B-Cell Populations in Focus: A New Flow Cytometry Assay for Increased Sensitivity in Autoimmune Research

September 19, 2025

Alex Guo, PhD

B cells are central to both protective immunity and autoimmune pathology. With the recent shift of cell therapies from oncology indications to autoimmune diseases, interest has been growing towards this immune cell population.1,2

Flow cytometry remains the gold standard for monitoring B cells in both research and clinical settings. However, lack of convention for classification as well as reliable and stable markers, especially following thawing of samples, can make it difficult to capture rare B-cell populations relevant to autoimmune drug development.

For translational research teams, this creates an urgent need for tools that deliver the sensitivity and consistency required to fully understand B-cell dynamics and drive the development of new B-cell therapies.

The Challenge of Defining B-cell Subsets

B cells are far from uniform. Transitional, naïve, memory, double-negative, and plasma cell subsets each play distinct roles in health and disease, but their phenotypic profiles often overlap. Inconsistent marker usage and variability in gating strategies have made it difficult to classify B-cell subsets consistently, which can complicate the comparison of results across studies.3

For drug developers, the lack of standardization creates real-world hurdles. Autoimmune therapies that aim to induce a B-cell reset (eliminating autoreactive populations and allowing the immune system to repopulate with naïve B cells) depend on precise monitoring of which subsets return after the B-cell aplasia phase. Without consistent, high-resolution phenotyping, it is difficult to determine whether a therapy is resetting B-cell populations in a way that supports durable disease control.

Recent efforts to harmonize approaches are beginning to address these issues, with publications recommending standardized marker sets to improve reproducibility and resolution of B-cell subsets.³ Markers such as CD21, once regarded mainly for their functional role, are now recognized as important phenotypic indicators that help distinguish distinct populations. Incorporating markers like these into flow cytometry panels is essential to provide the clarity and consistency needed for research on B-cell reset in autoimmune diseases.

A Refined Flow Cytometry Assay for B-Cell Subsets

To address these challenges, CellCarta has advanced its flow cytometry capabilities with a refined B-cell assay that improves the sensitivity and consistency of B-cell subset profiling.

1- Updated gating strategy

We refined our panel strategy by incorporating markers such as CD21 as phenotypic indicators alongside other established markers. This enables further stratification of B-cell subtypes, providing better insight into both activated and developmentally distinct populations that are increasingly linked to autoimmune disease.

Section image

Table 1: B-cell subsets identifiable with CellCarta’s refined flow cytometry panel. Rows show major populations, while columns list the markers used to classify them. CD21 provides added resolution by distinguishing activated and developmentally distinct subsets relevant to autoimmune disease.

2- Improved bulk lysis method

We’ve developed a refined bulk lysis method using the B-cell panel. In comparison to the direct whole blood (WB) analysis (100ul of blood), the improved bulk lysis method resulted in a 10-fold increase in the cell input compared to the traditional analysis using WB for flow cytometry assay (Figure 1). As more cells are acquired, rare populations can now be assessed with better precision. The whole method was evaluated at both 4°C and room temperature (RT), providing flexibility for the sample management and transportation.

Figure 1: Event counts of total B cells and subsets acquired from healthy donors using direct whole blood analysis method (blue) and refined bulk lysis method (orange) WB – Whole Blood; NWM – Non-switched memory; SWM – Switched memory, DN – Double negative

Global Scalability With the Lyric Platform

To offer global site-to-site consistency, we switched our B-cell assay from the Fortessa to the Lyric platform, leveraging the built-in capabilities of this platform to achieve high inter-instrument/inter-site standardization. Unified workflows and directly comparable data make it easier to scale studies internationally, reduce variability, and build confidence in results across multicenter trials.

Supporting the Next Generation of B-Cell Therapies

With refinements to its gating strategy, bulk lysis method, and global platform standardization, CellCarta’s B-cell flow cytometry assay provides the resolution, sensitivity, and reproducibility needed to study B-cell dynamics in detail. In the context of the development of B-cell reset therapies, these advancements enable the precise monitoring and consistency needed to better define which B-cell populations are depleted, which repopulate, and how these shifts influence autoimmune disease outcomes.

