIB) took place in Atlanta, GA, USA on September 26–30, 2022. Over 1000 professionals representing pharma/biotech companies, CROs, and multiple regulatory agencies convened to actively discuss the most current topics of interest in bioanalysis. The 16^th WRIB included 3 Main Workshops and 7 Specialized Workshops that together spanned 1 week to allow an exhaustive and thorough coverage of all major issues in bioanalysis of biomarkers, immunogenicity, gene therapy, cell therapy and vaccines.

Moreover, in-depth workshops on ICH M10 BMV final guideline (focused on this guideline training, interpretation, adoption and transition); special features of the 16^th edition included mass spectrometry innovation (focused on novel technologies, novel modalities, and novel challenges); and flow cytometry bioanalysis (rising of the 3^rd most common/important technology in bioanalytical labs).

As in previous years, WRIB continued to gather a wide diversity of international, industry opinion leaders and regulatory authority experts working on both small and large molecules as well as gene, cell therapies and vaccines to facilitate sharing and discussions focused on improving quality, increasing regulatory compliance, and achieving scientific excellence on bioanalytical issues.

The active contributing chairs included:

Dr. Chris Beaver (Syneos), Dr. Arindam Dasgupta (US FDA), Dr. Fabio Garofolo (BRI Frontage), Ms. Dina Goykhman (Merck), Dr. James Huleatt (Sanofi), Dr. Akiko Ishii-Watabe (Japan MHLW / ICH M10 EWG), Mr. Gregor Jordan (Roche), Dr. John Kamerud (Pfizer), Dr. Steve Keller (AbbVie), Dr. Lina Loo (Vertex), Mr. Fred McCush (Pfizer), Mr. Luis Mendez (Merck), Ms. Dulcyane Neiva Mendes Fernandes (Brazil ANVISA / ICH M10 EWG), Dr. Luying Pan (Takeda), Mr. Noah Post (Ionis), Dr. Mohsen Rajabi Abhari (US FDA), Dr. Yoshiro Saito (Japan MHLW / ICH M10 EWG), Dr. Daniel Spellman (Merck), Dr. Giane Sumner (Regeneron), Dr. Matthew Szapacs (Abbvie), Dr. Albert Torri (Regeneron), Dr. Montserrat Carrasco-Triguero (Sangamo), Dr. Elizabeth Verburg (Lilly), Dr. LaKenya Williams (BMS), Dr. Karl Walravens (GSK), Dr. Yongjun Xue (BMS)

The participation of major and influential regulatory agencies continued to grow at the 16^th WRIB during its traditional Interactive Regulators' sessions including presentations and panel discussions on:

• Regulated Bioanalysis and BMV Guidance/Guidelines: Dr. Chris Burns (UK MHRA), Dr. Seongeun Julia Cho (US FDA), Dr. Arindam Dasgupta (US FDA), Dr. Xiulian Du (US FDA), Dr. Akiko Ishii-Watabe (Japan MHLW / ICH M10 EWG), Dr. Elham Kossary (WHO), Dr. Yang Lu (US FDA), Ms. Dulcyane Neiva Mendes Fernandes (Brazil ANVISA / ICH M10 EWG), Dr. Mohsen Rajabi Abhari (US FDA), Dr. Yoshiro Saito (Japan MHLW / ICH M10 EWG), Mr. Stephen Vinter (UK MHRA / ICH M10 EWG), Dr. Yow-Ming Wang (US FDA), Dr. Li Yang (US FDA), Dr. Jinhui Zhang (US FDA)

• Biotherapeutic Immunogenicity, Gene Therapy, Cell Therapy and Vaccines: Dr. Nirjal Bhattarai (US FDA), Dr. Eric Brodsky (US FDA), Dr. Isabelle Cludts (UK MHRA), Dr. Heba Degheidy (US FDA), Dr. Shirley Hopper (UK MHRA), Dr. Chad Irwin (Health Canada), Dr. Akiko Ishii-Watabe (Japan MHLW), Dr. Julie Joseph (Health Canada), Dr. Susan Kirshner (US FDA), Dr. Mohanraj Manangeeswaran (US FDA), Dr. Kimberly Maxfield (US FDA), Dr. Joao Pedras-Vasconcelos (US FDA), Dr. Mohsen Rajabi Abhari (US FDA), Dr. Zuben Sauna (US FDA), Dr. Vijaya Simhadri (US FDA), Dr. Therese Solstad (EU EMA/Norway NoMA), Dr. Seth Thacker (US FDA), Dr. Omar Tounekti (Health Canada), Dr. Daniela Verthelyi (US FDA), Dr. Meenu Wadhwa (UK MHRA), Ms. Leslie Wagner (US FDA), Dr. Joshua Xu (US FDA), Dr. Takenori Yamamoto (Japan MHLW), Dr. Lucia Zhang (Health Canada), Dr. Lin Zhou (US FDA).

• Biomarkers/CDx and BAV Guidance/Guidelines: Mr. Abbas Bandukwala (US FDA), Dr. Shirley Hopper (UK MHRA), Dr. Kevin Maher (US FDA), Dr. Yoshiro Saito (Japan MHLW), Dr. Yow-Ming Wang (US FDA), Dr. Joshua Xu (US FDA)

The 16^th WRIB included the traditional evening roundtables, which were attended by both industry key opinion leaders (KOL) and regulatory representatives. The extensive and fruitful discussions from these roundtables together with the lectures and open panel discussions amongst the presenters, regulators and attendees culminated in consensus and recommendations on items presented in this White Paper.

A total of 63 recent issues (‘hot’ topics) were addressed and distilled into a series of relevant recommendations. Presented in the current White Paper is the background on each issue, exchanges, discussions, consensus and resulting recommendations.

Due to its length, the 2022 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication covers Part 2 recommendations.

Part 1 – Volume 15 Issue 16 Month August 2023

Mass Spectrometry, Chromatography & Sample Preparation (4 Topics)

Mass Spectrometry Novel Technologies, Novel Modalities, & Novel Challenges (4 Topics)

ICH M10 BMV Guideline & Global Harmonization (12 Topics)

Impact of Global Harmonization on Regulated Bioanalysis

Common Mass Spectrometry & Ligand-binding Assays Issues

LBA Unique Challenges

Input from Regulatory Agencies on Regulated Bioanalysis/BMV & Biomarkers/CDx/BAV

ICH M10

• 1: Introduction, 2: General principles, 4: Ligand Binding Assay

• 3: Chromatography, 5: Incurred Sample Reanalysis (ISR), 6: Partial and Cross Validation, 8: Documentation

• 7: Additional Considerations

• Adoption by ANVISA

US FDA

• Bioanalytical Considerations for Antibody-Drug Conjugates (ADC)

• Recent Review Experience with Biosimilar Bioanalysis using LBA

• Deficiency in Method Validation for Endogenous Analytes

• General Considerations in Pharmacokinetic Bioequivalence Studies of Endogenous Compounds in ANDA Submission

• Reflections on FDA Remote Evaluation Activities over the Past 2 Years

• Regulatory Findings from Recent Inspections

• Biomarkers for Biosimilars: US FDA perspective

• CDRH CLIA Categorization Processes

• Biomarker Qualification and Analytical Guidance

• Next-Generation Sequencing (NGS) Panels for Precision Oncology Biomarkers

UK MHRA

• Bioanalytical Observations, Findings and Data Integrity Issues

• International Reference Standard Materials (RSM) for Biotherapeutics and Advanced Therapies

Japan MHLW

• Recent Developments of Biomarker Assay Validation (BAV) in Japan for qPCR Assays

WHO

• Inspection & Review of CROs' computerized systems validation

Input from Regulatory Agencies on Immunogenicity, Gene Therapy, Cell Therapy & Vaccines

Immunogenicity

US FDA

• Immunogenicity Information in Prescription Drug Labeling

• Assay Signal-to-Noise Ratio (S/N) as a Potential Alternative to Titer for an ADA Response

• Preclinical tools for assessing the risk of innate immune response modulating impurities applied to biosimilars

• Updates of the US FDA OCP Efforts on Evaluating Clinical Impact of Immunogenicity

Health Canada

• Immunogenicity Labelling for Biologics in Health Canada Drug Submissions

UK MHRA

• Development of reference material as positive controls for ADA assays

Gene & Cell Therapy & Vaccines

US FDA

• Unique Scientific Challenges in the Immunogenicity Assessment of Novel Modalities

• Understanding, Assessing and Managing Immune Responses to CAS-proteins

• Perspective on Emerging Landscape of Gene Therapies

• Application of Flow Cytometry in Cell Therapy; Current Perspective

• Serology Assay Validation

EU EMA/ Norway NoMA

• Regulatory Perspective on Vaccine Serological Assays- Validation as Clinical Endpoints

UK MHRA

• Importance of immunobridging data for vaccine approval: recent experience with COVID-19 vaccines

Health Canada

• Cell and Gene Therapies: Regulatory Challenges and Considerations

• Authorization of new COVID-19 vaccines: The utility of immunobridging studies

• Use of Functional Assays in the Development of Vaccines

Japan MHLW

• Anti-SARS-CoV-2 Neutralizing Antibody Titer as a Clinical Endpoint of Vaccine Clinical Study in Japan

• Two-Dimensional Droplet Digital PCR as a Tool for Titration and Integrity Evaluation of Recombinant Adeno-Associated Viral Vectors

Part 2 – Volume 15 Issue 15 Month August 2023

Biomarkers & CDx Development & Validation (8 Topics)

Cytometry Validation & Innovation (6 Topics)

LBA, Enzyme Assays & Critical Reagents (5 Topics)

Part 3 – Volume 15 Issue 14 Month July 2023

Gene Therapy, Cell Therapy & Vaccines (14 Topics)

Immunogenicity

Technologies

Immunogenicity of Biotherapeutics (10 Topics)

SECTION 1 – Biomarker & CDx Development & Validation

Giane Sumner¹, Steve Keller², James Huleatt³, Roland F Staack²⁶, Leslie Wagner⁵, Mitra Azadeh⁴, Abbas Bandukwala⁵, Liching Cao⁶, Xiulian Du⁵, Gabriela Franco Salinas⁷, Fabio Garofolo⁸, Shannon Harris⁹, Shirley Hopper¹⁰, Chad Irwin¹¹, Qin Ji¹², Julie Joseph¹¹, Lindsay King¹³, Arvind Kinhikar¹⁴, Yang Lu⁵, Rosa Luo¹⁵, Omar Mabrouk¹⁶, Ludovic Malvaux¹⁷, Jean-Claude Marshall¹⁸, Kristina McGuire¹, Vincent Mikol¹⁹, Robert Neely²⁰, Xiazi Qiu²¹, Yoshiro Saito²², Bruno Salaun¹⁷, Ingrid Scully²³, John Smeraglia²⁴, Therese Solstad²⁵, Jeroen Stoop⁷, Huaping Tang²⁷, Priscila Teixeira²⁶, Yixin Wang²⁰ & Mike Wright²⁸

Authors are presented in alphabetical order of their last name, with the exception of the first 5 authors who were session chairs, working dinner facilitators and/or major contributors.

Author affiliations can be found at the beginning of the article.

HOT TOPICS & CONSOLIDATED QUESTIONS COLLECTED FROM THE GLOBAL BIOANALYTICAL COMMUNITY

The topics detailed below were considered as the most relevant “hot topics” based on feedback collected from the 15^th WRIB attendees. They were reviewed and consolidated by globally recognized opinion leaders before being submitted for discussion during the 16^th WRIB. The background on each issue, discussions, consensus and conclusions are in the next section and a summary of the key recommendations is provided in the final section of this manuscript.

BAV for Primary/Secondary End Points in Clinical Studies

What do bioanalytical scientists need to know about CLIA and clinical diagnosis? What and when to follow in absence of a biomarker specific guidance? What is the best source to follow when a biomarker is used as a primary/secondary clinical study endpoint? Beyond scientific principles/rigor, what are additional factors/considerations for biomarker lab selection? What factors should be considered when selecting a laboratory to conduct biomarker work supporting a primary/secondary study endpoint?

Method Development & BAV Strategies for Biomarker & CDx

What is the role of CDx for personalized medicine beyond oncology? What are the challenges to CDx development in China? What are the regulatory requirements for development (CLIA certified labs, GMP material)? When are bridging studies necessary?

Fit for Purpose Validation for Endogenous Analytes: BMV vs BAV for Mass Spectrometry & comparison with other Biomarker Assays

Is there a need or desire for separate regulatory guidance for BAV? Can the ICH M10 guideline section 7.1 be used as a reference for biomarker assay validation? Is parallelism needed for mass spectrometry biomarker assays? Does the use of a specific detector (i.e., high resolution MS) minimize the importance of parallelism to inform on selectivity?

BAV for Vaccine Study Endpoints

What are the advantages and disadvantages of reference standards for vaccine methods? Can the ULOQ be established prior to clinical sample availability? What is the importance of parallelism in single dilution assays?

Difficult Method Development & BAV: Tissues, Complex Matrices & ROS

What are the challenges in biomarker assays using tissues and complex matrices? What are the different approaches being used in normalization for biomarkers?

Extracellular Vesicles Bioanalysis: Latest Developments & Next Steps

Are there reliable/validated EV markers for any specific organs? How has the field advanced/what can be recommended in the following areas: normalization for biological variation, controls and standards, technologies for isolation and detection, interference from other particles?

A decade of Free/Total Assays Discussions for Biomarker & PK Assays

What are strategies to develop QCs for free and total PK assays? How to differentiate equilibrium vs kinetic endpoints for total and free PK. What are strategies for free target assay feasibility and analytical validation? What is the use of modeling and simulation by bioanalytical scientists? Are free and total target assays necessary vs one right assay? What are regulatory expectations for target assays?

Challenges with Multiplex Immunoassays for Biomarkers

How is the industry using multiplex immunoassays?

DISCUSSIONS, CONSENSUS & CONCLUSIONS

BAV for Primary/Secondary End Points in Clinical Studies

Per regulatory authorities, semi-quantitative biomarker data are now routinely included in regulatory submissions. Categories of biomarkers include susceptibility/risk biomarker, diagnostic biomarker, monitoring biomarker, prognostic biomarker, predictive biomarker, pharmacodynamic/response biomarker, and safety biomarker. With biomarker assay validation (BAV) included in the regulatory BMV guidance [32,33] and since Crystal City VI (2016)), fit-for-purpose BAV has been extensively discussed in the bioanalytical community, literature, and conferences. Most discussions have focused on how the biomarker assays should be validated as represented by the C-Path White Paper (2019) and further supported by the 2019–2020 White Paper in Bioanalysis [24,28].

Meanwhile, questions around how the biomarker assays are being used, particularly in clinical development were discussed in the 2019 White Paper. The multiple regulatory structures and guidances such as GLP/GCLP or CLIA (Clinical Laboratory Improvement Amendments 1988), 2018 FDA BMV, or CLSI (Clinical Laboratory Standards Institutes) may also cause confusion on which regulation and guidance to follow for a biomarker assay. Specifically, questions remain on whether a newly developed biomarker assay should be run at a CLIA lab instead of conducted in a GCLP lab based on the phase of clinical development. Similarly, it is important to know in which situation a qualified target biomarker test used to assess disease stage or inclusion/exclusion criteria for a clinical trial enrollment should be sent to a lab with CLIA certification.

The 2021 White Paper in Bioanalysis [30] provided guidance that biomarkers used for individual patient treatment decisions must be tested under CLIA and IDE regulations. Those for primary and secondary endpoints have no regulatory definitions but are subject to GxP guidelines defined by what is critical to the sponsor. Appropriate bioanalytical validation must be in place before using the assay to clinically validate the biomarker as a surrogate endpoint. The key recommendation was to engage with regulatory agencies early to plan for the specific context of use case and required validation package.

