BOI2 Antibody

What is BDCA2 and why is it a valuable target for antibody development?

BDCA2 (blood dendritic cell antigen 2) is a receptor exclusively expressed on the surface of plasmacytoid dendritic cells (pDCs). This receptor has emerged as a crucial target for therapeutic antibody development due to its role in regulating type I interferon (IFN-I) production. When BDCA2 is engaged by antibodies, it inhibits the production of IFN-I in human pDCs, which are major producers of these cytokines . This inhibitory mechanism is particularly important because excessive IFN-I production by pDCs is implicated in the pathogenesis of several autoimmune diseases, most notably Systemic Lupus Erythematosus (SLE).

The specificity of BDCA2 expression to pDCs makes it an ideal target for selective immunomodulation. Unlike approaches that broadly suppress immune function, targeting BDCA2 allows for precise modulation of a key cellular source of pathogenic IFN-I without directly affecting other immune cell populations. In SLE, immune complexes bind to the CD32a (FcγRIIa) receptor on pDCs and stimulate IFN-I secretion, contributing to disease pathology . Anti-BDCA2 antibodies can interrupt this pathogenic process, offering a targeted therapeutic approach for autoimmune conditions.

How do anti-BDCA2 antibodies exert their immunomodulatory effects?

Anti-BDCA2 antibodies operate through a sophisticated dual mechanism to inhibit pDC responses:

• BDCA2 engagement and internalization: When antibodies like 24F4A bind to BDCA2 on pDCs, they induce receptor internalization, which correlates directly with inhibition of TLR9-induced IFN-α production . Research has demonstrated a strong correlation between the EC50 of 24F4A-mediated BDCA2 internalization and the IC50 of IFN-α inhibition, with an R² value of 0.68 across multiple donors . This indicates that receptor internalization is likely a key mechanism of action.

• BCR-like signaling cascade: Cross-linking BDCA2 with anti-BDCA2 monoclonal antibodies promotes a B-cell receptor (BCR)-like signaling cascade that results in the inhibition of TLR7 or TLR9-mediated IFN-I production by pDCs . This signaling pathway interrupts the normal response of pDCs to TLR stimulation.

For antibodies like 24F4A, the Fc region provides an additional mechanism of action. This region is critical for potent inhibition of immune complex-induced IFN-I production through internalization of CD32a (FcγRIIa) . This represents a particularly relevant mechanism in the context of SLE, where immune complexes stimulate pDCs through CD32a engagement.

What distinguishes functional inhibition by anti-BDCA2 antibodies from cell-depleting approaches?

A key advantage of anti-BDCA2 antibodies is their ability to functionally inhibit pDCs without causing significant cell depletion. Studies with 24F4A in cynomolgus monkeys demonstrated that this antibody induced BDCA2 internalization and inhibited TLR-induced IFN-I production without depleting pDCs . This characteristic offers therapeutic advantages over cell-depleting approaches.

The functional inhibition approach provides several benefits:

• Preservation of protective immunity: Complete pDC depletion has been shown to impact anti-viral immunity, whereas functional inhibition preserves some pDC capabilities . This is particularly important for long-term therapeutic applications where maintaining defense against viral infections is essential.

• Efficacy in autoimmune conditions: Research has shown that even partial functional inhibition of pDCs can dramatically improve lupus-like disease in mouse models of SLE, suggesting that complete depletion is not necessary for therapeutic benefit .

• Reversibility: Functional inhibition through BDCA2 ligation is potentially reversible as new receptors are synthesized, allowing for more flexible treatment regimens compared to cell-depleting approaches.

• Safety profile: The preservation of pDCs, albeit in a functionally inhibited state, may contribute to a better safety profile for anti-BDCA2 antibodies in autoimmune disease treatment .

How do variations in antibody structure affect BDCA2 internalization efficiency and functional outcomes?

Not all anti-BDCA2 antibodies demonstrate equal efficacy in inducing receptor internalization and inhibiting IFN-I production, despite similar binding affinities. This phenomenon has been investigated through comparative studies of different anti-BDCA2 monoclonal antibodies. For example, when comparing 24F4A with another anti-BDCA2 mAb (murine 6G6), researchers observed that although 6G6 bound BDCA2 with high affinity and achieved full receptor occupancy, it only led to modest BDCA2 internalization and consequently modest inhibition of TLR9-induced IFN-α production .