In addition to our B-cell panel, CellCarta can support researchers with both off-the-shelf panels for rapid deployment and custom panel development tailored to specific scientific questions. With this flexibility, pharma teams can choose the right approach for their needs, supporting clearer decision-making in the development of new B–cell–targeted therapies.

Meet our expert:

author photo

Alex Guo, PhD, is a Principal Scientist at CellCarta, specializing in immune monitoring and proteomics. With a doctorate in Immunology and Molecular Oncology, he has extensive expertise in developing and validating novel assays to address complex clinical needs. Alex has led immune monitoring analyses across multiple clinical programs, translating high-dimensional data into actionable insights for clients. He combines deep scientific expertise with practical project execution to advance translational and clinical research.

References

  1. Lee, D. S., Rojas, O. L., & Gommerman, J. L. (2021). Nature reviews Drug discovery, 20(3), 179-199.
  2. Harrison C. Nature Biotechnology, vol. 42, 2024, pp. 995–997.
  3. Sanz, I., Wei, C., Jenks, S. A. et al (2019). Frontiers in immunology, 10, 2458.

B-Cell Populations in Focus: A New Flow Cytometry Assay for Increased Sensitivity in Autoimmune Research

September 19, 2025

Alex Guo, PhD

B cells are central to both protective immunity and autoimmune pathology. With the recent shift of cell therapies from oncology indications to autoimmune diseases, interest has been growing towards this immune cell population.1,2

Flow cytometry remains the gold standard for monitoring B cells in both research and clinical settings. However, lack of convention for classification as well as reliable and stable markers, especially following thawing of samples, can make it difficult to capture rare B-cell populations relevant to autoimmune drug development.

For translational research teams, this creates an urgent need for tools that deliver the sensitivity and consistency required to fully understand B-cell dynamics and drive the development of new B-cell therapies.

The Challenge of Defining B-cell Subsets

B cells are far from uniform. Transitional, naïve, memory, double-negative, and plasma cell subsets each play distinct roles in health and disease, but their phenotypic profiles often overlap. Inconsistent marker usage and variability in gating strategies have made it difficult to classify B-cell subsets consistently, which can complicate the comparison of results across studies.3

For drug developers, the lack of standardization creates real-world hurdles. Autoimmune therapies that aim to induce a B-cell reset (eliminating autoreactive populations and allowing the immune system to repopulate with naïve B cells) depend on precise monitoring of which subsets return after the B-cell aplasia phase. Without consistent, high-resolution phenotyping, it is difficult to determine whether a therapy is resetting B-cell populations in a way that supports durable disease control.

Recent efforts to harmonize approaches are beginning to address these issues, with publications recommending standardized marker sets to improve reproducibility and resolution of B-cell subsets.³ Markers such as CD21, once regarded mainly for their functional role, are now recognized as important phenotypic indicators that help distinguish distinct populations. Incorporating markers like these into flow cytometry panels is essential to provide the clarity and consistency needed for research on B-cell reset in autoimmune diseases.

A Refined Flow Cytometry Assay for B-Cell Subsets

To address these challenges, CellCarta has advanced its flow cytometry capabilities with a refined B-cell assay that improves the sensitivity and consistency of B-cell subset profiling.

1- Updated gating strategy

We refined our panel strategy by incorporating markers such as CD21 as phenotypic indicators alongside other established markers. This enables further stratification of B-cell subtypes, providing better insight into both activated and developmentally distinct populations that are increasingly linked to autoimmune disease.

Section image

Table 1: B-cell subsets identifiable with CellCarta’s refined flow cytometry panel. Rows show major populations, while columns list the markers used to classify them. CD21 provides added resolution by distinguishing activated and developmentally distinct subsets relevant to autoimmune disease.

2- Improved bulk lysis method

We’ve developed a refined bulk lysis method using the B-cell panel. In comparison to the direct whole blood (WB) analysis (100ul of blood), the improved bulk lysis method resulted in a 10-fold increase in the cell input compared to the traditional analysis using WB for flow cytometry assay (Figure 1). As more cells are acquired, rare populations can now be assessed with better precision. The whole method was evaluated at both 4°C and room temperature (RT), providing flexibility for the sample management and transportation.