The discussions continued with a focus on elaboration of challenges and recommendations for the BAV component of biomarkers used for endpoints in clinical studies. Key discussion points included understanding GCLP vs. CLIA regulation and guidance for clinical biomarker analysis, bridging bioanalysis and clinical lab testing, the additional technical and regulatory requirements for the exploratory biomarker assays developed in FIH to be used in Ph2 and 3 studies, technical and logistic challenges in execution and global correlation of primary end point protein biomarker using IVD in global Ph2/3 studies.

A case study was discussed demonstrating a biomarker strategy implementing biomarkers for multiple COU in trials beyond FIH and which regulatory structures were utilized for each COU. Patient enrollment biomarkers were implemented following CLIA regulations. Primary and secondary endpoint, and exploratory markers were implemented with CLIA and GCLP/BMV regulations. The assay strategy was governed by the application of the data i.e., understanding how efficacy/ PD biomarkers in Ph 2/3 is being used.

The consensus remained that biomarkers for treatment decisions must be measured in CLIA/ISO compliant labs. CLIA/ISO may also be used even when not required for some COU, but not all labs are willing or able due to capacity. Often times, clinicians want a reference range, and there are challenges with providing that for many biomarkers. It was recommended that these limitations should be communicated early to stakeholders during clinical development.

Another topic of discussion was what factors and considerations are important for biomarker lab selection beyond scientific principles/rigor when supporting a primary/secondary study endpoint. There was consensus that choosing a CRO to conduct biomarker work should minimally include an assessment of quality and compliance systems/inspection history, capacity, cost, ability to meet timelines, staff training/longevity, and robust data management practices.

Method Development & BAV Strategies for Biomarker & CDx

The field of Companion Diagnostics (CDx) is continually evolving as the promise of personalized medicine becomes more integrated into drug development strategy and approvals. Much of the CDx landscape to date has been oncology focused but there is a need for personalized medicine/CDx in other therapeutic indications and thus a need to prepare early for the need of a CDx which may come much later in the development process.

Case studies of how and when to generate prevalence and pilot study data based on learnings from oncology CDx development were provided as this impacts the ability of a dataset to support assay development/validation strategy and is a critical input requirement. The recommendations arising from this case study described a risk-based approach to biomarker/CDx assay development. The consensus opinion was that pre-analytical variables including sample collection and processing steps need to be considered with forward thought to real-world processing and diagnostic components that may be part of the sample analysis process. Assay development strategies should try to incorporate potential critical diagnostic elements such as cut-off, sensitivity and selectivity to ensure that early phase patient populations are not dissimilar from a potential registrational study population. Sample analysis strategies (both prospective and retrospective) can be implemented to balance risk. Assay reagents are an additional critical component that can de-risk a program and considerations/case studies can be presented as these are a critical element in ensuring data has sufficient validation for any potential registrational needs.

Another discussion topic for an updated recommendation was when to initiate CDx assay development. With the increasing trend of precision medicine strategies and the speed of clinical trial progression, it's often hard to determine an ideal time for transitioning biomarker analysis from an exploratory tool to a potential approach for IVD or companion diagnostic. Given the length of time it takes to fully develop and deploy a CDx, there is a struggle to determine the right time to pivot the early biomarker assay into a CDx. It is possible that early adoption strategies and other risk mitigating approaches could become useful. However, when, and how to implement such approaches may vary significantly from case to case. There is no one solution to solve this issue and the strategies to adopt will be based on several variables in the decision-making process. The recommendation was to balance cost, timelines, and regulatory risk into the decision-making process for when to pivot a biomarker assay into a CDx.

Case studies were discussed highlighting differences in strategies between CDx assay development for some clinical programs and unique solutions. Different strategies included investing early in CDx partner collaboration, using a third-partyarty lab for early trial analysis and transition plans to CDx, and a post marketing commitment to deliver a CDx. These decisions were based on considerations that include what platform may be used for a biomarker assay, when does an assay need implementation for a clinical trial, what is the context of use of an assay, what is the cost of investment, and whether such assay implementation complements drug development program timelines (e.g., accelerated timelines and competitive landscape).

The discussions also elaborated on the need to co-develop CDx with the therapeutic product for gene therapy. In 2020, FDA published guidance for gene therapy drug development pertaining to the use of CDx in support of gene therapy for rare diseases [34]. The two main classes of CDx addressed in this guidance include genetic tests for disease diagnosis and assays to appropriately select patients due to pre-existing antibodies to a gene therapy product.

Case studies focused on the use of pre-existing antibodies against the viral vector as a predictive biomarker to guide diagnostic development were discussed. The primary assay formats used to detect pre-existing antibodies against adeno-associated viral (AAV) vectors are the transduction inhibition assay also known as neutralizing antibody assay (NAb) and the total antibody binding assay (TAb). Concordance between the two formats is likely tied to assay sensitivity rather than the assay format. The pros and cons of using either format was also discussed. CDx planning for clinical readiness typically takes more than 2.5 years with GT CDx often considered a “significant risk” device which will require an Investigational Device Exemption (IDE) submission. Early and continuous engagement with the regulatory agencies is recommended as the CDx landscape continues to shift and develop for gene therapy. Additionally, the recommendations in Part 3 of the 2020–2021 White Paper in Bioanalysis on this topic were confirmed [28] and an undate on this topic has also been provided in the Part 3 (2022) recommendations of this White Paper.

Another pressing discussion topic is overcoming the challenges of biomarker and diagnostic assay development in China. Multinational pharmaceutical companies conducting clinical trials in China have been facing new challenges in regulation, quality and operations. These challenges include special requirements of using human genetic resources for biomarker and diagnostic assays in China, variable levels of development experience and quality standards from vendors, and complexities of logistics to implement technology platforms supporting clinical trials. To overcome the challenges, efforts have been made to build frameworks and processes that enable assessment of assay technologies, qualification of vendors for assay development and validation, as well as compliant execution of biomarker and diagnostic assays to support clinical trials.

Learnings were discussed on the development of biomarker and diagnostic assays for China clinical studies. Topics included biomarker selection and prioritization in consideration of the limited number of samples for a China study, assay platform and timelines for assay setup, and HGRAC application and approval, which is a unique aspect for conducting biomarker studies in China due to the newly implemented HGR regulations and the China biosecurity law. Intellectual property also continues to be a concern.

Despite the challenges, the information provided by the biomarker and diagnostic assays would help characterize the disease (especially in the Chinese patient population) and enable segmentation of patients for therapy selection and choice. Early adopters will not only develop innovative solutions to overcome these barriers but also benefit from implementation of biomarker and diagnostic assays to support precision medicine strategies in clinical trials and beyond. Therefore, the previous recommendation was reiterated that early engagement with diagnostic partners is vital tied to clinical milestones. Previous recommendations on challenges to perform bioanalysis in China were confirmed.

Fit for Purpose Validation for Endogenous Analytes: BMV vs BAV for Mass Spectrometry & comparison with other Biomarker Assays

Both small molecule bioanalysis platforms (e.g., LCMS) and ligand binding based technologies can be used for biomarker assays and there are considerations and implications of context of use on assay validations strategy across multiple technology platforms. There are a range of fundamental principles of assay validation that must be adhered to however the precise requirements of a validation strategy are often modified based on the context of use or the advantages/limitations of the technology platform being used to measure key endpoints. The discussion was focused on considerations and interrelationship of context of use and determination of validation strategies based on different technology platforms such as LCMS, LBA, hybrid assays, flow cytometry or PCR for biomarkers.

Regardless of technology, development and validation strategy is dependent on understanding how the data will be used (target validation, PK, target engagement/ occupancy, biological effect, and surrogate endpoints). The next stage is choosing the right technology/ platform and how much quantification is needed. IHC is mostly qualitative, RT-PCR and LBA platforms give relative quantitation, and MS is definitively quantitative [35]. Validation tests performed should be fit for purpose dependent on COU and limitations of the technology (analytical range, matrix interference, precision, accuracy, selectivity, carry over, parallelism, stability, etc.).

A follow-up discussion topic was whether there is a need or desire for a separate regulatory guidance for BAV or if the ICH M10 guideline section 7.1 can be used as a reference for biomarker assay validation [19,28,30,36]. There was discussion and consensus on writing guidelines for well-established platforms used for biomarkers (Mass Spec, LBA and flow Cytometry), but different technologies emerge and quickly become more widely used, it will be difficult to continue updating the document. There was consensus that even if BAV is out of scope of ICH M10 guideline the section 7.1. on Endogenous Compounds provides very useful information for biomarkers as well.

US and Japanese Regulatory authorities are still working on general guidance documents with points to consider, intending to be general enough to cover multiple biomarker classes and context of use without defining specific acceptance criteria. It was confirmed that currently the C-PATH Points to Consider Document still provides the best scientific and regulatory considerations for BAV [37].

The utility of one particular validation parameter, parallelism, was discussed again for LBA and MS platforms. ICH M10 made excellent progress on providing guidance for the parallelism assessment of bioanalytical assays, especially for PK assays. However, very few recommendations have distinguished the difference between LCMS and LBA platforms [37]. The final 2018 US FDA guidance on method validation and ICH M10 only inluded a general regulatory statement that “parallelism should be evaluated for assays for endogenous compounds” [32,33,38,39].

It was agreed that goal for parallelism assessment for biomarker mass spectrometry assays is to confirm that MS responses within the calibration concentration range are similar for samples prepared in surrogate matrix versus those in authentic biological matrix presenting real assay samples from studies. In LCMS, often the reference material and the analyte are more closely related (e.g., stable isotope labeled analytes) which usually stabilizes response-concentration correlation despite the use of different matrices (surrogate vs authentic). Case studies were discussed comparing spike recovery and standard addition in LCMS biomarker quantification. It was also discussed regarding the accuracy/precision of QC samples in authentic matrix. Per ICH M10, it is recommended to calculate % accuracy of QC samples based on the spiking concentration. Calculation of QC % accuracy based on total observed concentration (i.e., spiked plus endogenous) may be acceptable, especially for QCs at middle or high concertation levels, if appropriate justification is provided.

There was a consensus that parallelism plays an important role in demonstrating that the reference standard in a surrogate matrix has a proportional response to the endogenous analyte in the authentic matrix.

Finally, it was discussed whether the use of a specific detector (i.e., HRMS) minimizes the importance of parallelism to inform on selectivity. Immunoassay specificity is entirely reliant on antibodies and the analytical detection method (i.e., fluorometric or colorimetric detection) does not offer a way to resolve interfering sample constituents. On the other hand, HRMS encodes specificity of a target measurement through its ability to resolve molecules with very similar masses. Therefore, an immunocapture-HRMS based approach can tolerate a certain degree of antibody non-specificity. There was agreement that the use of HRMS does not minimize the importance of parallelism and that some form of parallelism should still be established. In addition, using advanced technologies or platforms to generate data in support of regulatory decision making usually requires additional clarification, justification, and validation, including parallelism.

BAV for Vaccine Study Endpoints

For vaccine development, bioanalytical assays are needed to characterize the vaccine itself as well as the immune response elicited by the vaccine. In contrast with traditional drug development, where the drug has intrinsic potency, the immune response elicited by a vaccine is the desired outcome. Consequently, the immune assays to support vaccine development need to cover a wide range of responses, from low levels prior to vaccination to potentially order of magnitude increases after vaccination. In addition, large portions of people may be naturally exposed to the target pathogen and have varying levels of natural immunity. Challenges and solutions for vaccine assay development with a wide validated range using BAV principals was discussed.

It was recommended to consider appropriate diluents to validate limit of detection, limits of quantitation, dilutability, linearity, selectivity and specificity for immune assays supporting vaccine development. Presumptive negative human sera may have non-specific or weakly active antibodies that when spiked with positive immune sera react in unanticipated ways that may not be reproducible across different lots of negative human sera. If antibody depleted sera are used, the strategy used to remove antibodies needs to be considered to determine if the depleted sera remains an appropriate matrix for the assay. Outcomes for assay characteristics may be different if assay buffer, presumptive negative sera or antibody-depleted sera are used as the diluent in assay validation. Moreover, the choice of diluent may lead to assay artifacts that may not be representative of how the assay is routinely performed. Thus, consideration should be given to the diluent used when designing an assay validation strategy to ensure the outcome is meaningful with regards to how the assay will be performed routinely.

Validation of a vaccine immunogenicity assay also requires careful consideration as to the choice of samples to be used. Although the use of blood derived samples from commercial sources can seem more practical, these samples may not always be sufficiently representative of the samples the assay is intended for (eg. samples collected during clinical trials). For example, factors such as the trial population, sampling methodologies, and the pathogen or vaccine-candidate antigen can potentially have impact on assay performance. When the intended of use of the assay is to quantify vaccine induced immune responses it is therefore important to validate the assay performance using trial-specific samples.

To demonstrate this, a case study was discussed comparing data for different validation parameters assessed using samples obtained from either commercial or vaccine clinical trial sources. The validation parameters selected for this comparison were: (dilutional) linearity, intermediate precision, relative accuracy, total error, and the limit of detection. It was found that the source of the samples did not lead to a difference in the linearity and the intermediate precision results. However, clear differences were observed for relative accuracy. The concentration range in which an acceptable relative accuracy was observed was considerably wider when commercial samples were used as compared to when clinical trial samples were used. This difference was caused by differences in parallelism with the reference standard (which also consists of commercial material) between the two types of samples (the parallelism was better with commercial samples). These findings demonstrated the risk of only using commercial samples in assay validation as it may not always be representative of assay performance with clinical trial samples. Depending on the assay and validation methodology, this can potentially lead to an incorrect validated assay range. Therefore, it was recommended to validate the linearity, accuracy, and intermediate precision of serology assays with relevant clinical trial samples from an appropriate study population when available and feasible in agreement with previous recommendation on vaccine assay validation [28,31].

Based on these experiences, recommendations were provided on establishment of ULOQ prior to availability of clinical samples, the importance of parallelism for ligand binding single-dilution assays, and the advantages and disadvantages of reference standards. There was agreement that ULOQ should be estimated with available Phase I and II samples ensuring precision and accuracy are maintained. Afterwards, as part of assay life cycle management, the ULOQ may be refined as additional clinical samples become available. Although, for clinical trial purpose analysis, values above the ULOQ are often imputed (at the ULOQ or at 2xULOQ), for assay characterization purpose, participants considered the measured value as more relevant. It was also agreed that parallelism is a critical point to consider early in the validation of single dilution vaccine assays. Finally, agreement was reached that reference standards should be representative of the nature of the response to be validated (polyclonal). The use of international reference, when available, is recommended to calibrate working standards. However, although it allows for more alignment between calibrated assays, this apparent alignment should not be overinterpreted. Two assays developed by two companies to support two vaccine programs, even if calibrated against the same reference, are probably not fully comparable as they likely measure two different subsets of the antibodies present in the reference.

Difficult Method Development & BAV: Tissues, Complex Matrices & ROS

Biomarkers in drug development rely on both the selection of the appropriate markers that show correlation with clinical manifestations or endpoints and also on the selection of appropriate tissues for analysis. Use of disease tissue offers the most direct access to study diseases; however, many tissues are not accessible, creating the need to use surrogate tissues.

A case study was discussed demonstrating development and validation of assays for the detection of reactive oxygen species (ROS) biomarkers 4HNE, S-Glutathione, 8-Isoprostane, DNA Damage, and MDA Adduct to enable monitoring of ROS-mediated toxicity events. As ROS are transient species, method development included a comprehensive evaluation aimed at optimizing procedures for the collection, storage, handling and treatment of samples for clinical bioanalysis. Method optimization involved assessment of the impact of sample freeze-thaw (FT) as well as the impact of antioxidant supplementation on ROS levels. Data showed that except for 4HNE, the majority of ROS are impacted by FT. Furthermore, addition of antioxidants to the biosample collection tube preserved ROS activity and demonstrated that antioxidants had a protective effect against FT.