This variance in efficacy despite similar receptor binding highlights several critical factors that influence functional outcomes:

• Epitope specificity: The precise epitope recognized by the antibody on BDCA2 may influence its ability to trigger receptor internalization and downstream signaling.

• Antibody format: The antibody isotype, Fab architecture, and hinge flexibility can affect crosslinking efficiency and subsequent receptor clustering required for internalization.

• Fc region functionality: The Fc region plays a crucial role in enhancing inhibition of immune complex-induced IFN-I production through interactions with CD32a .

The table below summarizes comparative characteristics of different anti-BDCA2 antibodies based on research findings:

These differences underscore the importance of comprehensive antibody characterization beyond simple binding affinity when developing therapeutic anti-BDCA2 antibodies.

How can pharmacokinetic/pharmacodynamic (PK/PD) modeling enhance clinical translation of anti-BDCA2 antibodies?

PK/PD modeling has proven instrumental in translating anti-BDCA2 antibody research from preclinical studies to clinical applications. The development of BIIB059, a humanized anti-BDCA2 mAb for the treatment of SLE and Cutaneous Lupus Erythematosus, exemplifies this approach .

Researchers utilized a sophisticated modeling strategy that involved:

• Comprehensive non-human primate (NHP) data collection: PK data from 17 cynomolgus monkeys receiving BIIB059 through various routes (intravenous and subcutaneous) and dosing schedules, along with PD data (BDCA2 receptor density on pDCs) from 6 monkeys, provided the foundation for model development .

• Two-compartment PK model with indirect response PD: This modeling approach accurately captured the relationship between drug concentration and receptor modulation .

• Cross-species scaling methodology: Combining traditional allometric PK scaling with sensitivity-analysis-driven scaling of PD parameters allowed for translation from NHP to human predictions .

• Prospective validation: When clinical data from the BIIB059 Phase I study became available, they confirmed the accuracy of the model predictions, validating this approach for mAb development .

This modeling strategy offers several advantages for anti-BDCA2 antibody development:

• Supports rational selection of safe first-in-human doses

• Predicts receptor occupancy and pharmacodynamic effects at different dose levels

• Optimizes dosing regimens and administration routes

• Reduces the number of animals needed in preclinical studies through more efficient experimental design

• Provides a quantitative framework for understanding exposure-response relationships

The successful prediction of human PK/PD for BIIB059 using this approach demonstrates its value for accelerating the development of novel therapeutic antibodies while minimizing risk .

What are the critical experimental considerations for evaluating anti-BDCA2 antibodies in autoimmune disease models?

Evaluating anti-BDCA2 antibodies in autoimmune disease models requires careful experimental design to assess both mechanistic aspects and therapeutic potential. Several critical considerations include:

• Selection of appropriate disease models: For SLE research, models that recapitulate key features of human disease, including immune complex formation, IFN-I pathway activation, and pDC involvement, are essential. Non-human primates offer advantages due to better conservation of BDCA2 expression and function compared to rodents .

• Comprehensive pharmacodynamic assessment: Beyond measuring drug levels, researchers should evaluate:

  • BDCA2 receptor occupancy and internalization on pDCs

  • Inhibition of TLR-induced IFN-I production ex vivo

  • Changes in IFN-stimulated gene expression (IFN signature)

  • Effects on disease-relevant autoantibody production

• Distinguishing mechanisms of action: Experimental designs should differentiate between effects mediated by BDCA2 engagement versus Fc-dependent mechanisms. This can be achieved by comparing wild-type antibodies with Fc-modified variants that maintain BDCA2 binding but lack Fc effector functions .

• Temporal considerations: Treatment initiation at different disease stages (preventive versus therapeutic) provides insights into when pDC inhibition is most effective for disease modification.

• Dose-response relationship: Testing multiple dose levels is crucial for establishing the relationship between receptor occupancy, functional inhibition, and disease modification.

• Long-term assessment: Evaluating both efficacy and safety over extended periods addresses concerns about potential consequences of chronic pDC inhibition, particularly regarding antiviral immunity .

• Combination approaches: Testing anti-BDCA2 antibodies in combination with standard-of-care treatments or other experimental therapies can reveal potential synergistic effects relevant to clinical applications.

These experimental considerations ensure robust evaluation of anti-BDCA2 antibodies' therapeutic potential while providing mechanistic insights that guide clinical development.