Figure 1: Event counts of total B cells and subsets acquired from healthy donors using direct whole blood analysis method (blue) and refined bulk lysis method (orange) WB – Whole Blood; NWM – Non-switched memory; SWM – Switched memory, DN – Double negative

Global Scalability With the Lyric Platform

To offer global site-to-site consistency, we switched our B-cell assay from the Fortessa to the Lyric platform, leveraging the built-in capabilities of this platform to achieve high inter-instrument/inter-site standardization. Unified workflows and directly comparable data make it easier to scale studies internationally, reduce variability, and build confidence in results across multicenter trials.

Supporting the Next Generation of B-Cell Therapies

With refinements to its gating strategy, bulk lysis method, and global platform standardization, CellCarta’s B-cell flow cytometry assay provides the resolution, sensitivity, and reproducibility needed to study B-cell dynamics in detail. In the context of the development of B-cell reset therapies, these advancements enable the precise monitoring and consistency needed to better define which B-cell populations are depleted, which repopulate, and how these shifts influence autoimmune disease outcomes.

In addition to our B-cell panel, CellCarta can support researchers with both off-the-shelf panels for rapid deployment and custom panel development tailored to specific scientific questions. With this flexibility, pharma teams can choose the right approach for their needs, supporting clearer decision-making in the development of new B–cell–targeted therapies.

Meet our expert:

author photo

Alex Guo, PhD, is a Principal Scientist at CellCarta, specializing in immune monitoring and proteomics. With a doctorate in Immunology and Molecular Oncology, he has extensive expertise in developing and validating novel assays to address complex clinical needs. Alex has led immune monitoring analyses across multiple clinical programs, translating high-dimensional data into actionable insights for clients. He combines deep scientific expertise with practical project execution to advance translational and clinical research.

References

  1. Lee, D. S., Rojas, O. L., & Gommerman, J. L. (2021). Nature reviews Drug discovery, 20(3), 179-199.
  2. Harrison C. Nature Biotechnology, vol. 42, 2024, pp. 995–997.
  3. Sanz, I., Wei, C., Jenks, S. A. et al (2019). Frontiers in immunology, 10, 2458.

Qualification of Gene and Protein Signatures from CITE-seq Data for Deep Immunophenotyping in Human Clinical Trials

April 7, 2025

Matt Clutter

Qualification of Gene and Protein Signatures from CITE-seq Data for Deep Immunophenotyping in Human Clinical Trials

Qualification of Gene and Protein Signatures from CITE-seq Data for Deep Immunophenotyping in Human Clinical Trials

April 7, 2025

Matt Clutter

Qualification of Gene and Protein Signatures from CITE-seq Data for Deep Immunophenotyping in Human Clinical Trials

Biomarker Strategies for Cell Therapy in Autoimmune Diseases

October 16, 2024

Biomarker Strategies for Cell Therapy in Autoimmune Diseases Measuring the B Cell Reset

Biomarker Strategies for Cell Therapy in Autoimmune Diseases

October 16, 2024

Biomarker Strategies for Cell Therapy in Autoimmune Diseases Measuring the B Cell Reset

Drug Target Engagement with Flow Cytometry Receptor Occupancy Assays

September 17, 2024

Damien Montamat-Sicotte, Scientific Business Director

Receptor Occupancy Assays by Flow Cytometry

A crucial step in the drug development process involves optimizing drug-target engagement for your biotherapeutic and gaining valuable pharmacodynamic biomarker data. High-quality receptor occupancy assays (RO assays) are vital tools in this process.

Reliable and accurate results in the design, development, and implementation of receptor occupancy assays can seem to be a tasking prospect, as they are prone to numerous technical and logistical challenges, requiring-

  • expert assay design
  • optimal matrix selection
  • data normalization/reporting
  • and rigorous quality control1, 2

Such challenges can escalate further in difficult development scenarios, such as when the target antigen is expressed at low levels, where there is receptor modulation, or when the therapeutic molecules are bi-specific and bind multiple targets2.

Types and Methodologies

RO assays can be classified into two main types: competitive assays and saturation assays. Competitive assays involve the use of competitive and non-competitive antibodies to the drug, to note that the competitive antibody can also be substituted by an anti-drug antibody. Saturation assays use a competitive antibody and the drug product itself detected by an antibody as a reference point.