Surrogate specimens offer the advantage that they are generally easily accessible, collected in a minimally invasive way, and thus, can be obtained live across different time points of a disease. Types of surrogate tissues include tears, synovial fluid, sputum, and exhaled breath condensate. These types of tissues are often complex matrices making method development difficult. Acquisition of these matrices involves operational, pre-analytical, and analytical challenges.

Another complex matrix discussed was synovial fluid where blood contamination determination and normalization are important. Tears are also challenging due to low sample volume and variability. Sputum offers a unique way to sample lung target tissue but poses challenges due to viscosity and heterogeneity. Applications and method development solutions for exhaled breath condensate (EBC) were also discussed in the 2021 White Paper in Bioanalysis and recommendation confirmed [27].

Another difficult biomarker for method development are ROS which are important cell signaling molecules for normal physiology; they also play a major role in the induction of oxidative damage in multiple organelles leading to tissue toxicity. ROS overactivity may underly risk of drug-induced liver injury (DILI) and other toxicity manifestations associated with pharmaceutical drugs [40,41].

As demonstrated by the case studies, each of these methods requires development of a fit-for-purpose assay development and BAV to overcome challenges and understand heterogeneity for the context of use. There was discussion on operational considerations including lack of experience and complexity in collection, leading to variability in the results. Development of biomarker assays in complex matrices also has several difficulties, starting with the availability of the matrix for assay development. Some matrices are not commercially available and need a study protocol for sample collection. In this case, it was recommended that it is reasonable to use a matrix that is as close as possible to the intended matrix for assay development.

Pre-analytical considerations that were discussed include specimen collection standardization, sample processing, sample heterogeneity, and stability of biomarkers in these matrices. There was agreement that samples need to be treated appropriately (may need to be digested, adding detergents and/or inhibitors) to eliminate matrix interference while also ensuring the stability of the biomarker (e.g., sputum processing). Additional assessment needs to be done to ensure the integrity of the biomarker. Samples also need to be stored appropriately. Freeze-thaw stability and storage stability need to be carefully evaluated.

Examples were discussed where sample collection and treatment impacted the biomarker and therefore the reliability of the data. Therefore, it was recommended that additional development may be needed to understand the stability of the biomarker and to ensure the samples are collected, stored and treated appropriately to preserve the biomarker. Finally, platform selection and validation needs to be adapted based on challenges posed by specific matrices e.g. Ella or O-Link becomes an appropriate choice to measure inflammatory cytokines being they use a very small sample volume.

A final discussion topic was the different approaches being used in normalization for biomarkers in complex matrices. For tissues, the most commonly used approaches are tissue weight and total protein after homogenization/lysis for complex matrices. People may also use specific surface markers and cell count for cell samples. Albumin, GAPDH, total protein, and urea may also be used. It will depend on the biomarker and the matrix. The appropriate approach will be dependent on the sample type and the specific biomarker and context of use.

Extracellular Vesicles Bioanalysis: Latest Developments & Next Steps

Extracellular vesicles (EV) are a heterogeneous group of cell-derived membranous structures. All cells release EVs normally and during acquired abnormalities. EVs contain a variety of biological molecules that were present in the cells from which they were derived such as nucleic acids, proteins, and lipids. The interest around extracellular vesicles has increased in recent years due to their potential utility as circulating biomarkers in clinical research [27,30]. EVs have been isolated from diverse body fluids and may provide important information about tissue-related changes in the context of a drug response, the target molecule, disease activity and patient stratification while reducing the patient`s burden of invasive tissue sampling.

Bioanalysis of EVs for drug development biomarker use was extensively discussed in previous White Papers [27,30]. This included discussion of clinical applications, isolation/ collection, and bioanalysis of EVs. Previous case studies demonstrated that isolation procedures (pre-analytical) need to be tightly controlled to minimize heterogeneity. Key technologies used to detect and quantify EVs were discussed (MRPS, microscopy, scatter-based nanoparticle tracking analysis, western blot or ELISA-based characterization, multiparameter flow cytometry, global proteomic analysis using mass spectrometry, fluorescence-based nanoparticle tracking analysis).

Another key application of EVs has been detection of organ specific EVs. The 2021 White Paper in Bioanalysis discussed that quantification of biomarkers on organ-specific EVs has to consider two parameters: biomarker expression on EVs and the overall number of EVs in order to accurately evaluate differences in biomarker expression between samples. Normalization is also needed because of variations between isolates. Overall, while the clinical applications were recognized through case studies, the consensus was that more case studies are needed to demonstrate applications for clinical endpoints and for recommendations for specific isolation and analysis methods.

Due to this recommendation, more case studies on the isolation and bioanalysis of EVs, organ specific EVs, and normalization of EVs in clinical samples were discussed. One case study discussed hybrid immunoassay development to detect organ-specific extracellular vesicles and its application in human samples. Comparison of different isolation methods showed proper EV detection depends on isolation efficiency and protein concentration. Biological variation and interferences were evaluated during method development by dilution linearity and normalization methods. Recommendations for EVs based on how the field has advanced were discussed. There was consensus that there are no reliable or validated markers for the detection of organ specific EVs. Sample sizes are small, and variability is an issue. In addition, there is no gold standard for comparison except invasive biopsies, while other approaches such as ctDNA are currently more reliable.

Advancements in biological variation (intra-donor variability) and normalization methods (EV numbers, marker expression, protein content) were also discussed. There was agreement that analytical variability is still too big of an issue to allow for evaluation of biological variation. Nevertheless, recommendations were provided to control it to some extent via use of same donor, same timepoint, and large blood draws. It is yet unknown as to whether there will be changes to homogeneity and/or, target degradation during storage. Based on experience, there was consensus that qualitatively determining presence or absence of signal has had success. Qualitative endpoints are more difficult to ascertain.

A new discussion topic was what controls and standard reagents are available to be used as calibration curves and in assay validation. Commercially available EV's, viral particles, cell culture products are all viable options, but there was agreement that there is no approach sufficiently robust to serve the purpose of controlling methods or calibrating measurements. Ultimately, in-house custom reagents may be necessary.

Continued discussion on isolation and detection methods have shown some of the methods that are not recommended. For example, there was agreement that polymer-based isolation kits seem less favorable compared to size exclusion. The various proposed methods all have their limitations (but potential huge payoff), but additional academic and industry innovation is still needed.

The final discussion topic was differentiating EVs from other interfering particles such as viral particles, lipid particles, and cellular debris. Viral particles and apoptotic bodies do not express some exosome markers and therefore are worth continued exploration. Currently, there is no consensus on what the best markers are for this purpose, and continued investigation is needed. Further discussion at WRIB has already been planned.

A decade of Free/Total Assays Discussions for Biomarker & PK Assays

Lee et al. [42] highlighted the challenges and considerations for the measurement of biotherapeutics, and monoclonal antibody drugs), in particular, as well as their target because the interaction is non-covalent, multiple forms may exist in vivo. The implication of non-covalent binding is the act of measurement may alter the result; equilibrium may be significantly disrupted depending on the affinity of binding as result of sample dilution, incubation time and reagent affinity and concentration. The main forms of drug and target measured are free and total and the recognition that assay format and assay conditions that might alter sample equilibrium during the measure of free target. However, confirmation of the forms being measured remains technically challenging.

The importance of clearly defined bioanalytical data of free drug or total drug to evaluate the pharmacokinetic behavior of therapeutic proteins and to enable pharmacokinetic (PK)/ pharmacodynamics (PD) assessment has been extensively discussed over the last years [7,13,17,28]. The relevance of assay formats was the main focus of the discussion. In the most recent White Paper in Bioanalysis, recommendations were provided for using free drug and/ or total drug assays for target engagement. Previous discussions demonstrated target engagement of a candidate drug may require independently developed assays to generate data for the free, total and complex fractions of the target. But there was agreement that it is not common practice to offer multiple types of assays (free, total) for a TE program with priority given to development of total assays which are less susceptible to overestimation of target when complex dissociation occurs.

Additional critical factors for scientifically sound free or total drug analysis include reagent selection, assay incubation times, blank matrix selection for calibrator and QCs preparation as well as for sample dilution (see above mentioned White Papers in Bioanalysis). While no final conclusions on how to deal with these challenges, the recent paper by the FDA [43] reflected the diversity of industry approaches with regard to bioanalytical PK assay characterization and the lack of alignment within the industry community on how assay characterization should ideally be performed.

The case studies discussed illustrated the scientific and regulatory challenges for appropriate free / total assay development. It was demonstrated that ICH M10 solved the matrix problem for free drug analysis and matrix-dependent errors (calibration, dilution) can be avoided [44]. QC-based assay development is also complex for free/kinetic-based assays to analyse free drug or target engagement. Modelling of free analyte concentration in vivo based on total binding partner concentrations is theoretically possible but there was discussion that it should be of the same quality as bioanalytically derived data. This requires exact knowledge of the appropriate KD data. In-solution KD data is needed and “surface based” KD values should be used with caution [45,46]. Furthermore, it is important that instead of “total protein” concentrations “total binding competent” concentrations of the binding partners need to be determined and used for the calculation. Finally, the exact concentrations of the two “total” binding partner concentrations are needed, which might require tighter accuracy and precision acceptance criteria than typically accepted for PK assays [46].

However, the assay variability (accuracy & precision) of the applied total assays might introduce a significantly higher variability of the calculated free concentration of the binding partners. This error propagation needs to be taken into consideration since the error of the final free result can be very significant and much higher than what is expected for an appropriately developed free drug or target assay [47]. The use of free analyte QCs [47] enabled successful development of “free drug” assays by LBA and LC-MS fulfilling regulatory expectations for PK evaluation [48,49]. The case studies also demonstrated that modeling is highly difficult in the presence of additional binding partners (e.g., ADAs, soluble receptors). This biological complexity cannot be mimicked using artificially prepared QC samples. The use of “model-informed assay development” (MIAD) was proposed as an option to include these additional binding partners into the assay equilibrium reaction of the reagents and the analyte to ultimately identify the optimal assay conditions [46].

There was continued discussion on whether multiple assays are needed for a program, the need for early feasibility assessments and team education on the bioanalytical risks. After the publication of Lee et al. [42] there is better awareness of the complexity of measuring different forms of drug and target within the bioanalytical community, clinical teams often do not fully understand the challenges and costs of developing multiple assays as well as the risks of using free target assays. Many clinical scientists may not have supported a program where the question of free and total was relevant, and as a result, teams sometimes request both free and total target as well as free and total PK assays. It was agreed that developing an internal strategy with shared learning from external and internal programs would be beneficial.

Free target assays are typically the hardest to develop and the most likely to overestimate the levels of analyte as a result of the measurement process (sample dilution etc.). Free target levels normally go down after dosing so assays often need high sensitivity. Significant complexity can be expected when drug target binding affinity is lower, when the target exists as dimer or multimer and/or when there are endogenous binding proteins for the target.

It was recommended that communication with teams regarding the challenges of developing and using target assays, when work needs to start, and to carefully assess if two target assays are really needed.

An early decision to develop a free target assay needs to be made because it may take a year or more to generate reagents, to develop and validate the assay. It was noted that bioanalytical validation of free target measurement is often limited to drug “interference experiments”. It is difficult to know how much free target should be present and thus whether an assay overestimates free target levels. Therefore, building confidence in the ability of a free target assay to accurately measure free target using modeling and simulations as well as experimental data is valuable. Unreliable measurement of the free target could lead to an under estimation of free target suppression. Particular effort should be made to assess the risk at the end of the dosing cycle if total target level could be very high (eg 100 fold accumulation over baseline) because even a very small amount (e.g. even 1%) of target released because of sample measurement process could result in a significant over estimate of free target levels which may be interpreted a biological rebound leading to significant team time spent interpreting and investigating results/uncertainty and potentially questioning the validating of all the data.

If a free target assay appears to be analytically feasible, and experimental and in vitro modeling support its ability to measure free (i.e., not over measure), the study data generated may be of limited use. A free target assay should measure suppression and return to baseline reliably but assay lower limit of quantification (LLOQ) and/or sparse sampling may lead to a baseline result with most time points BLQ and as a result the data may not actually be able to be used for dose selection. The duration of BLQ results may be reassuring but not decision making.

It was discussed that bioanalytical scientists may be asked about and should be able communicate why differences can be seen in target levels when comparing target assays that other companies have developed, why published data of a free assay may not be accurate and why a commercial kit may be not designed or able to measure either free or total target per say. Whether a target assay measure total target of free target is a drug specific question.

The common desire for teams to ask for multiple target assay was also discussed with a case made to generally avoid taking two target assays into the clinic for a variety of reasons including opportunity and financial costs with uncertain return on investment in generating decision making data but also the potential for data uncertainty as descried above. An additional source of concern was described in situations where free and total assays results are not concordant at baseline which is not uncommon.

The use of modeling and simulation tools to inform free target assay design and development to predict in vitro and in vivo target concentrations were discussed. The impact of sample dilution, reagent concentration and incubation times can all be simulated to inform initial feasibility assessments and risk over full range of expected target and drug concentration. Typically, there is some uncertainty regarding in vivo KD sensitivity analysis of model parameter assumptions should also be tested and can facilitate illustrating risks to the team and/or support decision to not develop a free assay.

PK/PD modeling is also a well-established approach to simulated/predicted in vivo free and total target profiles and to manage situations where while free target would be preferred but only total target was measured along with, typically, free drug.

These discussions led to consensus recommendations for free and total biomarker assays. It was recommended to fully understand target properties and biology and drug/target and reagent/target binding kinetics before designing assays to measure the intended form of an analyte. The generation of internal modeling and simulation tools and a best practice document was also recommended. Modeling can be used to inform assay experimental feasibility, provide direction for what free levels should be, and build PK/PD models that allow the use of total target and free drug to predict free (suppression/target coverage). However, such an approach always needs to account for potential error propagation as discussed above into consideration and is significantly limited when additional binding partners (e.g., soluble receptors/binding proteins of the target or anti-drug antibodies) are present [44]. Finally, there was consensus that free assays results might need to be considered not fully quantitative based on the analytical limitations if assay development and validation data proving appropriate assay conditions is lacking. However, since the error of calculated free analyte concentrations might be much higher due to error propagation of the used data sets and other limitations as mentioned above (KD value, additional binding partners) it needs to be evaluated what accuracy and precision is required in this respective case. Accurate free drug analysis was successfully shown by LBA and LC-MS using free QCs [49]. Most challenging are cases where one binding partner is in huge excess, as is often encountered for target engagement analysis. In such cases, a minimal shift of the equilibrium of the binding partners caused by assay conditions can sometimes not be excluded due to technology limitations and might result in a significant error of the free analyte result.

Challenges with Multiplex Immunoassays for Biomarkers

Multiplexed biomarker assays are an attractive means to support a push towards biomarker rich study programs. The large number of biomarkers assessed in these programs can enable greater characterisation of disease biology whilst also potentially identifying companion diagnostics. Some commonly used multiplex biomarkers for drug development include multiplexed cytokines, proteomics, and other multi-omics approaches.

For multiplex cytokine assays, the data can either be used as part of pattern recognition, or as a panel, where the measurement of the group of markers can answer a number of different questions. Each scenario raises its own unique questions regarding validation parameters and techniques of demonstrating assay control during study support. For multiplexed cytokine assays where the cytokines are measured as a panel, performance compromises that are inherent in high plex assays can result in the need to move to better performing single plex assays as the biology becomes understood and the program progresses.