How can researchers accurately measure BDCA2 internalization and correlate it with functional outcomes?

Accurate measurement of BDCA2 internalization following anti-BDCA2 antibody treatment requires sophisticated methodological approaches to avoid artifacts and establish clear correlations with functional outcomes. The following methods have proven effective in research settings:

• Flow cytometry with non-competing antibody clones: When measuring BDCA2 surface expression after treatment with anti-BDCA2 antibodies, researchers must use detection antibodies that bind to non-overlapping epitopes. For example, when studying 24F4A-induced BDCA2 internalization, researchers used antibody clone 2D6 for detection to avoid competition for binding sites .

• Dose-response analysis with correlation studies: Performing dose-response experiments with increasing concentrations of anti-BDCA2 antibodies allows determination of EC50 values for BDCA2 internalization, which can be directly compared with IC50 values for inhibition of IFN-α production. Research with 24F4A demonstrated a correlation between these parameters with an R² value of 0.68 .

• Ex vivo whole blood assays: These preserve physiological conditions and are preferable to isolated cell systems when assessing both BDCA2 internalization and functional inhibition of IFN-I production . This approach more closely approximates in vivo conditions.

• Time-course experiments: Measuring BDCA2 surface expression at multiple time points after antibody addition provides insights into internalization kinetics and the duration of receptor modulation, which is critical for predicting dosing intervals.

The following table summarizes key methodological approaches and their applications in anti-BDCA2 antibody research:

These methodological approaches have been validated in studies of antibodies like 24F4A, providing a framework for characterizing novel anti-BDCA2 antibodies in research and therapeutic development .

What approaches can optimize the translation of in vitro findings to in vivo efficacy for anti-BDCA2 antibodies?

Translating in vitro findings to in vivo efficacy for anti-BDCA2 antibodies requires bridging methodologies that account for the complexities of whole organism physiology. Several approaches have proven valuable for enhancing this translation:

• Ex vivo assays using in vivo samples: Collecting blood samples at various timepoints after in vivo administration of anti-BDCA2 antibodies and stimulating them ex vivo with TLR ligands provides a direct assessment of functional inhibition that bridges in vitro and in vivo settings . This approach was successfully used with 24F4A in cynomolgus monkeys, where inhibition of TLR9-induced IFN-I production was observed in blood samples collected post-administration .

• PK/PD modeling with mechanistic components: Developing models that incorporate both pharmacokinetic parameters and mechanistic aspects of receptor engagement, internalization, and functional inhibition provides a quantitative framework for predicting in vivo efficacy from in vitro data . For BIIB059, a two-compartment PK model linked with an indirect response PD model successfully predicted human responses from NHP data .

• Biomarker integration strategy: Identifying and validating biomarkers that reflect target engagement (BDCA2 internalization) and downstream functional effects (inhibition of IFN-I pathway) creates a translational bridge from in vitro findings to in vivo efficacy assessment. These biomarkers should be measurable in both preclinical models and clinical settings.

• Physiologically-based pharmacokinetic (PBPK) modeling: Incorporating tissue distribution patterns, receptor expression levels across tissues, and antibody properties into PBPK models enhances prediction of in vivo efficacy based on in vitro potency data.

• Comparative systems approach: Testing multiple anti-BDCA2 antibodies with varying in vitro characteristics in the same in vivo model helps establish quantitative relationships between in vitro parameters (e.g., affinity, internalization efficiency) and in vivo efficacy, guiding antibody optimization.

These approaches collectively enhance the translational value of in vitro findings and increase the probability of successful clinical development of anti-BDCA2 antibodies.

How should researchers design studies to evaluate the effects of anti-BDCA2 antibodies on immune complex-mediated pDC activation?