Type of Assay Description
Competing vs. non-competing antibodies Competing and non-competing antibodies are added to a sample. Competing antibodies bind to the drug's target site, indicating unbound targets. Non-competing antibodies bind elsewhere on the target, showing total available targets. Alternatively, the competing antibody can be substituted for a anti-drug antibody
Saturation assay Half of the sample is saturated with the drug, mimicking 100% RO, showing the total number of available target sites. The other half remains unsaturated, reflecting drug binding in the patient.
A secondary antibody detects the drug, this can be done using an anti-drug or an anti-Ig antibody, and the ratio of unsaturated to saturated samples reveals the drug's receptor occupancy (RO) level.

Custom RO Strategies for Enhanced Drug Development

CellCarta’s flow-cytometry-based receptor occupancy (RO) assays are designed to overcome these challenges and accelerate your efforts, providing you with the critical information needed to demonstrate target engagement, and gain insight into what degree and how long your biotherapeutic binds its target.

Our RO assays can also be used to complement your pharmacokinetic profiling to provide valuable information on dose selection and frequency of drug infusion. Additionally, RO assays can be validated to support secondary endpoints.

One of our RO strategies starts with the identification of both a competitive and a non-competitive antibody. The competitive antibody will only bind to its target if it is not currently bound by the drug, allowing identification of free receptors, while the non-competitive antibody identifies the total amount of target receptors.

We monitor receptor occupancy only in cell populations of interest by combining target-specific reagents into a flow cytometry panel of phenotypic markers. Competitive and non-competitive antibodies can even be used in the same panel.

When competitive or non-competitive antibodies cannot be identified, or when antibodies to the receptor are not available, we use a saturating vs. non-saturating approach to determine the receptor occupancy or RO.

The strategy involves saturation of half of the sample, mimicking a 100% RO. The other half is not saturated, allowing us to perform a ratio of drug-binding between the two halves to accurately determine the receptor occupancy of the sample.

Pharmacokinetic and Pharmacodynamic Insights

RO assays are integrated with pharmacokinetic (PK) and pharmacodynamic (PD) models to inform dosing strategies and optimize drug efficacy. These assays help determine the relationship between drug concentration and its biological effect, providing critical data for dose selection and frequency of administration. This integration is particularly valuable in clinical trials, where RO assays can serve as pharmacodynamic biomarker measurements to assess drug efficacy.

Choosing the ideal sample matrix for accurate RO Assays

The choice of sample matrix can have a profound effect on the quality of a RO assay. For example, PBMC processing can negatively impact the binding of the drug, resulting in an underestimation of the RO. We also typically test different vacutainers to maximize the stability and precision of the RO measurement.

Our experienced scientists develop and validate different RO strategies to address a variety of drug types and reagent availabilities, drawing on our extensive experience in deploying RO assay strategies in clinical trials.

Challenges and Considerations

Despite their importance, RO assays present several challenges. The development and optimization of these assays are complex and demand high-quality reagents and rigorous controls. Additionally, interpreting the data can be complicated by factors such as receptor internalization and degradation, necessitating a thorough understanding of the underlying biological processes.

Emerging Trends and Technological Breakthroughs in Receptor Occupancy Assays

Advanced technologies and methodologies are continually enhancing the accuracy and reliability of RO assays. Complex RO assays can provide additional insights into receptor internalization and shedding, contributing to a more comprehensive understanding of drug-target interactions. These advancements hold the potential to revolutionize drug development by providing more precise and detailed pharmacodynamic data.

CellCarta exemplifies these advancements with state-of-the-art flow cytometry and custom panels that ensure precise measurements, even in complex scenarios. This accuracy is crucial for informing dose selection and optimizing therapeutic efficacy. Emerging technologies like single-cell RNA sequencing and high-dimensional flow cytometry promise even deeper insights into drug-receptor interactions.

Step Up to the Next Level in Your RO Assay Development and Validation

Enhance the robustness of your RO assay development with our custom-designed panels and expert guidance, ensuring accurate and reliable data that drives informed decision-making in your drug development process.