Another frequent driver of this change is the requirement to generate baseline cytokine data on each subject. This is often achieved by switching the analysis to a highly sensitive and robust single-plex assay. The downsides of making this change includes the requirement to validate a second assay, having to perform extensive cross validation experiments to assess concordance, and the subsequent transformations performed on previously generated data to enable comparisons between studies.

The emergence of high-sensitivity multiplex assays provides the opportunity to use these assays throughout the drug development pathway and thus avoid both the need for concordance assessments and the challenge of deciding what to do when assays do not correlate. Experiences to date with comparing high sensitivity multiplex cytokine assays to historical multiplex and high sensitivity single plex assays were discussed. Comparisons of high sensitivity multiplex assays over other multiplex immunoassays showed that high sensitivity assays can enable more successful measurement of baseline samples, particularly cytokines. Importantly however, there was agreement that exchangeability with historical data is unlikely, due to different critical reagents and methodologies, without some form of transformation (and in some cases may not be possible).

Challenges in validation of multiplex assays and commercial kits include validating LLOQ and demonstrating control with QCs. The probability of all analytes in a multiplex assay passing QC falls as the number of analytes increases. This is exacerbated by poorly characterized assays and endogenous material. One solution is to apply Westgard rules [50] with reduced QC stringency over the traditional 4-6-X method. Other approaches include limiting QC acceptance criteria to key biomarkers and removing poor performing biomarkers to be run as a single-plex. It was agreed upon discussion that assay reagents switching from pAb to mAb promising regarding commercial kit us, but critical reagent control and communication with vendors is key to mitigating performance shifts through lot number changes.

Other applications demonstrating use of multiplexed biomarkers were discussed with a case study on identification of biomarkers of NASH/NAFLD disease progression. Recent epidemiological data reported Non-alcoholic Fatty Liver Disease (NAFLD) as one of the most common causes of chronic liver disease in the developing world. The ABOS cohort [51] is a unique cohort which contains clinical longitudinal data up to 10 years and associated liver biopsies. Analysis of the ABOS cohort led to the stratification of about 800 patients in 3 distinct groups according to their liver status (NASH, NAFL, Healthy). A multiomics analysis was performed including proteomics and metabolomics (lipids, free fatty acids and oxysterols) from plasma/serum, miRNA sequencing from liver biopsies, RNA seq on a subset of samples from extreme phenotypes with unequivocal diagnosis. Predictive disease biomarker candidates were identified which are being further validated in additional independent cohorts.

These case studies led to recommendations on the use of biomarker multiplex assays in clinical trials and validating them. As demonstrated in case studies, there was agreement that the higher the number of biomarkers in the multiplex, the greater the complexity for development, validation, analysis and use of the assay in clinical development. In addition, the assay might not reflect the optimal conditions for every single biomarker.

Therefore, there was consensus that there is a need for compromise when running multiplex assays. Multiplex assays were recommended for use in early discovery for biomarker pattern recognition and hypothesis generation consistent with current industry use of them. Based on these data produced, a small number of more significant biomarkers can be then further used to generate PD data as the drug program advances with additional assay characterization.

Data analysis for multiplex assays can also be complex when trying to identify patterns when not just trying to narrow down to a few biomarkers. Due to this, regulatory authorities have not seen much multiplexed data in data submission packages, but it was recommended to understand what is being tested and how the output and patterns correlate with the assay.

RECOMMENDATIONS

Below is a summary of the recommendations made during the 16^th WRIB:

BAV for Primary/Secondary End Points in Clinical Studies

• There was continued push to standardize terms e.g. (biomarker methods are “validated” while biomarker themselves are qualified as described in the FDA Biomarker Qualification Program.

• When the assay is used for regulatory decision-making outside of the FDA's Biomarker qualification program, it also needs to be fully validated.

• Methods used for deriving patient inclusion/ exclusion criteria and/or treatment decisions must be performed in compliance with CLIA or equivalent (e.g., ISO, CE)

• Choosing a CRO to conduct biomarker work should minimally include an assessment of quality and compliance systems/inspection history, capacity, cost, ability to meet timelines, staff training/longevity, and robust data management practices.

Method Development & BAV Strategies for Biomarker & CDx

• Due to the challenges of development, early engagement with diagnostic partners was recommended but not always feasible.

• Since investment costs can be significant development should be tied to clinical milestones.

• When biomarkers are included late in the development process, bridging studies should be considered, with appropriate samples stored under characterized stable conditions.

• There was consensus that it is critically important to ensure adequate supply and storage of clinical samples to enable bridging (even when bridging isn't necessarily planned).

• If the assay is repurposed to meet the needs of clinical development, the BAV should be adapted to fit it for purpose.

Fit for Purpose Validation for Endogenous Analytes: BMV vs BAV for Mass Spectrometry & comparison with other Biomarker Assays

• If BAV is out of scope of ICH M10 guideline the section 7.1. on Endogenous Compounds provides very useful information for BAV too.

• Currently, the C-PATH Points to Consider Document still provides the best scientific and regulatory considerations for BAV.

• Regarding the importance of parallelism in Mass Spec biomarker assays, parallelism plays an important role in demonstrating that the reference standard in a surrogate matrix has a proportional response to the endogenous analyte in the authentic matrix.

• The use of HRMS does not minimize the importance of parallelism.

BAV for Vaccine Study Endpoints

• Recommendations were provided for performing vaccine endpoint BAV

• Though availability of clinical samples is challenging, it was recommended to estimate ULOQ with available Phase I and II samples; ensure precision and accuracy are maintained

• Refine ULOQ as additional clinical samples become available which becomes part of lifecycle management.

• Parallelism is a critical point in validation of single dilution assays.

• Reference standard should be representative of the nature of the response to be validated (polyclonal)

Difficult Method Development & BAV: Tissues, Complex Matrices & ROS

• Development of biomarker assays in complex matrices has several difficulties, starting with the availability of the matrix for assay development.

  ○

  It is important to understand the biomarker and its biology, from what is the correct matrix, if a surrogate matrix needs to be used, how to collect (without contamination) and treat the samples, and ultimately understanding assay limitations/variability.

• Recommended approaches for normalization of biomarkers in tissues include weight, total protein, cell count, urea, specific surface markers, etc.

  ○

  The appropriate approach is dependent on matrix, biomarker, and context of use of data

• For tissues, complex matrices, and ROS, the parameters most critical for biomarker assay validation are precision, reproducibility, and biomarker stability.

Extracellular Vesicles Bioanalysis: Latest Developments & Next Steps

• Reliable/validated EV markers do not exist for any organs at this stage and other approaches like ctDNA are more accurate while continued research is performed on understanding range of EVs and isolation technology.

• Analytical variability is still too large to allow for evaluation of biological variation and normalization methods between donors and timepoints. Qualitative methods have more success thus far.

• Regarding advancements in controls and standards, commercially available EV's, viral particles, cell culture products are viable options, but it is not clear that any particular approach is sufficiently robust

• The updated views on isolation and detection methods suggest size exclusion is preferred to polymer, but there was agreement that methods for EV isolation and detection all have their limitations, and additional academic and industry innovation is still needed.

• Previous recommendations to continue to clearly define and describe EV collection and isolation procedures (preanalytical considerations) in published methodologies were reiterated.

A decade of Free/Total Assays Discussions for Biomarker & PK Assays

• It is crucial to fully understand target properties and biology and drug/target and reagent/target binding kinetics before designing assay to measure intended form of analyte.

• The generation and use of internal modeling and simulation tools for free and total assay development was recommended to.

  • inform assay experimental feasibility.

  • provide direction for free level should be.

  • build PK/PD models that allow the use of Total Target and Free drug to predict Free (suppression/target coverage)

  • The prerequisites that enable free analyte calculations such as knowledge of the in-solution KD value, exact concentrations of the binding partners at higher accuracy and precision than accepted for PK evaluation do limit the variability of the result due to error propagation and absence of additional binding partners need to be carefully considered.

• Free assays results might need to be considered not fully quantitative based on the analytical limitations if assay development and validation data proving appropriate assay conditions is lacking

Challenges with Multiplex Immunoassays for Biomarkers

• Multiplex assays are recommended to be mainly used in early discoveries for biomarker pattern recognition and hypothesis generation.

• The higher the number of biomarkers in the multiplex, the greater the complexity and the assay might not reflect the optimal conditions for every biomarker.

  ○

  Therefore, based on early discovery data, a small number of more significant biomarkers can be then further used to generate PD data as the drug program advances.

• Regulatory authorities have not seen much multiplexed data in data submission packages, but it was recommended to understand what is being tested and how the output and patterns correlate with the assay.

SECTION 2 – Cytometry Validation & Innovation

Luis Mendez²⁹, Chris Beaver³⁰, Gabriela Franco Salinas⁷, Jacqueline Eacret³³, Amelia Au-Yeung³¹, Abbas Bandukwala⁵, Vilma Decman³², Francis Dessy¹⁷, Steven Eck³⁴, Polina Goihberg³⁵, Enrique Gomez Alcaide²⁶, Christele Gonneau³⁶, Katharine Grugan³⁷, Michael Nathan Hedrick²⁰, Shirley Hopper¹⁰, Chad Irwin¹¹, Julie Joseph¹¹, Sumit Kar²¹, Yoshiro Saito²², Bruno Salaun¹⁷, Sarita Sehra³⁸, Erin Stevens³⁹, Chad Stevens³⁵, Yongliang Sun²⁰, Priscila Teixeira²⁶ & Leslie Wagner⁵

Authors are presented in alphabetical order of their last name, with the exception of the first 4 authors who were session chairs, working dinner facilitators and/or major contributors.

Author affiliations can be found at the beginning of the article.

HOT TOPICS & CONSOLIDATED QUESTIONS COLLECTED FROM THE GLOBAL BIOANALYTICAL COMMUNITY

The topics detailed below were considered as the most relevant “hot topics” based on feedback collected from the 15^th WRIB attendees. They were reviewed and consolidated by globally recognized opinion leaders before being submitted for discussion during the 16^th WRIB. The background on each issue, discussions, consensus and conclusions are in the next section and a summary of the key recommendations is provided in the final section of this manuscript.

Vaccine Functional Assays

What are common practices and acceptance criteria for bridging detection antibodies, reagents, and instrumentation? What are guidelines for assessing relative accuracy when handling undiluted and diluted control samples to establish linearity; are there alternatives to determine LOD and assay specificity in the absence of true negative samples, and definition of LOB for cell-based assays? What are current issues in standardization of cell-based assays during global clinical trials? What are ongoing approaches to PBMC isolation and handling?

Cytometry in Tissue Bioanalysis

What are strategies for validation of tissue flow cytometry or ChipCytometry for clinical use? What are strategies for tissue handling and processing to a single-cell suspension?

Innovation in Cytometry

What is the role of and recommendations for high dimensional flow assays in clinical trials? What platform is preferred between full spectrum and mass cytometry? What are considerations for working with CROs to perform high-dimensional flow cytometry? Are new approaches ready for clinical trial settings for data management and analysis?

Current Challenges with Cytometry Validation

How can we apply statistical approaches to fit-for-purpose validation in the context of a clinical trial? Are there more specific statistics that can be applied to interpretation of the flow data?

Are there recommended approaches besides % CV precision-based testing (e.g. confidence interval-based based criteria) that could be applied to flow cytometry measures? Are there recommendations for validating cut- or decision-points where the assay may not have the precision to be quantitative but are above LOD? How do you use this data? What are reasonable criteria to demonstrate performance is adequate to determine a measurand is on one side or the other of a decision point? Are there acceptable ways to handle presenting data on measures that are past quantifiable stability for exploratory uses aside from outright exclusion? Do we have examples of when such approaches would be appropriate and when they would not? Are there examples of fit-for-purpose statements that might support reporting of a sample past its quantitative stability? What are the current approaches being pursued to extend sample stability? With the advent of Project Optimus are flow cytometry assays such as receptor occupancy or cell depletion measures for PK/PD analysis as part of dose selection being viewed differently? How do we do validation in cases where it is not feasible to obtain samples (e.g., rare matrices)? What is the importance of tracking stability of critical reagents? What are validation requirements for assay modifications?

Biomarkers, RO, Macrophage Polarization & Phagocytosis Measurements

What are the challenges for tumor receptor occupancy assays by flow cytometry for small molecules and bispecific antibodies? Assays for assessing monocyte/macrophage function in whole blood and tumors. Extracellular vesicles as biomarkers with regard to RNA and protein profiling

Cytometry Conventional/Novel Technologies & Main Applications

What are the benefits and risks of combining flow cytometry data with other “omics” platforms and AI/ ML based analysis? What steps should be taken early during development to prepare for the transition of assays to companion diagnostics? What are uses of CyTOF for quantitative biomeasures? How are the needs of industry different than academia? What is the future need for CyTOF? What are uses of imaging cytometry? What is the future need for imaging cytometry?

DISCUSSIONS, CONSENSUS & CONCLUSIONS

Vaccine Functional Assays

Increasing evidence suggests that induction of T cell-mediated antigen-specific immunity is essential for candidate vaccines, particularly those targeting complex intracellular pathogens such as SARS-CoV-2, the causative agent of the ongoing COVID-19 pandemic. As such, thorough evaluation of vaccine-induced cell-mediated immunity (CMI) is essential for measuring breadth, durability and cross-reactivity of protective immune responses. To date, the most widely used CMI functional assays are the IFNγ ELISpot and flow cytometry-based intracellular cytokine staining (ICS). Time-sensitive procedures and the requirement for trained personnel/specialized equipment significantly hamper the standardization of these assays during global clinical trials. It is imperative to employ sensitive and scalable methods for measuring CMI during vaccine trials, particularly when evaluating novel infectious disease vaccines for pandemic prevention/control [52–58].

Therefore, a case study aiming to demonstrate a simplified approach for measuring CMI in vaccine clinical trials through evaluation of alternate blood collection methods and T cell immunoassays was discussed. SARS-CoV-2-specific T cell responses were analyzed from healthy human donor blood samples, serving as a critically relevant model for CMI. Initial efforts to streamline PBMC isolation compared blood samples collected via traditional BD Vacutainer^® tubes or CPT Mononuclear Cell Preparation^® tubes, followed by stimulation with overlapping SARS-CoV-2 peptides and analysis by IFNγ ELISpot and ICS [59–63].

This case study led to discussion of approaches for standardization of cell-based assays during global clinical trials and ongoing approaches to PBMC isolation and handling. There was consensus to 1) determine whether the flow assay will be conducted at a central vs. local lab; 2) define the method of collection and sample handling procedures; 3) understand the stability of cell subset(s) of interest; and 4) clarify the extent of panel design, optimization, and validation. In order to develop an appropriate approach for PBMC isolation and handling, it is of primary significance to determine the type of data that is needed (CD4/CD8, Th1/Th2, or population-level cytokine profile). This will ultimately influence all downstream decisions regarding the assay(s) that will be executed, collection tube type, the need for fresh vs. fixed cells, local or central lab responsibilities. In all instances, a high-quality sample must be ensured through validation of loss of cell subset, cell function, or changing cell maturity/activation status with increasing time from collection to processing. Finally, it is helpful to understand whether sites have the capabilities to perform the processing from whole blood to PBMCs and the appropriate storage conditions for timely cryopreservation. Temperature controls should be implemented when shipping frozen PBMCs. PBMC isolation and handling guidelines and recommendations from the 2021 White Paper in Bioanalysis should also be followed.