Evaluating the effects of anti-BDCA2 antibodies on immune complex-mediated pDC activation requires specialized experimental designs that reflect the pathological mechanisms of diseases like SLE. The following methodological approaches enable comprehensive assessment:

• Physiologically relevant immune complex preparation: Using well-characterized immune complexes is critical for disease-relevant results. Options include:

  • SLE patient-derived immune complexes containing nucleic acids and autoantibodies

  • Synthetic immune complexes generated from purified DNA/RNA and IgG

  • Surrogate immune complexes created by combining TLR ligands with antibodies

• Experimental timing variations: Testing antibody effects in different temporal relationships to immune complex exposure:

  • Pre-treatment model: Adding anti-BDCA2 antibodies before immune complex stimulation (preventive scenario)

  • Co-treatment model: Simultaneous addition of anti-BDCA2 antibodies and immune complexes

  • Post-activation model: Adding anti-BDCA2 antibodies after immune complex stimulation (therapeutic scenario)

• Mechanistic dissection through antibody engineering: Comparing the effects of:

  • Wild-type anti-BDCA2 antibodies with intact Fc regions

  • Fc-modified variants that maintain BDCA2 binding but lack CD32a engagement

  • F(ab')2 fragments that retain BDCA2 binding without Fc effector functions

This approach isolates the contribution of direct BDCA2 engagement versus CD32a-mediated effects. Research with 24F4A demonstrated that the Fc region was critical for potent inhibition of immune complex-induced IFN-I production through internalization of CD32a, highlighting the dual mechanism of action .

• Comprehensive readout parameters:

  • IFN-α/β production (protein level)

  • IFN-stimulated gene expression

  • Cell surface marker modulation (BDCA2, CD32a, activation markers)

  • Intracellular signaling pathway activation

By implementing these methodological approaches, researchers can comprehensively evaluate how anti-BDCA2 antibodies modulate immune complex-mediated pDC activation, which is particularly relevant for understanding their potential efficacy in SLE and other autoimmune conditions.

How can anti-BDCA2 antibodies advance our understanding of pDC biology in disease pathogenesis?

Anti-BDCA2 antibodies serve as powerful tools for dissecting the specific contributions of pDCs to disease pathogenesis, offering advantages over less selective approaches. Their research applications include:

• Selective functional inhibition: Unlike genetic depletion models or broad-spectrum immunosuppressants, anti-BDCA2 antibodies allow researchers to selectively inhibit pDC function without eliminating the cells or affecting other immune populations . This selectivity helps identify pDC-specific contributions to disease processes.

• Temporal intervention studies: By administering anti-BDCA2 antibodies at different disease stages in animal models or experimental systems, researchers can determine critical windows during which pDC activity drives disease initiation, progression, or flares. This temporal precision is particularly valuable for understanding the dynamic role of pDCs in autoimmune diseases like SLE.

• Pathway dissection: Anti-BDCA2 antibodies inhibit IFN-I production by pDCs while potentially preserving other functions . This selective inhibition allows researchers to distinguish IFN-dependent from IFN-independent contributions of pDCs to disease pathology.

• Human translational research: Ex vivo treatment of patient samples with anti-BDCA2 antibodies provides insights into how pDC inhibition might affect disease-relevant parameters in different patient subsets. The research with 24F4A successfully demonstrated inhibition of TLR-induced IFN-I in blood from both healthy and SLE donors, confirming translational relevance .

• Autoantibody development investigation: By modulating pDC function at different stages of disease development, researchers can investigate how these cells contribute to autoantibody generation, a critical aspect of autoimmune pathogenesis . This is particularly relevant given observations that "autoantibodies can be used as promising biomarkers for diagnosis/prognosis of various diseases" .

These research applications highlight the value of anti-BDCA2 antibodies as selective tools for advancing our understanding of pDC biology in disease, beyond their potential therapeutic applications.

What role might anti-BDCA2 antibodies play in investigating the link between viral infections and autoimmunity?

Anti-BDCA2 antibodies provide unique opportunities to investigate the complex relationship between viral infections and autoimmunity, particularly in light of emerging research on COVID-19 and autoantibody development. Their application in this field enables several research directions:

• Post-viral autoimmune phenomena: Recent research has demonstrated that "COVID-19 triggers the development of autoantibodies directly" and that "these autoantibodies can remain for over 6 months, or much longer, after the original COVID-19 virus disappeared" . Anti-BDCA2 antibodies can help determine whether pDC activation during viral infections represents a mechanistic link to subsequent autoantibody development.

• Sex-specific autoimmune responses: Studies have identified "sex-specific patterns of autoantibody reactivity" following COVID-19, with "males carrying the risk of diverse autoimmune activation following symptomatic COVID-19, while females carry the risk for a distinct profile of autoimmune activation following asymptomatic COVID-19" . Anti-BDCA2 antibodies could help investigate whether differential pDC activation contributes to these sex-specific patterns.