Expert Insights: Watch the following video from our expert to mastering receptor occupancy assays with Flow Cytometry

 

 

About the author:

author photo

Damien Montamat-Sicotte is a Scientific Business Director at CellCarta, specializing in the flow cytometry platform. With a PhD in immunology and post-doctoral expertise from various institutions, Damien has profuse experience in managing the processing and analysis of clinical samples by flow cytometry in an immune monitoring context.

References

  1. Liang M, Schwickart M, Schneider AK, et al. Receptor occupancy assessment by flow cytometry as a pharmacodynamic biomarker in biopharmaceutical development. Cytometry B Clin Cytom 2016;90:117-27.
  2. Hilt E, Sun YS, McCloskey TW, et al. Best practices for optimization and validation of flow cytometry-based receptor occupancy assays. Cytometry B Clin Cytom 2021;100:63-71.

Drug Target Engagement with Flow Cytometry Receptor Occupancy Assays

September 17, 2024

Damien Montamat-Sicotte, Scientific Business Director

Receptor Occupancy Assays by Flow Cytometry

A crucial step in the drug development process involves optimizing drug-target engagement for your biotherapeutic and gaining valuable pharmacodynamic biomarker data. High-quality receptor occupancy assays (RO assays) are vital tools in this process.

Reliable and accurate results in the design, development, and implementation of receptor occupancy assays can seem to be a tasking prospect, as they are prone to numerous technical and logistical challenges, requiring-

  • expert assay design
  • optimal matrix selection
  • data normalization/reporting
  • and rigorous quality control1, 2

Such challenges can escalate further in difficult development scenarios, such as when the target antigen is expressed at low levels, where there is receptor modulation, or when the therapeutic molecules are bi-specific and bind multiple targets2.

Types and Methodologies

RO assays can be classified into two main types: competitive assays and saturation assays. Competitive assays involve the use of competitive and non-competitive antibodies to the drug, to note that the competitive antibody can also be substituted by an anti-drug antibody. Saturation assays use a competitive antibody and the drug product itself detected by an antibody as a reference point.

Type of Assay Description
Competing vs. non-competing antibodies Competing and non-competing antibodies are added to a sample. Competing antibodies bind to the drug's target site, indicating unbound targets. Non-competing antibodies bind elsewhere on the target, showing total available targets. Alternatively, the competing antibody can be substituted for a anti-drug antibody
Saturation assay Half of the sample is saturated with the drug, mimicking 100% RO, showing the total number of available target sites. The other half remains unsaturated, reflecting drug binding in the patient.
A secondary antibody detects the drug, this can be done using an anti-drug or an anti-Ig antibody, and the ratio of unsaturated to saturated samples reveals the drug's receptor occupancy (RO) level.

Custom RO Strategies for Enhanced Drug Development

CellCarta’s flow-cytometry-based receptor occupancy (RO) assays are designed to overcome these challenges and accelerate your efforts, providing you with the critical information needed to demonstrate target engagement, and gain insight into what degree and how long your biotherapeutic binds its target.

Our RO assays can also be used to complement your pharmacokinetic profiling to provide valuable information on dose selection and frequency of drug infusion. Additionally, RO assays can be validated to support secondary endpoints.

One of our RO strategies starts with the identification of both a competitive and a non-competitive antibody. The competitive antibody will only bind to its target if it is not currently bound by the drug, allowing identification of free receptors, while the non-competitive antibody identifies the total amount of target receptors.

We monitor receptor occupancy only in cell populations of interest by combining target-specific reagents into a flow cytometry panel of phenotypic markers. Competitive and non-competitive antibodies can even be used in the same panel.

When competitive or non-competitive antibodies cannot be identified, or when antibodies to the receptor are not available, we use a saturating vs. non-saturating approach to determine the receptor occupancy or RO.

The strategy involves saturation of half of the sample, mimicking a 100% RO. The other half is not saturated, allowing us to perform a ratio of drug-binding between the two halves to accurately determine the receptor occupancy of the sample.

Pharmacokinetic and Pharmacodynamic Insights

RO assays are integrated with pharmacokinetic (PK) and pharmacodynamic (PD) models to inform dosing strategies and optimize drug efficacy. These assays help determine the relationship between drug concentration and its biological effect, providing critical data for dose selection and frequency of administration. This integration is particularly valuable in clinical trials, where RO assays can serve as pharmacodynamic biomarker measurements to assess drug efficacy.