Flow cytometry based functional assays are used in vaccine clinical trials as readouts of cellular immunogenicity. Immunogenicity endpoints are often included in vaccine registration studies, and full assay validation is therefore required. Intracellular Cytokine Staining (ICS) is a flow cytometry-based functional assay used to assess antigen-specific T cells frequencies. It quantifies positive events (i.e., T cells expressing activation markers such as cytokines) after antigen-specific stimulation of Peripheral Blood Mononuclear Cells (PBMCs). T cells of a given antigenic specificity are rare in peripheral blood, and frequencies greatly vary according to antigen/pathogen specificity. For this reason, a high cell number of PBMCs is needed to conduct the assay to ensure a relevant number of antigen-specific T cells is captured. In addition, the design of validation experiments (many repeats and many different parameters) make these cell-hungry assays, ultimately requiring large blood volumes to be collected in order to generate PBMCs in sufficient numbers for all conditions to be tested. This adds many layers of complexity in clinical trial design, making PBMC-based assays difficult to execute, particularly in late-phase clinical trials.

To circumvent these limitations and allow for generation of ICS assay validation data as required to support registration immunogenicity endpoints, the use of PBMCs from biobank studies (blood collection from healthy donors) was shown to be a valuable alternative. However, natural responses against vaccine antigens can be very low or absent in healthy volunteers, who are often naïve for a given pathogen of interest. To evade this challenge, an antigen or combination of antigens that are specific to pathogens known to infect a majority of the population (e.g., peptides targeting CMV, tetanus, influenza, etc.) can be used to induce quantifiable antigen-specific responses in a high proportion of individuals, regardless of genetic background, geographical location or previous antigen exposure. The use of such model antigens to stimulate PBMCs was successful at generating a wide range of T cell responses from biobank studies (independently of clinical trial samples), without relying on vaccine-induced responses to validate the capacity of the assay to reliably and repeatedly detect antigen stimulation-induced cytokines.

Another case study highlighting the challenges associated with the use of ICS assays to study antigen-specific T cell responses to vaccines was discussed. This study focused on the unique challenges for validation of ICS assays due to the complexity of the technique, biological variability of immune cells, and the multiplicity of readouts that can be obtained. Sensitivity of the assay is a primary challenge. Often, the relevant responses in an ICS assay are of very low magnitude, thus extensive optimization of assay conditions are needed to maximize signal-to-noise ratio. A second challenge is the availability of vaccine-specific validation samples, where typically, only few aliquots of such samples are available for assay validation. Although the use of surrogate antigens for stimulation (e.g., CMV), as described above, provides one solution, it also raises the challenge of identifying donors with a frequency of response relevant to the vaccination context. This approach therefore requires screening of multiple samples to match different levels of response per readout.

This case study led to discussion of common practices and acceptance criteria for bridging detection antibodies, reagents, instrumentation, and assessing relative accuracy when handling undiluted and diluted control samples to establish linearity. Alternatives to determine LOD and assay specificity in the absence of true negative samples and definition of LOB for cell-based assays were also discussed.

When bridging of detection antibodies for ICS was discussed, it was agreed that performing a titration of two different lots (as opposed to establishing bioequivalence by systematic difference) was sufficient when the assay readout is the proportion of positive cells. Concerning flow cytometers and readers, all instruments should be validated with proper controls and maintained under narrow margins (intra- and inter- site cross instrument validation). Scrambled peptides can be used to evaluate assay specificity. For ICS assays, it was recommended to identify proper technical/assay controls. Synthetic cells expressing proteins/peptides of interest can be used as positive controls. CRISPR/Cas9 gene edition tools could be used to develop negative cell lines to serve as negative controls. However, more case studies/ examples of these alternatives are necessary to verify their adequacy. When evaluating ICS assay linearity, there was agreement to start with diluted reference control samples and continue to further dilute as opposed to starting with undiluted material that can affect the outcome of linearity. Appropriate controls should be used, for example donor-matched unstimulated cells on a per sample basis should serve as the background to subtract from stimulated cells to obtain true positive signal. Similar approaches can be used to evaluate LOB, by subtracting 2 duplicate unstimulated conditions over a wide range of samples/repeats, as typically available from precision experiments.

Cytometry in Tissue Bioanalysis

Peripheral blood is an ideal matrix for flow cytometry applications from a multitude of perspectives. However, there are concerns that peripheral blood may not adequately represent the diseased site, e.g., the tumor microenvironment. Tissue flow cytometry provides direct insight to the diseased site to aid in identification of drug mechanisms of action, disease biology and potential clinical biomarkers. This includes classifying hot and cold tumors [64] since peripheral blood may not adequately represent the TME [65]. Measurement of target antigens by tissue flow cytometry can also guide CAR-T therapy in B-cell malignancies [66].

While tissue-based applications have many advantages there are also technical challenges in its routine use. Tissues need to be dissociated into single cell suspensions and the measurement of certain surface target markers might be compromised due to this processing step. As such, the dissociation process needs to be qualified before moving to the next step. Furthermore, the stability of tissue is limited not allowing for repeated analysis. The limited stability and processing requirements in conjunction with markers for analysis needing to be pre-defined, making it challenging to adjust if new clinical questions or hypotheses are raised during the period of analysis or during the long-term follow-up of patients.

ChipCytometry can quantitatively multiplex dozens of protein markers at the single-cell level using FFPE or frozen tissue sections, providing spatial composition of cells in tissues. It allows for repeated analysis of valuable clinical tissue samples which is especially useful for longitudinal biomarker studies. However, some challenges include antigen retrieval affecting the measurement of protein markers using FFPE sections, low throughput (only up to five markers can be stained simultaneously), and antibodies for FFPE tissues are not as broadly available as for fresh frozen tissues. Recommendations were discussed to address these challenges and validation strategies for tissue bioanalysis with flow cytometry and ChipCytometry.

For validation, there was agreement that tissue for QCs can be challenging to source, but artificial options exist. It was recommended that QC material should be properly identified or generated, ensuring that all necessary markers are incorporated. Tissue engineering approaches should be considered to serve as a surrogate control sample. This material can validate panels and the assay.

When processing tissue into a single-cell suspension, consensus was reached that it is important to consider the effects on cell viability, cleavage of the cell surface proteins, and the quantity of cells obtainable. It was also suggested that although CD45 can identify leukocytes, adding a viability marker is advisable. Suggestions were made to optimize mechanical and/or enzymatic digestion utilizing various buffers and qualify the entire process. Overall, it was recommended that ChipCytometry should be considered a viable option for limited tissue cells as this platform can render spatial information.

Innovation in Cytometry

Flow cytometry technology has evolved over the last several years, providing new technical advances such as full spectral flow instruments that, due to their optical design, are capable of measuring the full fluorescence spectrum. Currently, instruments up to 5 lasers allow determination of up to 40 fluorescent parameters. Although traditionally the research laboratories have benefited more from the advancement of the technology, the advantages of the spectral flow instruments have shortened the time for the transition from research to clinical trial settings.

Previous White Papers in Bioanalysis have discussed high dimensional assays [27,30]. Additional case studies were discussed demonstrating high dimensional assays running in clinical trials and challenges that still need to be solved. Benefits of high dimensional assays were shown to simplify oncology programs such as multiple myeloma to evaluate minimal residual disease. Seventeen-plex assays were used to identify plasma cells with better discrimination. High dimensional panel design can also compare different compartments from a patient and capture inter-patient heterogeneity. Finally, assays were shown to be used as prognostic biomarkers of cytokine release syndrome.

However, several areas for improvement exist. For high dimensional flow assays, there is an increase in time required for validation and increased turn-around time for data delivery. Gating strategies are complex and are usually conducted manually. Unmixing issues are frequent, requiring transferring of fcs files. Low frequency populations are also difficult to interpret. New data management workflows, semi-automated supervised gating, iterative validation strategies, and cryopreserved material for validation are the areas for improvement that were identified through this discussion.

Finally, new assay development and validation approaches, i.e. the modular model, were discussed. This model would allow a straightforward, leaner and cost-efficient development/validations of the assays, which would provide higher flexibility to the clinical programs due to the feature of dropping-in, dropping-out modules of a backbone assay.

It was recommended that high dimensional flow assays should be considered for exploratory endpoints while acknowledging that reportables are a challenge. Users should preserve a manageable/limited number of reportables to answer the clinical readout and consider other options to analyze HDF outside of CROs, whether internal or cloud-based solutions for HDF data analysis. Controls that allow for normalization should be highly considered.

Aside from high dimensional flow, other innovations were shown in mass cytometry, which utilizes isotopic heavy metal ions with significantly reduced signal spillover allowing the detection of over 40 markers. Although mass cytometry is a mature technology, there have been very few studies that have evaluated the accuracy and precision of mass cytometry relative to flow cytometry, which is especially relevant to clinical studies.

A case study assessed inter-assay precision, in triplicates and across three days of a single 24-parameter mass cytometry panel using a Fluidigm^® CyTOF Helios instrument to multiple 8-color flow cytometry panels with a BD FACSCanto^™ II instrument to immunophenotype T, B, and Myeloid cell subsets and report on select markers of interest. Thirty-seven individual reportables that were manually gated were compared between the two platforms for assessing variability within and across platforms. Overall, mass cytometry and flow cytometry were found to have highly similar levels of precision and nearly all reportables were quantitatively concordant. These observations support the utility of mass cytometry for clinical studies.

With both platforms showing utility in clinical studies, recommendations for preferred platforms between full spectrum flow and mass cytometry were provided. Full-spectrum cytometry was recommended when measuring parameters up to 30 colors. If >30 is required, mass cytometry should be considered with the caveat that CROs offering mass cytometry services are limited. Therefore, thorough evaluation of the expertise within the CRO, availability of validated panels, equipment, and data reporting capabilities were recommended. Data transfer with cloud-based storage and analysis environments should be utilized because of the size of HDF files.

Current Challenges with Cytometry Validation

Establishing analytic performance criteria that are fit-for-purpose in flow cytometry can be challenging. Hence, the first discussion topic focused on how to apply statistical approaches to fit-for-purpose validation in the context of a clinical trial for the interpretation of the flow cytometry data. Considerations were made for whether there are approaches other than % CV precision-based testing (e.g., confidence interval-based criteria) that could be applied to flow cytometry measures. There was agreement that application is limited in flow cytometry when there are more than a small number of readouts and exploratory uses. Alternative options include performing analysis, defining medians/ means, and confidence interval for RO and other flow assays.

A newer approach would be to enable studies in healthy donor samples with patient challenge (e.g., antigen challenge in Phase 1 studies). Historically, cohort sizes have been limited in Phase 1, but as Phase 1 cohorts increase in size these studies gain enough power, as is seen particularly with Project Optimus. It is possible to define biological variability in Phase 1 as part of iterative validation. In this scenario, the first validation demonstrates robustness of the assay. Use of patient challenge shows assay remains robust when used with patient populations. An additional case study was discussed where validation was performed on healthy donor samples spiked with cell lines to mimic AML patient samples due to time constraints before the assay was needed. The first set of patients were used to determine the gating parameters were appropriate. At this stage, an approach can be taken to determine target expressions in the patient population, for precision testing, to define the level of quantification possible, and to discriminate between standards.

Overall, it was recommended that the value of statistical approaches for validation depends on the assay and must be in agreement with previous recommendations [25,27,67]. It is necessary to have an initial statistical plan with a properly powered sample size to define acceptance criteria and regulatory authorities should be engaged as needed. Sponsors should attempt to assess the patient population early during validation. Because this is extremely challenging, the alternative approach to assess during a Phase 1 study, as described above, was recommended. As a final note, it is necessary to establish a collaboration between assay leads and clinical biomarker leads to plan ahead to ensure acquisition of the necessary samples for this approach.

A related discussion topic was to provide recommendations for validating cut- or decision-points where the assay may not have the precision to be quantitative but are above LOD [68]. Questions included 1) how to use this data, and 2) reasonable criteria to demonstrate adequate performance for determining which side of the decision point a particular measure lies. In this case, it was agreed that it is important to correlate decision points with functional response to a drug or emergence of another biomarker. It is necessary to explain limitations to clinical teams, as well. Ultimately, it is critical to clearly tag this data (e.g., imprecise analyte, informational purposes only). Regulatory authorities provided feedback that this data is useful/ valuable for identifying trends, but sponsors should state how criteria were met and keep data for future use.

Issues related to flow cytometry sample stability and validation continue to persist, as discussed in previous white papers [25,27,67]. Flow cytometry samples are usually very labile and, as such, irreplaceable. This often leads to choices around presenting data on sample measurements that are past quantifiable stability. Discussion aimed to determine whether there are acceptable ways to handle such data for exploratory uses, aside from outright exclusion. Examples were considered for situations where such approaches would be either appropriate or inappropriate. In addition, examples of fit-for-purpose statements that might support reporting of a sample past its quantitative stability were also discussed. Consensus was reached that careful evaluation of data and consideration of data in context with PK and ADA data is conducted. One approach is to determine how other internal teams can use the data generated, considering stability limitations of each measurement of the assay. An alternative approach would be to test the effect of stability on each measurement of interest. Similar to solutions described above, data that is determined to be beyond its pre-defined stability should be clearly identified.

A parallel discussion addressed possible methods to overcome challenges of sample stability for flow cytometry-based assays. The agreement was reached that it is typically not feasible to decrease time between whole blood collection and data acquisition due to the demands of clinical trials. Trials are getting more complex with more clinical sites located in an increasing number of countries. For RO, chemical stabilizers have been inadequate for improving sample quality. Commercially available tube options are improving (e.g., tubes for CDx assays, multiple myeloma), however, it is necessary to determine which of these tube types are most appropriate for a given clinical trial, since there is not currently a universally preferred option. The recommendation provided was to define the effect of time between collection and acquisition during assay validation (Does it bias data? Does it affect precision?). It was reiterated that it is necessary to highlight when data is for informational purposes only.

Next, with the advent of Project Optimus, whether data use is being viewed differently was discussed. The advent of the FDA's Project Optimus has resulted in re-evaluation of risk categorization in setting validation schemes. Flow cytometry assays, such as receptor occupancy or cell depletion measures, are often intended for PK/PD analysis as part of dose selection. These are often used by companies considering internal decisions that support their categorization as exploratory research use.

It was confirmed that requirements for fit-for-purpose validation still apply [25,27]. Biomarkers used in modeling for a regulatory decision, beyond internal decision making on appropriate dose, requires full validation. This applies to all biomarkers being used for PK/PD modeling. As described previously, it is important to be clear to internal teams about the limitations of the use of the data. The iterative approach in H62 lets sponsors add additional data to the validation. The H62 approach to increase confidence in assays is helpful in this regard [67]. Specifically, amendments to validation and assay can be made (e.g., additional gating strategy to existing data set). Finally, it was recommended to be explicit about data use, including justification, and to clearly show data integrity.

Another validation challenge discussed was what to do in cases where it is not feasible to obtain samples (e.g., rare matrices). There are logistical issues in obtaining rare matrices samples (biological variability of samples, cellularity, analyte frequencies) and limited controls, variability with sample quality (viability or hemodilution) and limited ability to add to validation with study samples as well. It was recommended to use the best option available to define the limitations of the assay. A potential alternative proposed was to use surrogate samples (e.g., spiked stimulated cells) even if not representative of disease. It is possible to describe in the validation plan those future clinical studies (e.g., post-marketing studies) that will be used to fortify the validation. Ultimately a device trial may be needed. It was also agreed that stability of critical reagents should be characterized and tracked, as they are crucial for assay performance and can largely impact detection of cell populations of interest.

Regarding validation requirements for assay modifications, it was discussed whether changes in an assay (e.g., gating strategies) can be incorporated in an iterative process after new data becomes available. Agreement was reached that changes to the assay and validation plan must be justified, documented, and the original data set should be analyzed with the modified analysis.