• Long COVID mechanisms: As "many scientists believed that autoantibodies may play a role in long COVID symptoms" , anti-BDCA2 antibodies provide a tool to examine whether persistent pDC activation maintains autoantibody production and contributes to chronic symptoms.

• Preventive intervention models: In experimental viral infection models, prophylactic administration of anti-BDCA2 antibodies could test whether preventing early pDC activation might reduce subsequent autoimmune manifestations, potentially informing early intervention strategies for at-risk individuals.

• Viral-induced IFN signatures: By modulating pDC responses during viral infections, researchers can determine how virus-induced IFN signatures compare with autoimmune disease-associated IFN signatures, and whether they contribute differently to pathology.

These applications of anti-BDCA2 antibodies could provide critical insights into the mechanistic links between viral infections and autoimmunity, potentially identifying new therapeutic targets and intervention windows.

How can anti-BDCA2 antibodies contribute to developing better models of autoantibody-mediated diseases?

Anti-BDCA2 antibodies offer several advantages for developing improved models of autoantibody-mediated diseases, advancing both basic understanding and therapeutic development:

• Mechanistic disease models: By selectively inhibiting pDC function at different disease stages, researchers can develop refined models that distinguish between pDC-dependent and pDC-independent phases of autoantibody-mediated diseases. This precision helps identify optimal intervention windows for different therapeutic approaches.

• Biomarker validation: Anti-BDCA2 antibodies enable validation of biomarkers that reflect pDC activation and IFN pathway engagement in autoimmune diseases . These biomarkers can improve diagnostic accuracy, patient stratification, and treatment monitoring in both experimental models and clinical settings.

• Treatment response prediction: Testing anti-BDCA2 antibodies in diverse autoimmune disease models helps identify disease characteristics that predict response to pDC-targeted therapies. This contributes to developing "more targeted approach" treatments, as mentioned in the literature .

• Dual-mechanism modeling: The dual mechanism of action of effector-competent anti-BDCA2 antibodies (BDCA2 engagement and CD32a effects) provides a framework for modeling complex intervention strategies in autoantibody-mediated diseases . This complexity better reflects the multifaceted nature of human autoimmune conditions.

• Vaccine response modeling: Methodologies developed for "phenomenological modeling of antibody reactivity elicited by nanoparticle-based vaccines" could be adapted, using anti-BDCA2 antibodies as experimental tools, to model autoantibody responses in different disease states . Such models could help predict "vaccine efficacies against arbitrary pathogen variants" and, by extension, therapeutic responses in heterogeneous autoimmune diseases.

By applying anti-BDCA2 antibodies in these contexts, researchers can develop more sophisticated and clinically relevant models of autoantibody-mediated diseases, accelerating therapeutic development and improving patient outcomes.

What biomarkers could improve patient selection and response monitoring for anti-BDCA2 antibody therapies?

Identifying reliable biomarkers for patient selection and treatment monitoring represents a critical challenge in advancing anti-BDCA2 antibody therapies. Several promising biomarker approaches warrant further investigation:

• IFN signature stratification: Gene expression profiles of IFN-stimulated genes could identify patients with high IFN pathway activation who might benefit most from pDC inhibition. Different patterns within the IFN signature might predict specific responses to anti-BDCA2 therapy versus other IFN-targeting approaches.

• pDC activation state assessment: Baseline measurements of pDC activation markers and their capacity to produce IFN-I upon stimulation might predict the magnitude of response to anti-BDCA2 antibodies. This functional characterization goes beyond simple enumeration of pDCs.

• Autoantibody profiles: Specific autoantibody patterns might identify patients with greater pDC activation driven by immune complexes, who could particularly benefit from the dual mechanism of anti-BDCA2 antibodies . Since "autoantibodies can be used as promising biomarkers for diagnosis/prognosis of various diseases" , integrating autoantibody profiling into patient selection strategies appears logical.

• CD32a polymorphism analysis: Given the role of CD32a in the mechanism of action of effector-competent anti-BDCA2 antibodies , genetic polymorphisms in this receptor might influence therapeutic response, particularly for immune complex-mediated disease manifestations.

• Tissue-specific biomarkers: For diseases with organ-specific manifestations like cutaneous lupus, biomarkers reflecting local pDC infiltration and activation in affected tissues might better predict response than systemic markers.