Choosing the ideal sample matrix for accurate RO Assays

The choice of sample matrix can have a profound effect on the quality of a RO assay. For example, PBMC processing can negatively impact the binding of the drug, resulting in an underestimation of the RO. We also typically test different vacutainers to maximize the stability and precision of the RO measurement.

Our experienced scientists develop and validate different RO strategies to address a variety of drug types and reagent availabilities, drawing on our extensive experience in deploying RO assay strategies in clinical trials.

Challenges and Considerations

Despite their importance, RO assays present several challenges. The development and optimization of these assays are complex and demand high-quality reagents and rigorous controls. Additionally, interpreting the data can be complicated by factors such as receptor internalization and degradation, necessitating a thorough understanding of the underlying biological processes.

Emerging Trends and Technological Breakthroughs in Receptor Occupancy Assays

Advanced technologies and methodologies are continually enhancing the accuracy and reliability of RO assays. Complex RO assays can provide additional insights into receptor internalization and shedding, contributing to a more comprehensive understanding of drug-target interactions. These advancements hold the potential to revolutionize drug development by providing more precise and detailed pharmacodynamic data.

CellCarta exemplifies these advancements with state-of-the-art flow cytometry and custom panels that ensure precise measurements, even in complex scenarios. This accuracy is crucial for informing dose selection and optimizing therapeutic efficacy. Emerging technologies like single-cell RNA sequencing and high-dimensional flow cytometry promise even deeper insights into drug-receptor interactions.

Step Up to the Next Level in Your RO Assay Development and Validation

Enhance the robustness of your RO assay development with our custom-designed panels and expert guidance, ensuring accurate and reliable data that drives informed decision-making in your drug development process.

Expert Insights: Watch the following video from our expert to mastering receptor occupancy assays with Flow Cytometry

 

 

About the author:

author photo

Damien Montamat-Sicotte is a Scientific Business Director at CellCarta, specializing in the flow cytometry platform. With a PhD in immunology and post-doctoral expertise from various institutions, Damien has profuse experience in managing the processing and analysis of clinical samples by flow cytometry in an immune monitoring context.

References

  1. Liang M, Schwickart M, Schneider AK, et al. Receptor occupancy assessment by flow cytometry as a pharmacodynamic biomarker in biopharmaceutical development. Cytometry B Clin Cytom 2016;90:117-27.
  2. Hilt E, Sun YS, McCloskey TW, et al. Best practices for optimization and validation of flow cytometry-based receptor occupancy assays. Cytometry B Clin Cytom 2021;100:63-71.

How cell therapy developers are future-proofing clinical monitoring of B-cell aplasia

July 11, 2024

Liesbet Vervoort, PhD

As cell therapies become more complex, the pressures facing clinical developers are rising. A greater number and diversity of cell therapy products are progressing to clinical stages, all requiring comprehensive, accurate, and yet rapid characterization to ensure that the journey from bench to bedside is as fast, safe, and effective as possible.

To accommodate this ever-growing number of new cell therapy concepts, clinical developers need robust, adaptive, affordable testing strategies for extensive yet efficient characterization. To realize these, developers are turning to complementary methods and modularized testing, and working to identify the most high-value readouts. Taking such an approach allows developers to assess aspects such as B-cell aplasia, even as the parameters monitored in B-cell populations expand as cell therapies address new indications.

Our new Cell Therapy Trend Report reveals how clinical testing is adapting to the rapidly changing cell therapy landscape. Download the report now to learn more and explore several broad trends to be aware of within the space, spanning the testing areas of HLA typing, cytokine profiling, cell enumeration and vector copy number determination, single-cell analytics, and B-cell aplasia.

Bringing complementary testing to B-cell aplasia

We anticipate that B-cell monitoring will soon become a standard part of clinical testing programs for new cell therapies and indications. Because of this, identifying the most efficient, effective, and appropriate monitoring approaches is of undeniable value.

Complementarity in particular offers huge promise here. By leveraging the synergies and capabilities of different established testing methods, developers can evaluate B-cell therapies more comprehensively to paint a detailed picture of how cell therapies act against B-cells. Such an approach could help to identify differences in body tissues, discriminate between on- and off-tumor activity, and shed light on off-tumor effects (such as the depletion of healthy B cells).