Biomarkers, RO, Macrophage Polarization & Phagocytosis Measurements

Demonstration of target engagement to cell surface receptors can be achieved with flow cytometry-based receptor occupancy (RO) methods. RO can link the pharmacokinetic data to a pharmacodynamic effect and is useful to inform in vivo binding affinity and target saturation to influence dosing strategy and safety assessments [25]. RO assays are challenging to develop and implement in clinical studies, requiring specialized reagents, stringent validation designs, controlled laboratory settings, and sufficient sample stability. These challenges increase when assessing RO of bispecific therapeutics that bind to multiple targets on distinct cell types and where depletion of one target cell is part of the therapeutic mechanism of action. During method development and validation, it is critical to select the appropriate assay format, blood collection tube type and reagents based on the design of the clinical trial, taking into consideration study site locations and sampling schedule. Therefore, there is agreement that selection of a global CRO experienced in supporting clinical flow with harmonization across testing laboratories is paramount.

Case studies dealing with these challenges were discussed from recent receptor occupancy assessments in clinical trials of bispecific T cell redirectors, with tips on what to consider during method development and validation to achieve desired assay sensitivity and stability. RO assays have been utilized to inform in-vivo Kd and compared to PK/PD modeling, in vitro results and can serve as an additional early indicator of MoA. Challenges of dual cell RO methods were discussed including differential affinity of bispecific arms, healthy donor vs. diseased matrix, and post-dose target cell depletion. Methods to identify specific cell types, such as tumor targets, were demonstrated to address challenges of heterogeneity between samples. Logistical challenges were also addressed including when to start method development to allow time for selection of detection antibody, validation parameters, when to start testing (FPI vs. when dosing is high enough), and tubes and kits to use and when to implement in a clinical study.

The recommendations provided focused on these challenges for flow cytometry tumor receptor occupancy assays for small molecules and bispecific antibodies. Development steps and challenges include obtaining viable cells, especially from core biopsies with high variance. It was agreed that comparison of shipping media is needed during development. Choice of dissociation methods (enzymatic vs. mechanical) can have large effects on target expression and must also be evaluated during development. Receptor internalization should be evaluated by confocal microscopy or similar technologies. Assessing tumor types with enough receptor expression and comparing concordance to whole blood assay should also be performed. Analytical validation can be performed in resected tumors with enough cellularity. A final recommendation was to describe the plan to use different sample types in the assay protocol.

Another case study addressed challenges in the development of novel flow cytometry assays for bioanalysis of pharmacodynamic markers with demonstration of macrophage polarization and phagocytosis measurements. Novel methods were developed to analyze macrophage markers by quantitating gene expression utilizing Nanostring^® Myeloid Innate Immunity Panel and flow cytometry. To assess pharmacodynamics, phagocytosis of fluorescent beads by monocytes was used. Fluorescent bead uptake by monocytes was measured by flow cytometry and confocal microscopy. There was consensus that these applications are novel applications of flow cytometry and more discussion at WRIB is needed to provide recommendation.

Cytometry Conventional/Novel Technologies & Main Applications

Flow cytometry assays in clinical trials have evolved in complexity over the past 4 decades, in parallel with the development of technology. Beyond characterizing cell populations and monitoring changes in immune cell composition in response to treatment, clinical assays have evolved to measure drug-target engagement and pharmacodynamic impact. Target engagement can be assessed through direct or indirect detection of receptor-bound drug, or through measurement of functional inhibition of a signaling pathway, with resulting data informing PK/PD modeling and dose selection. Flow cytometry assays have also been critical in the development of immune modulating treatments for both oncology and inflammatory disorders. Assessments of T cell activation or exhaustion, cell depletion or normalization of immune cell profiles are key in establishing proof of mechanism for drug candidates and optimizing clinical dosing strategies. The field continues to advance with the incorporation of spectral cytometers, increased fluorochrome availability and high dimensional analysis tools, allowing for refined identification of rare cell populations. These advancements enable generation of high dimensional data that informs disease biology and enables identification of novel biomarkers.

Increased dimensionality, complexity, and combination of this data with other “omics” platforms will require improved data analysis tools to maximize the information obtained during clinical studies.

AI/ ML based analysis will be required. The utility of these programs was also discussed in the 2021 White Paper in Bioanalysis and compared to conventional analysis [30]. Analysis using AI is becoming much faster. Experiences were shared that these analyses are primarily used in whole blood assays. It was recommended that analysis should be assessed internally if possible (e.g., 100 clinical sample study for correlation comparing manual and supervised ML gating), as quality issues (e.g., unmixing) can be introduced or amplified and there is often a need to manually gate artifacts. Quality issues can be mitigated by titration of antibodies, which should be done upfront. There was consensus that AI analysis should be established with documented stability of the biomarker among specific cell subsets and retraining is necessary if matrix changes. Although AI/ ML algorithms for automated gating are being developed and have demonstrated their potential to reduce the workload and the time for data delivery, the field is still in its inception phase and more studies showing a high correlation between manual and semi-automated gating results are needed.

As discussed above, flow cytometry data contributes to patient stratification, patient disease status, target engagement, PK and PD. Another discussion topic focused on which steps should be taken early during development to prepare for the transition of assays to companion diagnostics. It was agreed that use of flow cytometry assays for CDx purposes will be a need in the near future. Sponsors should determine early if another platform or a simpler binary assay should be considered. IHC approaches for CDx development may not apply. It was recommended to apply approaches for iterative validation discussed above.

Applications of newer cytometry technologies such as mass cytometry, CyTOF, and imaging cytometry were shared with discussion of challenges and solutions in implementation and future needs. Mass cytometry is a pioneer in high dimensional single cell cytometry that allows for the analysis of functional responses, quantitative biomeasures, as well as global immunophenotyping. This technique has played a key role in pharmaceutical development and continues to evolve in informing pre-clinical and clinical teams on binding, target burden, efficacy, and biomarker discovery.

CyTOF offers many unique advantages over spectral cytometry including multiplexing (e.g., multiple receptors), improved stability of reagents (i.e., can lyophilize antibodies for shipping to other locations), better for use in tissue, and more quantitative measures without compensation. There was consensus that one of the best applications is potential use for target spatial localization within tissue. However, limitations were discussed that need to be addressed for wider adoption in bioanalysis. There is limited availability of reagents other than some limited pre-made panels. Manual conjugation of antibodies is needed for adoption of <35 markers. Although conjugation is relatively easy, in-depth titration is also needed. Availability of services at CROs, cost, maintenance, logistics of installation, and lower throughput also need to be improved. Regarding approaches for assay development and validation, there was consensus to follow fit-for purpose principles for use consistent with conventional cytometry. It is recommended for high parameter lower throughput assays mass cytometry can be utilized for bioanalysis, but when higher throughput using a well-defined panel is required, a smaller spectral flow cytometry panel may be well suited. The ability to multiplex with barcoding, along with sample and reagent stability compared to fluorescent technologies, should be taken into account when performing longitudinal studies. CyTOF samples can be stabilized, shipped, and stored at -80 for long term storage, which allows for batch acquisition and decreased batch effects.

Additional discussion compared spectral flow cytometry with CyTOF. Light based flow cytometry has finally caught up with CyTOF in the number of markers that can be processed on a single sample, due to the advent of spectral flow cytometry. With spectral flow, the signal from each marker is not limited to a narrow bandwidth of peak emission, but it encompasses all the emission spectra across every channel in instrument. This gives each color a unique signature that can be used to distinguish between colors that were previously used interchangeably. Spectral flow has had great impact in the field of clinical flow cytometry with many commercial labs now switching over to primarily spectral based instruments for their exploratory clinical sample analysis. Spectral flow has helped reduce the amount of blood needed from patients, reduced the overall number of panels needed to be analyzed per timepoint and enhanced the ability to correlate multiple measures on discrete cell populations. Case studies were presented where spectral cytometry was used to enhance key target engagement assays to yield much more valuable data. It is unclear yet what impact spectral flow will have on regulated assays required for primary endpoints, secondary endpoints, and for assays directly contributing to patient management, but there could be advantages to assays such as MRD.

Another technique, imaging flow cytometry combines the throughput of flow cytometry with the capabilities of fluorescence light microscopy to visualize samples. This platform interrogates numerous characteristics of cell morphology and intensity and spatial features of the signals generated by fluorescence markers, resulting in abundant data on cell phenotype and biological functions. Therefore, quantitative image analysis performed with imaging flow cytometry instruments provides valuable measurements informing on the target-drug interactions and functional responses. Building on the 2021 recommendations on the topic of applying imaging cytometry in preclinical development of biotherapeutics [30], approaches for implementing imaging flow cytometry for cellular biomeasures was discussed. There was agreement that the best applications of imaging cytometry include target engagement, half-life, RBC characterization, and other examples from previous White Papers. Barriers for wider adoption in bioanalysis include developing standardization and validation strategies. There is limited throughput and harmonization to other platforms because of additional layer of image analysis.

RECOMMENDATIONS

Below is a summary of the recommendations made during the 16^th WRIB:

Vaccine Functional Assays

• Best practices were recommended for bridging, critical reagents, and instrumentation for development of vaccine functional assays.

  • Identify proper technical/assay controls, titrate antibodies, understand specificity.

  • Validate instruments with proper controls and maintain narrow margins, perform intra- and inter- site instrument validation.

  • Start with diluted reference control samples and continue to further dilute to show linearity as opposed to starting with undiluted material that can affect the outcome of linearity.

  • Matched unstimulated cells on a per-sample basis should serve as the background to subtract from stimulated cells to obtain true specific signal.

• Recommendations were provided on operational and pre-analytical considerations for implementation in global clinical trials.

  • Understand assay(s) that will be executed, collection tube specifics, fresh vs. fixed cells, local or central lab stability concerns.

  • Time from blood collection to PBMC isolation and cryopreservation should be minimized, and the impact of holding time should be evaluated and explicitly stated.

  • Validate the loss of cells/function over time, ensure that cells when assayed are at same maturity (time point since collection)

  • Temperature controls should be implemented when shipping frozen PBMCs.

Cytometry in Tissue Bioanalysis

• Strategies were provided for validation of tissue flow cytometry or ChipCytometry for clinical use.

• ChipCytometry should be considered a viable option for limited tissue cells as this platform can render spatial information; may also be plagued by processing challenges.

• Processing tissue into a single cell suspension is a key consideration. Consider effects on quantity, quality, viability, and cell surface protein stability. It was suggested to optimize digestion with multiple buffers.

• It was recommended that QC material should be properly identified or generated, ensuring that all necessary markers are incorporated.

  ○

  Engineered tissues should be considered as surrogate controls.

Innovation in Cytometry

• High dimensional flow assays should be considered for exploratory endpoints while acknowledging that reportables are a challenge.

• Users should preserve a manageable/limited number of reportables to answer the clinical readout.

• Controls that allow for normalization should be highly considered.

• The role of mass cytometry vs. full spectrum cytometry was compared. It was recommended to use full-spectrum cytometry to measure parameters up to 30 colors. If >30 is required, mass cytometry should be considered with the caveat that CROs offering mass cytometry services are limited.

• It is suggested to thoroughly evaluate expertise within the CRO, availability of validated panels, equipment, data reporting capabilities.

Current Challenges with Cytometry Validation

• Have a statistical plan upfront with a properly powered sample size to define acceptance criteria. Engage agency earlier. You should try to assess the patient population early during validation, which is an extreme challenge, so there is an alternative approach to assess during Phase 1 study.

  	○	Can define biological variability in Phase 1 as part of iterative validation. First validation shows assay is robust. Use of patient challenges shows assay still robust in-patient populations.
  	○	Statistical approaches such as confidence interval-based criteria for FFP validation have limited application due to multiple readouts.

• For validating cut point decisions where an assay may not have precision to be quantitative, any approach is ok with justification and correlation to other measures. Current guidance applies to quantitative assays. No specific validation recommendations were made.

• For data for samples outside of established stability, look at data carefully and clearly tag data.

  	○	There was consensus on examples for flagging data (imprecise analyte, informational purposes only, interpret with caution) Regarding approaches to extend stability, define effect of time in validation (Does it bias data? Does it affect precision?). Define the limitations of technology too. Define when data is/ is not reliable using flags discussed above.
  	○	Commercially available stabilizer tubes are improving but marker specific.
  	○	Reducing time from collection to acquisition is challenging due to complex global trials.

• There was an agreement that validation strategy does not change due to Project Optimus and PK/PD analysis for dose selection.

  	○	Requirements for fit-for-purpose validation still apply. Biomarkers used in modeling for a regulatory decision beyond internal decision making on appropriate dose need full validation.
  	○	Employ an iterative approach as described in H62 to add additional data to validation.

• To validate assays in rare matrices, discuss with regulators and set expectations with sponsors ahead of time. Regulators will be receptive when presented with proper justification of limitations and the best possible plan.

• Critical reagents are crucial to assay performance, with large impact to population identification, so stability should be characterized and tracked.

• Changes in assay (e.g., gating strategies) after new clinical data can be incorporated in an iterative process.

Biomarkers, RO, Macrophage Polarization & Phagocytosis Measurements

• Challenges to developing tumor RO assays include obtaining viable cells from biopsies, optimizing shipping media, and variable dissociation methods.

  	○	Evaluate if there is a need to do RO in tumor and consider other TE assays in tumors (e.g., IHC) and blood (accounting for PK using models). Understand limitations if flow is the only option and have this discussion with clinical biomarker group. The use of flow cytometry in clinical studies has continued to increase over the past 40 years. Increased dimensionality and complexity and combination of this data with other “omics” platforms will require improved data analysis tools to maximize the information obtained during clinical studies.
  	○	AI/ ML based analysis will be required. Show examples why validation for secondary endpoint will be very difficult.
  	○	Analytical validation can be performed in resected tumors. Describe plan and different sample types in protocol. Variance in cores can be considered a pre-analytical variance.

• Measurement of phagocytosis and extracellular vesicles with flow cytometry are up and coming applications but need more experience is needed for recommendations.

Cytometry Conventional/Novel Technologies & Main Applications

• The use of flow cytometry with increased dimensionality and complexity and combination of this data with other “omics” platforms will require improved data analysis tools. Recommendations were provided for AI/ ML based analysis.

• Unsupervised analysis can enable important (unbiased) discoveries and can be compared to supervised approaches.

• There was agreement that software should be validated, and it is best used for screening assays.

• For data that will contribute to patient stratification, disease status, PK/PD, engage with regulators (e.g., CDRH) and comply early, comply with NY state for LDTs – at least for Phase 2 use

  ○

  IHC approaches for CDx may not apply.

• Panel recognized the limitations of imaging cytometry but agreed it has utility in very specific cases. More experience is needed - more expertise from people with microscopy experience and training of the community is needed too.

SECTION 3 – LBA, Enzyme Assays & Critical Reagents

Fred McCush³⁹, LaKenya Williams²⁰, Sally Fischer³¹, Bonnie Wu³⁷, Gregor Jordan²⁶, Chris Burns¹⁰, Isabelle Cludts¹⁰, Kelly Coble⁴⁰, Christine Grimaldi¹, Neil Henderson⁴¹, Alison Joyce⁴², Gregor Lotz²⁶, Yanmei Lu⁶, Linlin Luo³³, Florian Neff²⁶, Xiazi Qiu²¹, Gizette Sperinde³¹, Kay-Gunnar Stubenrauch²⁶, Yuting Wang²¹, Mark Ware³⁷ & Weifeng Xu³³

Authors are presented in alphabetical order of their last name, with the exception of the first 5 authors who were session chairs, working dinner facilitators and/or major contributors.

Author affiliations can be found at the beginning of the article.

HOT TOPICS & CONSOLIDATED QUESTIONS COLLECTED FROM THE GLOBAL BIOANALYTICAL COMMUNITY

The topics detailed below were considered as the most relevant “hot topics” based on feedback collected from the 15^th WRIB attendees. They were reviewed and consolidated by globally recognized opinion leaders before being submitted for discussion during the 16^th WRIB. The background on each issue, discussions, consensus, and conclusions are in the next section and a summary of the key recommendations is provided in the final section of this manuscript.