• Dynamic biomarker assessment: Early changes in selected biomarkers following initial doses could predict subsequent clinical response, enabling adaptive treatment strategies and early identification of non-responders.

Implementation of these biomarker approaches would support precision medicine for anti-BDCA2 antibody therapy, improving patient selection, treatment monitoring, and ultimately clinical outcomes.

How might computational approaches enhance anti-BDCA2 antibody development and application?

Computational approaches offer powerful tools to accelerate anti-BDCA2 antibody development and optimize their clinical application:

• PK/PD modeling with cross-species translation: As demonstrated with BIIB059, sophisticated PK/PD modeling can successfully scale preclinical data to predict human responses . This approach combines "traditional allometric PK scaling with sensitivity-analysis-driven scaling of the PD" to predict clinical outcomes and support first-in-human dose selection .

• Antibody engineering optimization: Computational approaches to epitope mapping, structural modeling, and binding kinetics simulation can guide the engineering of anti-BDCA2 antibodies with optimized properties for:

  • Enhanced BDCA2 internalization efficiency

  • Optimal Fc functionality for CD32a engagement

  • Improved tissue penetration

  • Extended half-life

• Systems immunology modeling: Computational models integrating IFN signaling networks, pDC regulatory pathways, and autoantibody development cascades can predict the systems-level impact of pDC inhibition by anti-BDCA2 antibodies, accounting for feedback mechanisms and pathway redundancies.

• Patient stratification algorithms: Machine learning approaches applied to multiparametric patient data (genetic, transcriptomic, proteomic, clinical) could identify biomarker signatures predictive of response to anti-BDCA2 antibody therapy, supporting precision medicine approaches.

• Phenomenological response modeling: Similar to approaches described for vaccine responses, where researchers "describe a simple biologically motivated model of antibody reactivity elicited by nanoparticle-based vaccines using only antigen amino acid sequences" , computational models could predict the effects of anti-BDCA2 antibodies on diverse immune parameters.

• Virtual clinical trial simulations: Integrating disease progression models with PK/PD models enables virtual trial simulations to optimize clinical trial design, dose selection, and endpoint selection for anti-BDCA2 antibody clinical development.

These computational approaches can significantly accelerate development timelines, reduce costs through more efficient experimental design, and increase the probability of clinical success by providing quantitative predictions of human responses.

What challenges remain in optimizing anti-BDCA2 antibodies for diverse autoimmune conditions?

Despite promising advances, several significant challenges remain in optimizing anti-BDCA2 antibodies for diverse autoimmune conditions:

• Balancing efficacy and safety: Determining the optimal degree of pDC inhibition that addresses autoimmunity without compromising antiviral defense remains challenging. While functional inhibition rather than depletion preserves some pDC functions , the long-term safety implications of chronic pDC inhibition require careful evaluation.

• Disease heterogeneity: Autoimmune diseases like SLE show considerable heterogeneity in pathogenesis, clinical manifestations, and treatment response. Identifying which disease subsets will benefit most from anti-BDCA2 antibody therapy requires sophisticated patient stratification approaches.

• Tissue penetration optimization: Many autoimmune diseases affect specific tissues and organs. Ensuring sufficient penetration of anti-BDCA2 antibodies into affected tissues, particularly for antibodies with large molecular weight, presents a pharmacokinetic challenge.

• Combination therapy development: Identifying optimal combinations of anti-BDCA2 antibodies with other immunomodulatory agents requires systematic evaluation of potential synergies and safety profiles. This is particularly important since monotherapy rarely achieves complete disease control in complex autoimmune conditions.

• Biomarker development: Developing reliable biomarkers for patient selection, dose optimization, and response monitoring remains challenging but essential for maximizing therapeutic benefit and minimizing unnecessary exposure.

• Timing of intervention: Determining the optimal disease stage for intervention with anti-BDCA2 antibodies—early prevention versus established disease treatment—requires longitudinal studies and better understanding of disease evolution.

• Viral infection risk management: Since pDCs play important roles in antiviral defense, strategies to manage potential viral infection risks during anti-BDCA2 antibody therapy need development. This is particularly relevant given observations about the relationship between autoimmunity and infection responses .

Addressing these challenges requires integrated approaches combining advanced antibody engineering, sophisticated clinical trial design, computational modeling, and continued refinement of our understanding of pDC biology in health and disease.