Additionally, as cell therapies increasingly address new indications and therapeutic areas — including autoimmune diseases and solid tumors — complementary assays can adapt to address a wider array of parameters, creating exciting new opportunities for in-depth analysis. Developers will also be able to mine the knowledge gleaned from previous testing to inform the design of new adaptive assays, enhance their clinical testing, and improve specificity.

B-cell aplasia: Understanding its role in cell therapy clinical testing

As well as improving our understanding of how cell therapies act against B cells, the fast, unambiguous enumeration of B cell populations and their depletion can…

  • Inform study inclusion
  • Help reveal the mechanisms behind autoreactivity
  • Support the development of new therapies
  • Potentially serve complementary purposes in the assessment of therapeutic efficacy and disease progression

Complementarity and other approaches to optimize and future-proof the clinical characterization of novel cell therapies, are discussed in our Cell Therapy Trend Report. Download the report now, or contact our team to speak to an expert about your cell therapy clinical testing needs.

 

About the author

author photo

Liesbet Vervoort is a Group Lead Program Management at CellCarta. With a PhD in immune-oncology and expertise as an operational lab lead and hematopathology program lead, Liesbet has profuse experience in aligning and translating customers’ needs to clinical trial implementation.

How cell therapy developers are future-proofing clinical monitoring of B-cell aplasia

July 11, 2024

Liesbet Vervoort, PhD

As cell therapies become more complex, the pressures facing clinical developers are rising. A greater number and diversity of cell therapy products are progressing to clinical stages, all requiring comprehensive, accurate, and yet rapid characterization to ensure that the journey from bench to bedside is as fast, safe, and effective as possible.

To accommodate this ever-growing number of new cell therapy concepts, clinical developers need robust, adaptive, affordable testing strategies for extensive yet efficient characterization. To realize these, developers are turning to complementary methods and modularized testing, and working to identify the most high-value readouts. Taking such an approach allows developers to assess aspects such as B-cell aplasia, even as the parameters monitored in B-cell populations expand as cell therapies address new indications.

Our new Cell Therapy Trend Report reveals how clinical testing is adapting to the rapidly changing cell therapy landscape. Download the report now to learn more and explore several broad trends to be aware of within the space, spanning the testing areas of HLA typing, cytokine profiling, cell enumeration and vector copy number determination, single-cell analytics, and B-cell aplasia.

Bringing complementary testing to B-cell aplasia

We anticipate that B-cell monitoring will soon become a standard part of clinical testing programs for new cell therapies and indications. Because of this, identifying the most efficient, effective, and appropriate monitoring approaches is of undeniable value.

Complementarity in particular offers huge promise here. By leveraging the synergies and capabilities of different established testing methods, developers can evaluate B-cell therapies more comprehensively to paint a detailed picture of how cell therapies act against B-cells. Such an approach could help to identify differences in body tissues, discriminate between on- and off-tumor activity, and shed light on off-tumor effects (such as the depletion of healthy B cells).

Additionally, as cell therapies increasingly address new indications and therapeutic areas — including autoimmune diseases and solid tumors — complementary assays can adapt to address a wider array of parameters, creating exciting new opportunities for in-depth analysis. Developers will also be able to mine the knowledge gleaned from previous testing to inform the design of new adaptive assays, enhance their clinical testing, and improve specificity.

B-cell aplasia: Understanding its role in cell therapy clinical testing

As well as improving our understanding of how cell therapies act against B cells, the fast, unambiguous enumeration of B cell populations and their depletion can…

  • Inform study inclusion
  • Help reveal the mechanisms behind autoreactivity
  • Support the development of new therapies
  • Potentially serve complementary purposes in the assessment of therapeutic efficacy and disease progression

Complementarity and other approaches to optimize and future-proof the clinical characterization of novel cell therapies, are discussed in our Cell Therapy Trend Report. Download the report now, or contact our team to speak to an expert about your cell therapy clinical testing needs.

 

About the author

author photo

Liesbet Vervoort is a Group Lead Program Management at CellCarta. With a PhD in immune-oncology and expertise as an operational lab lead and hematopathology program lead, Liesbet has profuse experience in aligning and translating customers’ needs to clinical trial implementation.