Novel Technologies & Automation in LBA

Should there be a FFP validation for assays developed on new platforms? How much DoE documentation should go into the submission dossier demonstrating how final assay conditions were established? What is the impact of automation on the validation of assays for large molecule bioanalysis? Can we consider using singlicate for LBA sample analysis when using automation? What are the practices for controlling consistency and understanding variability of performance in the application of automated liquid handling for multi-step assays employed in large molecule bioanalysis? What are the main challenges involved in automation instrument validation? How do we advance the change curve for laboratory scientists with respect to using automation for bioanalytical methods? Are CROs able to support ADA assays using automated pre-treatment approaches? How can sample pre-treatment procedures be streamlined for immunogenicity assays? What are the challenges encountered during the automation of pre-treatment procedures for immunogenicity assays?

Novel Modalities, Novel Method Development/Validation Challenges

What are ERT assays being used for? What are the unique challenges of enzyme assay development and validation for cell and gene therapy compared with ERT? What are the best practices of enzyme assay development and validation? What needs to be measured (of the RNP components) for the different routes of administration/context of use of trans gene expression? With commercial reagents available, sensitive methods can be generated. What are the thoughts on the sensitivity required to deploy a method to detect/show the absence of cas 9 protein? Novel modalities of drugs in “nontraditional” matrices that are difficult to obtain can pose a challenge during validation - can validations use relevant tissue surrogate matrix (e.g., vitreous fluid, CSF)?

Rare Matrices

Are there examples where PK measurements in non-standard matrices from animals' studies are/are not predictive of target tissue exposure and exposure-response relationships which have been useful for clinical PK/PD modeling? Are there examples where the ADA assessment in non-standard matrices is markedly different than ADA assessment in the systemic circulation? In order to reduce ocular sample consumption, ocular PK might be monitored by surrogate plasma samples and a suitable model which allows back calculation from plasma to vitreous or aqueous humor. Is such an approach acceptable? What would be required? Ultrasensitive analysis, multiplexing and/or microfluidic technologies offer opportunities to reduce ocular sample consumption. Are there further recommendations?

Problem Solving for Complex NAb Assays

What are the viable assay platforms to detect weak drug-target interaction? For multi-specific biotherapeutics, is domain mapping necessary for NAb assessment? When is NAb assay needed? What alternative methods exist for currently wide-used extraction methods [e.g., acid dissociation and biotin-drug competition (BEAD, SPEAD)] to improve drug tolerance?

Critical Reagents Deep Characterization

What are the general considerations in critical reagents deep characterization? Can we integrate the ADA and soluble target interference testing (I) to the CPF (concentration/ purity/ functionality) concept and change it to a CPFI concept as recommended standard approach? How to optimize labeling ratio in critical reagents generation in ADA assays to reach optimal binding profile? What are the community's preferences or recommendations for selecting SPR or biolayer interferometry (BLI) when characterizing LBA reagents?

DISCUSSIONS, CONSENSUS & CONCLUSIONS

Novel Technologies & Automation in LBA

Ligand binding assays (LBA) are the most commonly used bioanalytical methods in research and development of protein therapeutics. The gold standard and the most used LBA platform is the enzyme-linked immunosorbent assay or ELISA. However, despiteits popularity, attributable to lower costs as there is no need for expensive equipment or high level of expertise, it does have a number of limitations. ELISAs are labor and reagent intensive, in many cases lack adequate sensitivity, present a limited dynamic range and are prone to matrix interference. There are now numerous LBA technologies that have addressed the limitations of the ELISA platform [69]. These include technologies such as Gyrolab, which uses very small volumes and can overcome matrix interference; Single molecule count technologies such as Quanterix Simoa and Millipore SMCxPro, offering sub pictogram sensitivities, and multiplex technologies such as ProteinSimple Ella and MSD platforms. Each of these multiplex technologies has addressed a specific challenge but no one technology has all the elements desired and therefore careful consideration is essential to select the most appropriate technology for the needed measurement. These technologies have enabled evaluation of analytes in serum and/or plasma as surrogates for site of action, but also interrogation at the site of action. However, in additional to technical considerations, implementation and long-term support are also critical in the selection of a technology. For example, it is important to consider availability of off the shelf kits vs. home brew assay and the ability to generate consistent home brew assays for large studies.

[68]. Case studies were discussed illustrating the capabilities of these promising technologies and their impact on drug development. For example, Gyrolab technology was able to overcome the matrix interference in a new indication for a previously validated PK assay by significantly reducing the incubation times [70]. Another study demonstrated a solution for measurement of PK and biomarkers in peripheral circulation as surrogates for site of action to address challenges of sample collections in difficult matrices. Tissue-adjacent matrix evaluation requires increased sensitivity due to drug partitioning, microsampling, and dilution upon recovery from device. The case study demonstrated use of ultrasensitive platforms (SMCxPro, Simoa) to successfully measure baseline and on treatment changes in biomarkers [71]. There was agreement that these case studies demonstrated effective use of new LBA technologies to solve issues of matrix effect, low sample volume and sensitivity when applied judiciously with an understanding of the advantages and disadvantages of each platform.

It was discussed if FFP validation should be used for assays developed on these newer modalities. There was agreement that FFP validation may be dependent on endpoint and stage in clinical development regardless of the technology used. Fully validated assays should be used if appropriate for the COU, but if it deviates from this guidance, then justification should be provided. If an assay answers a specific question outside of the validated assay (i.e., exploratory), then only a minimum amount of characterization is needed to determine that the assay is reproducible and scientifically sound. A FFP assay may be used for supporting information, in tandem with a validated assay used for endpoints.

Another discussion topic was the challenges and need for normalization for analytes in tissue measurements. There was agreement that normalization should be done depending on the COU and where feasible. For quantitative tissue measurement, normalization is needed but one normalization scheme does not apply to all tissues. It was also agreed that normalization methods in novel matrices and PC selection needs further discussion.

Besides new LBA platforms, the application of automation to existing LBA platforms could be highly desirable to large molecule bioanalysis. Automation is also highly suitable for LBA because of the similarities in the basic components that are used, and the lack of change imparted upon methods over time, e.g., liquids, plates, tubes. The degree and extent of the integration and choice of automation should be determined firstly by understanding the benefit of making such investments and disruptions in operations. Other practical considerations discussed demonstrated the importance of considering infrastructure changes, access to pools of talent, IT infrastructure, and data scientists. Other hurdles include on-site testing of the automation before implementation, computer systems validation, adoption of equipment by the scientists and monitoring/ maintenance of performance to ensure long term benefits to assay performance and business needs. Several examples were discussed for automation of bioanalysis and sample analysis through integrating automated liquid workstation approaches for flexibility of operation which impacted throughput and quality of operation and automated data analysis when executed correctly. These included assay development steps, preparation of quality controls, standard curves and sample dilution for bioanalysis.

Other case studies were shown using automation implemented for both PK and ADA assay development. Automation makes comprehensive design of experiment (DOE) possible, leading to improvement in robustness, reproducibility, reliability, and throughput. Screening and selecting optimal reagents and assay format are critical in the development of robust PK assays. In the first case study, development of an automated workflow and scoring system was shown, which allowed for a quick ranking of candidate anti-idiotype antibodies (anti-IDs) anti-IDs with a variety of criteria, to identify the best anti-ID pairing and PK assay format. The identified anti-ID pair and assay format were compared with the selection from the standard manual approach.

In the second case study, a novel workflow incorporating DOE concepts and automation technology to optimize the ADA assay conditions was discussed, achieving the needed sensitivity, and required drug tolerance, and avoiding low cut point in order to provide more clinically relevant ADA data. Overall, experience has demonstrated that PK and ADA assay development could benefit greatly from incorporation of an automated bioanalytical workflow consisting of automated assay implementation and data analysis.

Another aspect of anti-drug and neutralizing antibody assays that could utilize automation are the complex ADA enrichment steps using magnetic beads to improve assay sensitivity and drug tolerance. Using beads for sample pre-treatment steps is time-consuming and resource intensive as optimization may be necessary for each project. In addition, coupling procedures may have batch-to-batch variability and stability issues, and bead-based methods may be difficult to transfer between labs. Bead procedures for depletion or enrichment have many manual steps using magnets, and bead loss during washing on plate washers can lead to imprecision and reduced recovery of ADA.

Automation of these procedures and/or bead alternatives were demonstrated to be an attractive approach to improve assay robustness, shorten timelines, reduce repetitive pipetting injuries and conserve resources. One solution shared was the use of Biotage PhyTip^® columns which provide dual flow chromatography capability in a pipette tip column and are designed for use on many different automated liquid handling systems, without the need for magnetic beads. One case study demonstrated successful use of streptavidin PhyTips for automated ADA enrichment for immunogenicity assays with high drug tolerance goals. Another case study focused on PhyTip use for target immunodepletion. This could be applied to the removal of target interference in ADA assays or target depletion to demonstrate specificity or aid in selectivity testing for biomarker assays. There was also agreement that CROs can offer these capabilities.

Recommendations for utilizing and implementing these automation steps in LBA laboratories were shared. It was discussed whether DoE documentation should go into the submission demonstrating how final assay conditions were established. It was recommended to keep a documented internal history on development details, but it was not recommended to add development details in submissions unless something is critical to the method.

There was also agreement that automation should be validated as the method would be used but it also is important to consider data integrity when using automation (e.g., security/change control of execution scripts, audit trails, equipment logs, batch log, archiving) with staff dedicated to computer system validation. If statistical analysis determines singlicate analysis is acceptable, then it could be possible following published recommendations [72]. The recommendations for controlling consistency and understanding variability of performance in the application of automated liquid handling for multi-step assays employed in large molecule bioanalysis was that formal calibration procedures were needed for each liquid handler, outside of the individual methods.

Suggestions were provided for advancing the learning curve for laboratory scientists with respect to using automation for bioanalytical methods. These recommendations included creating a simple graphical user interface to facilitate use for operators, creating a dedicated automation team, using automation as a time saving incentive, and trying for more standardized methods to simplify use.

Novel Modalities, Novel Method Development/Validation Challenges

LBA development and validation challenges were discussed for novel modalities including enzyme assays, measurement of CRISPR gene editing components for PK, and LBA assays for PK measurement of complex, multi-domain, recombinant proteins.

Enzyme assays

The major focus of the discussion was the development and validation of enzyme assays. The current standard of care for enzyme deficiencies is enzyme replacement therapy (ERT) and/or small molecule chaperones. In vivo gene therapy and ex vivo cell therapy is promising new therapeutic approaches for the treatment of hereditary monogenic disorders. During preclinical and clinical drug development, enzyme activity measurements serve as diagnostic biomarkers for disease detection and confirmation, important pharmacokinetic readouts for ERT as well as pharmacodynamic biomarkers for other therapies such as gene and cell therapy. An enzyme assay determines the specific activity (or concentration) of an enzyme by measuring the quantity of substrate consumption or more commonly, product formation over the course of a reaction. An enzyme activity assay is often preferred over measuring the amount of protein using protein quantification methodologies such as ligand binding assay.

A range of enzyme assay technologies are available, among which fluorescence-, absorbance-, and luminescence-based detections are more frequently used. An example of a fluorometric assay is measuring the increase of fluorescence from a converted product, 4-Methylumbelliferone (4-MU), upon cleavage of a fluorogenic substrate during an enzyme reaction. This assay design is a direct measurement of the fluorescent product produced in a single step reaction. The assay signal recording mode can be a single end point reading predetermined within the linear reaction time window or kinetic continuous recording of product appearance over time.

For ERT, the recombinant protein drug product is readily available as a reference material to create calibration curves, from which enzyme activity (or concentration) in a sample can be calculated. Enzyme assays for gene and cell therapy present a unique challenge as reference materials are lacking because the enzyme is produced in vivo from a transgene. Recombinant enzymes from different vendors may vary widely in activity due to purity and conformation. One solution is to use the synthetic 4-MU fluorophore, the enzyme cleavage product as a standard curve to calculate activity. The activity determination using the 4-MU product curve is independent of a surrogate recombinant enzyme. The 4-MU curve, however, does not account for variations of enzyme reaction in samples from run to run.

Therefore, assay quality controls (QCs) prepared from recombinant enzymes are employed to monitor assay performance and determine fate of run. It is highly recommended to include at least one QC containing endogenous analyte to better represent endogenous analyte in samples. The recombinant enzyme is also used during assay development to optimize buffer composition and determine enzyme kinetic parameters based on a Michaelis-Menten model, which guides the selection of substrate concentration and linear reaction time. It is important to confirm that the enzyme curve is parallel to the 4-MU product curve under the final optimized assay conditions before initiating assay qualification and/or validation.

Regulatory guidance specific for enzyme assay validation has not been established. Nevertheless, the European Medicines Agency (EMA) and Center for Drug Evaluation and Research (CDER) guidelines on bioanalytical method validation for ligand binding assays provide good references and general principles to follow. During method validation (or qualification), the parameters to evaluate include range of quantification, precision, accuracy, matrix effect and minimum required dilution, parallelism, selectivity/specificity and stability. QC plate acceptance criteria can be established from the precision and accuracy runs. Selectivity can be assessed by spiking enzyme QC in individual sample matrix (often containing endogenous enzyme), or heat inactivated matrix (if endogenous enzyme activity is too high).

There was consensus that ERT assays are being used for protein activity, Factor VIII activity (these assays fall under CLIA, and are well validated). For ERT, it is necessary to have drug products for reference standard, which is more challenging for gene therapy.

LBA for Cas9

The next category discussed was therapeutic gene editing (TGE) technologies such as CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated 9) and their LBA needs. This technology has been used to greatly investigate molecular pathways that may be involved in disease. Moving CRISPR-Cas9 from bench to bedside offers a potential revolutionary approach to treat disease through permanent gene editing. The functional CRISPR-Cas9 RNP (ribonucleic protein) complex is composed of a Cas9 protein and a guide RNA (gRNA) sequence. There are many factors that will influence the bioanalytical strategy required to progress these potential therapeutics through drug development and to meet regulatory expectations. These include, but are not limited to, whether the RNP complex will be applied ex vivo or in vivo (directly or indirectly), the route of administration and delivery approach, such as lipid nanoparticle (LNP) or adeno-associated virus (AAV), and if the RNP complex is dosed as DNA, RNA or protein.

Method development challenges and solutions for these assays were discussed, including the identification and sourcing of suitable analytical reagents, to be able to fully understand the bioanalysis of CRISPR-Cas9 components. Different LBA approaches for the measurement of Cas9 protein (e.g., SaCas9 and SpCas9) and LBA strategies for measurement of the guide RNA were discussed. There was also discussion on what needs to be measured (of the RNP components) for the different routes of administration/context of use of transgene Expression. It was recommended to start broad then narrow focus and determine critical end point vs what is nice to have. The components needed depends on therapeutic MOA, and delivery system. Priority should be to measure edited vs non-edited, viral vector: shedding or lack of shedding.

Another topic was the sensitivity required to deploy a method to detect/show the absence of Cas9 protein. If a good faith attempt is demonstrated for sensitivity, then justification of the sensitivity of the assay is often good enough. Overall, there is no requirement to assay Cas9 and it was agreed that preemptive approaches can be used.

PK measurement of complex, multi-domain, recombinant proteins

Another novel method development challenge for LBA assays is PK measurement of complex, multi-domain, recombinant proteins. The development of recombinant fusion proteins as drugs poses unique challenges for bioanalysis. A case study was described of a glycosylated fusion protein, where variable glycosylation, matrix interference as well as high sensitivity needs posed unique assay development challenges. Protein glycosylation can add a high degree of complexity to the bioanalytical development of assays, Therefore, a thorough bioanalytical evaluation of assay reagents and platforms was undertaken. After the selection of reagents was finalized, an additional evaluation took place to evaluate six different assay configurations, across four different platforms for the measurement of drug concentrations. The two platforms that achieved the assay requirements were Simoa HD-1 and immune-capture LC-MS/MS based assay. Both the Simoa HD-1 –and the mass spectrometry- based methods were able to detect total drug by providing the adequate matrix tolerance, required sensitivity and detection of all the various glycosylated fusion proteins to support clinical sample analysis. The Mass Spec based method was selected for validation and subsequent study support, due to robustness and ease of method transfer.

Rare Matrices

There is an increasing trend for administration of biologics by alternative routes such as intravitreal, inhaled, intrathecal and intratumoral. Typically, the relatively large size and biophysical properties of biologics limit tissue penetration, and for some drugs, it may be essential to direct the drug closer to the anatomical site of the disease. While much of our understanding of the adsorption, distribution, clearance and immunogenicity of biologics has been gained through experience with intravenously and subcutaneously administered drugs using assays that evaluate whole blood, less is known about the fate of biologics administered by non-standard routes. Tissue specific bioanalytical assays may aid in the understanding of exposure-response relationships when the biologic leaves the tissue site of administration and distributes to the blood. It is important to consider the value of PK and/or ADA readouts from tissue matrices and devise a sound bioanalytical strategy to address key scientific questions.

Gaps were discussed surrounding the PK and immunogenicity of biologics given by non-standard routes. BA challenges for inhalation and oral delivery of biologics were discussed previously [31] where it was agreed that novel routes may improve patient experience, but bioanalytical challenges include poor bioavailability and more invasive collection. Serum PK profiles and ADA are important components. A case study was also discussed of PK validation in monkey vitreous humor. Sourcing this rare matrix is difficult and a surrogate matrix for validation is necessary. Points to consider for PK assays including using animal data to provide insight into exposure levels and target engagement. This provides useful PK/PD modeling and can provide more direct bioavailability. ADA assessment in non-standard matrices was not recommended.

These case studies led to discussion of whether PK measurements in non-standard matrices from animal studies are/are not predictive of target tissue exposure and exposure-response relationships which have been useful for clinical PK/PD modeling. While examples exist, it was agreed that the biggest unknown is the PD component. Turnover of target is unpredictable when moving from animal to human. There are also not many examples where the ADA assessment in non-standard matrices is markedly different than ADA assessment in the systemic circulation. In ophthalmology studies, there was agreement that ADA data of plasma, aqueous and vitreous humor correlate well, as a rather large sets of pooled cynomolgus and minipig ADA data shows [73]. Therefore, systemic ADA analysis was agreed to be sufficient for ADA evaluation. Tissue assays were not recommended.

Challenges and solutions in method development and validation for LBA ophthalmology bioanalysis was also discussed. During the last years, the FDA has approved several biotherapeutics for the treatment of wet age-related macular degeneration and other diseases in ophthalmology. There are issues specific for ophthalmology and intravitreal (IVT) administration, e.g., limited availably of ocular samples, small volume and rather high demands on assay sensitivity – in particular for soluble targets and protein biomarkers. Several assays designs and corresponding data were shown, the experience with ultrasensitive technologies, like Simoa, was shared [74]. Regarding immunogenicity testing, the incidence and amount of “ocular” ADA were compared with “systemic” ADA from plasma samples by a large pre-clinical data set from cynomolgus monkey and minipig [75].

To reduce ocular sample consumption, it was asked if ocular PK may be monitored by surrogate plasma samples and a suitable model which allows back calculation from plasma to vitreous or aqueous humor. There was agreement that this approach is acceptable. Subjects generally don't want ocular tissues taken, so default is to plasma. Ultrasensitive analysis, multiplexing and/or microfluidic technologies were shown by experience to offer opportunities to reduce ocular sample consumption. Gyrolab was recommended if good reagents are available; new CD is also a positive for this approach. It was also suggested trying acoustic dispersion, iDot, or Olink using proteomics technology (high multiplexing, using very small sample volume).

Problem Solving for Complex NAb Assays

Immunogenicity testing to measure and characterize anti-drug antibodies is required for almost all biologic therapeutics. One common problem is that monoclonal antibody biotherapeutics usually have long half-lives and for high-dose indications such as oncology, high levels of drug will be present in the samples and therefore interfere with ADA and/or neutralization antibody (NAb) measurements. To overcome this drug interference, acid-dissociation-based sample pre-treatments such as bead-extraction and acid dissociation (BEAD) to dissociate the drug/NAb immune complex with harsh acid, followed by biotinylated-drug competition for NAb binding and extraction, have been successfully applied. The major concern for these acid-dissociation based methods, however, is that harsh acid treatment could potentially denature positive control Abs as well as NAb species in samples. In addition, high amounts of biotinylated drug are needed to effectively compete with high levels of drugs in the samples, which in turn requires significant amounts of expensive magnetic beads [76,77].

A novel approach was discussed to remove free drug in serum samples, using PEG to selectively precipitate drug/NAb immune complexes; the precipitated pellet is then treated with a mild and short acid dissociation to release NAb. Since free drug is mostly removed and the pellet contains a roughly 1:1 ratio of drug and NAb, only a small amount of biotinylated-drug is needed to not only compete for NAb binding, but also to be used in the down-stream competitive ligand binding NAb assays. Biotin-drug with or without bound NAb will be captured on SA-coated MSD plates, followed by ruthenium-labeled drug target as detection reagent. This novel method needs only one acid dissociation step, which is much milder and shorter, to maximally preserve NAb activity. In addition, there is no need for additional SA-plates or SA-magnetic beads thanks to the much-reduced amount of biotin-drug [78].

Other alternative methods for the currently widely used extraction methods [e.g., acid dissociation and biotin-drug competition (BEAD, SPEAD)] to improve drug tolerance were discussed. For example, heating instead of acid can be used to dissociate immune complex, especially for biotherapeutics with low molecular weight and low thermal stability [79]. In addition, high ionic strength dissociation assay (HISDA) using MgCl₂ could be used. However, this approach will need optimization as currently the method is only based on literature and may suffer from low compatibility with downstream procedure, especially in cell-based assay [80]. Therefore, buffer exchange may be needed. For biotin-drug competition essay, a higher dilution, e.g., 1:20, was recommended to increase drug tolerance. However, this may decrease signal readout.

These case studies led to discussion of viable assay platforms to detect weak drug-target interaction. There was consensus that if the drug trough concentration is high (especially in oncology indications), non-cell-based competitor LBA assay and/or assay platform with minimal wash steps is recommended. Guidance was discussed for rules to follow in selecting the assay platform to detect weak drug-target interaction which included using homogenous assay with no or minimal wash, signal amplification for the binding, and required pretreatment to deplete drugs.

Another discussion topic was for multi-specific biotherapeutics, focusing on whether domain mapping is necessary for NAb assessment and when a NAb assay is required. There was wide consensus that domain mapping for NAb assessment is not required but recommended by regulatory agencies to determine the NAb specificity for protein therapeutics with multiple functional domains. It was also recommended to engage in conversations with internal stakeholders (e.g., clinical pharmacology) and regulatory agencies to assess the timing for NAb assay development. In early clinical development, PK profiling that includes total and free may be helpful for understanding potential impact of ADA in the absence of a Nab assay. If the PK profiles do not correlate with each other, more immunogenicity data will be needed to help interpretate the results. Whether NAb sample analysis is needed or not will depend on the pharmacodynamic model [81]. If just to explain drug level change profile, ADA data is sufficient. If there is need to answer questions around efficacy and drug function on the other hand, then NAb assessment for study samples or appropriate PD read out with active PK assay is needed.

Critical Reagents Deep Characterization

Currently, many ligand binding assays for large molecules are developed empirically. This means that reagents are used and titrated against each other with different permutations to determine the best combination of reagents and/ or optimal incubation conditions. Nevertheless, the question arises of what is known about the reagents in terms of their binding kinetics, K_D, affinity, and what deep characterization parameters can be used to support the development of an assay through calculations and modeling.

One advantage of assay development supported by calculation is that different combinations can be quickly simulated, and equilibrium conditions can be compared with kinetic assay conditions. It is thus easy to assess which reagents may need to be better characterized in terms of their binding kinetics. On the other hand, questions that arise with calculations are the need for a precise K_D value describing the interaction of drug with the soluble target and whether the capture reagent always has to have a lower affinity to the target in target engagement assays.

Another important discussion was around target antigen reagents as critical reagents for clinical PK assay development. Deep biochemical characterization of the target-antigen reagent proves its physiological function and is the prerequisite for the development of an appropriate active PK assay. The reagent characterization allows for a proper assessment of anti-drug-antibody (ADA) impact on active drug exposure and therefore, for an understanding for ADA interference on drug-to-target interaction. However, a deeper functional characterization of target-antigen reagents for clinical assay development is often missing. Recently, FDA has published a survey of 28 development cases concluding that the community is far from a harmonized approach to assess ADA and soluble target interference [43]. It was discussed that the proof of the biological activity of the recombinant target antigen and its functional binding to drug are key parameters to select it as proper reagent for the PK assay development. The comparison of drug binding to recombinant target-antigen reagent versus cell membrane target antigen receptor together with similar ADA interference testing in both settings is another important layer of physiological characterization and a key parameter for the selection of an appropriate tool for an active PK assay development, as well as competitive ligand binding Nab assay. Therefore, PK assays using deep characterized target antigen reagent measuring active exposure are sensitive for a physiological relevant impact of ADA on exposure, once ADA response is in the patient detected, along the lines of ADA interference of drug binding to its target.

In the 2019 White Paper in Bioanalysis, strategies for critical reagent management are described. The overall recommendation in this White Paper is to measure concentration, to determine purity, and to assess functionality by an orthogonal method as important parameters for deep reagent characterization and it is defined as CPF (concentration/purity/functionality) concept. The fact that the assessment of ADA and soluble target interference is of integral importance for functional characterization of the target-antigen reagent and for the development of an appropriate active PK assay, it is recommended to expand the CPF concept to CPFI concept. The “I” stands for the Interference testing and should be part of the standard approach, at least for drugs with high-risk immunogenicity profile or known soluble target interaction.

Recommendations were also given on how to optimize labeling ratio in critical reagent generation for ADA assays to reach optimal binding profile. The consensus was to go as low as possible for labeling ratio, without compromising the assay signal. Characterizing the reagent after labeling was recommended. It was also recommended to use a small batch and test different ratios (low, mid and high). The ratio that gives the highest sensitivity may not be the final optimized ratio and has to be confirmed using a positive control for ADA assay. When going into large batch generation, there is a need to monitor real time incorporating ratio and perform batch-to-batch cross validation for different lots of labelled reagents [82].

Biosensor technologies - in particular surface plasmon resonance (SPR) and bio-layer interferometry (BLI) are commonly used for critical reagent characterization. Bioanalytical laboratories have been leveraging the advantage of real time label-free molecule interaction measurement for effective reagent screening, characterization and epitope binning for many years. Frequently, tool antibodies such as anti-idiotypes are selected from several candidates by applying SPR or BLI assessment before setting up the bioanalytical method on the final immunoassay platform to safe costs and time. In addition to classical kinetics and affinity determination, SPR and BLI were recommended for assessing different labeling strategies in order to identify most suitable conjugation conditions for biotherapeutic molecules intended for use as ADA capture reagents in bridging ELISAs.

In the context of total PK assay development, BLI was recommended for screening of sample pre-treatment conditions facilitating total drug detection in presence of high abundant target proteins. BLI not only enables testing and optimizing conditions for efficient dissociation of drug-target complexes but also for simultaneously selecting conditions not compromising the (re-)binding ability of the drug molecule which is a critical prerequisite for successful PK assay development relying on anti-idiotic capture reagents.

Recommendations for selecting SPR or biolayer interferometry (BLI) when characterizing LBA reagents were discussed. SPR has been used with high consistency and is considered as the gold-standard for CMC due to its convenience. However, the examples described above showcase increasing use and application of BLI in critical ligand binding assay reagent characterization. SPR like BLI can be used in normal PK essays to choose a very high affinity antibody. However, SPR and BLI were not recommended for target engagement free assay development. Instead, soluble K_d determination is preferred to understand binding relationships in vivo for free assay.

RECOMMENDATIONS

Below is a summary of the recommendations made during the 16^th WRIB:

Novel Technologies & Automation in LBA

• FFP validation principles apply to new LBA modalities such as ultrasensitive immunoassays. If an assay answers a specific question outside of the validated assay (i.e., exploratory), then only a minimum amount of characterization is needed to determine that the assay is reproducible and scientifically sound.

  ○

  FFP assay may be used for supporting information, in tandem with a validated assay used for endpoints.

• For tissue measurements, there was a consensus that normalization is required for quantitative tissue measurement but many normalization methods exist needing further discussion.

• Regarding documenting DOE method development especially with automation for inclusion in health authority submissions, it was recommended to keep a documented internal history on development details but not required to include it in regulatory submissions.

• Automation should be validated as the method would be used but with additional focus on IT validation.

  ○

  Careful consideration of data integrity and computer system validation with dedicated staff (e.g., security, change control, scripts, audit trails, equipment and batch logs) is recommended.

• Due to high reproducibility with automation, singlicate analysis is possible if statistical analysis determines it is acceptable.

• Formal calibration procedure recommended for each liquid handler, outside of the individual methods, to control variability in multistep LBA automated methods.

• Technologies for automation of immunogenicity assays were discussed including the possibility to use resin tips to replace magnetic beads, though more experience is needed.

Novel Modalities, Novel Method Development/Validation Challenges

• For enzyme assay development, which are used to measure protein activity, use LBA BMV as a general principal with a FFP approach for certain steps.

  	○	There is a need to be aware of potential instability for some analytes/methods.
  	○	Reference standards for ERT assays in cell and gene therapy are challenging and need more experience.

• LBA for CAS9 There was agreement there is no requirement to assay cas9; use preemptive approach.

  ○

  A robust effort to demonstrate sensitivity of cas9 methods is sufficient.

Rare Matrices

• While examples exist of PK measurements in non-standard matrices for exposure response relationships from animal studies vs. human, the biggest unknown is the PD portion. Turnover of target is unpredictable when moving from animal to human.

• There was a consensus that systemic ADA analysis is sufficient for ADA evaluation. Tissue assays are not recommended.

• Approach to monitor ocular PK by surrogate plasma samples is acceptable, animal correlation typically not sufficient.

• Ultrasensitive analysis, multiplexing, and microfluidic technologies may reduce ocular sample consumption and Gyrolab was recommended for ultrasensitive assays for ocular LBA.

Problem Solving for Complex NAb Assays

• Assay platforms for weak drug/target interaction were compared.

  	○	If the drug trough concentration is high (especially in oncology indications), non-cell based CLB assay and/or assay platform with minimal wash is recommended.
  	○	Signal amplification of binding is recommended, and drug depletion is required to improve drug tolerance and reduce matrix interference.

• Domain mapping for mutli-specific biotherapeutics for NAb assessment is not required by regulatory agency but it is recommended to determine NAb specificity for multidomain biotherapeutics.

• A higher sample dilution (e.g., factor of 20) is recommended to increase drug tolerance but may decrease assay readouts.

Critical Reagents Deep Characterization

• Considerations were discussed to characterize critical reagents.

  	○	Lot-to-lot validation is required.
  	○	Characterize stability over assay lifetime.
  	○	Characterize binding affinity after planned manipulation (e.g., labelling).

• It was recommended for labeling ratio of ADA assay critical reagents to go as low as possible without compromising assay sensitivity and characterize the reagent after labelling.

• To characterize LBA reagents, both BLI and SPR have been used. SPR has been used with high consistency and is considered as the gold-standard for CMC due to its convenience.

  ○

  Soluble Kd determination is recommended to understand binding relationships in vivo.