Immune Profiling: The Common Language of Modern Pharmacology

Immunological impact across diseases

Far more therapeutic areas involve immune regulation than traditional disease boundaries have suggested, leading to practical implications for how we profile drug candidates. Already a staple in immuno-oncology, autoimmune, and infectious disease drug discovery, immune profiling has been gaining traction across broader disease indications, including fibrosis, neurodegeneration, metabolic dysfunction, and even cardiovascular disease.

At the same time, therapeutic innovations ranging from multispecific biologics to cell and gene therapies are drawing immunology to the forefront of early discovery, regardless of the indication. These modalities engage immune pathways directly, making mechanistic immune readouts indispensable across programs once considered “non-immune.”

Although immune function is evaluated throughout the entire course of oncology and infectious disease research programs, indications with non-obvious immunology connections often receive less focus on immune profiling in early-stage programs. Researchers across these diseases are now finding that early immune profiling can enable the discovery of mechanistic drivers of efficacy and safety, reduce late-stage attrition, and more accurately predict patient response.

The result is clear: immune profiling is becoming a language through which early discovery across diseases can increasingly interpret biological intent.

Immune phenotypes offer insights into disease mechanisms and potential treatment targets

Immune pathways are increasingly recognized as core drivers of disease behavior across therapeutic areas. Critically for drug discovery teams, immune-regulatory states can directly influence inflammatory responses and immune cell function, ultimately affecting therapeutic outcomes.

For example, in neurodegeneration, microglia adopt distinct immune-regulated activation phenotypes that correlate with synaptic loss, cognitive decline, and differential responsiveness to emerging therapeutics.^1–3 These immune-regulatory states do not simply mirror pathology; they appear to drive mechanistic divergence within diseases we once treated as homogeneous.

A similar revelation is occurring in fibrosis research. Instead of a linear progression driven solely by fibroblast biology, fibrosis is now understood as the outcome of immune–stromal circuits that toggle damaged tissue toward repair or toward persistent scarring.^4,5 Distinct macrophage subsets, defined by their metabolic wiring, spatial localization, and cytokine signature, act as upstream regulators of this trajectory. Likewise, T‑cell activation states play a decisive role in determining whether tissue returns to homeostasis or slips into chronic inflammation and fibrosis⁸. Together, these immune programs form control nodes that can redirect an organ’s fate even when fibroblast‑intrinsic pathways remain unchanged, highlighting the importance of targeting immune regulation alongside stromal biology in antifibrotic strategies.

In metabolic dysfunction, the field has progressed beyond the high-level concept of “metaflammation” to immunometabolic checkpoints that integrate tissue stress, nutrient cues, and inflammation. These checkpoints, including succinate signaling, lipid-handling programs, and mitochondrial rewiring within macrophages and T cells, now appear to delineate disease subtypes with different therapeutic sensitivities.^6,7

Although these diseases are traditionally considered “non-immune,” immune cells play a pivotal regulatory role that affects the tissue state and response to therapeutics, making immune profiling a valuable asset for drug development.

Why emerging therapeutic modalities depend on immune profiling

Beyond the therapeutic areas themselves, emerging modalities are also demanding earlier examination of the immune response. Multispecific biologics, targeted protein degraders, RNA-based therapeutics, and microglia- or stroma-directed agents all engage pathways that intersect with immune circuits, even when the intended mechanism is not overtly immunological.

Across indications, researchers are increasingly using immune profiling to gain an early read on immune-related variables that influence therapeutic success:

• Whether a biologic triggers immunogenicity that compromises efficacy or safety
• Whether RNA therapeutics provoke innate immune activation that limits durability
• Whether stroma-modulating agents shift macrophage phenotypes toward tissue repair or fibrosis
• How candidate compounds affect T cell activation, exhaustion, or cytokine release in disease-relevant contexts

Even when therapies are not designed to modulate immunity directly, they often reshape local immune networks downstream, sometimes in ways that introduce translational risk. Early in vitro immunology assays provide a practical way to surface these context-dependent effects at a stage when study design, dose selection, and prioritization are still flexible, helping researchers de-risk critical early pipeline decisions.

Immune function as a core mechanistic readout

With immune pathways now recognized as key drivers of disease biology, many teams are integrating immune readouts as primary mechanistic endpoints alongside traditional biochemical and phenotypic assays.⁷ This shift is driven by a practical reality: early in vitro immune data can help teams prioritize candidates and de-risk decisions long before in vivo models reveal similar insights.

Researchers can use in vitro immune profiling to:

• Map early mechanism of action: Assays quantifying T-cell activation, macrophage state transitions, cytokine modulation, and immunometabolic shifts provide early mechanistic evidence of how a therapeutic engages immune pathways.^1,2,7
• Identify context-dependent effects: Co-culture systems incorporating immune-competent components help reveal whether candidate molecules behave differently in inflamed, fibrotic, immunosuppressed, or regeneration-biased environments.^4,5,7
• Predict translational risk: Early patterns such as aberrant cytokine signatures or inappropriate activation thresholds can highlight safety liabilities well before in vivo studies.⁷
• Guide rational combinations: Immune readouts can indicate whether a candidate synergizes or conflicts with agents targeting immunity, stroma, or immunometabolic pathways.^6,7
• Establish biomarkers and pharmacodynamic anchors: Cytokine ratios, exhaustion-state markers, and macrophage phenotypes frequently map onto translatable preclinical and early clinical readouts.⁷

By incorporating immune profiling upstream, development teams can create a feedback loop between early discovery, translational research, and patient-stratification strategies. The result is a more contextual and predictive preclinical understanding—one that clarifies how a therapeutic is likely to behave in vivo and across diverse patient backgrounds.

Immune intelligence strengthens drug development strategy

As disease biology and therapeutic design continue to converge on immune-regulated pathways, immune profiling is becoming a foundational component of translational strategy rather than a discipline-specific toolkit. What began as a set of assays largely associated with oncology and classical immunology is now recognized as a readily adaptable way to study immune modulation across diseases.

This shift is reshaping project strategies. Preclinical teams are integrating immune assays earlier, translational groups are using immune signatures to refine patient stratification hypotheses, and program leads are relying on immune-modulation data to select or deprioritize candidates with far greater confidence. Across these decisions, immune profiling data can help tie mechanistic signals to translational strategy.

In this landscape, the organizations that thrive will be those that treat immune function as a unifying layer of pharmacology, not an optional readout. Whether working in fibrosis, neurodegeneration, metabolic dysfunction, chronic infection, oncology, or regenerative biology, teams that incorporate in vitro immunology assays into preclinical studies gain a more complete understanding of therapeutic potential.

Explore our IO services to learn how we can strengthen your discovery pipeline, from immuno‑oncology to any therapeutic area where the immune system shapes disease and response to therapy.

References

(1) Xu, Y.; Gao, W.; Sun, Y.; Wu, M. New Insight on Microglia Activation in Neurodegenerative Diseases and Therapeutics. Front. Neurosci. 2023, 17. https://doi.org/10.3389/fnins.2023.1308345.

(2) Gao, C.; Jiang, J.; Tan, Y.; Chen, S. Microglia in Neurodegenerative Diseases: Mechanism and Potential Therapeutic Targets. Signal Transduct. Target. Ther. 2023, 8 (1), 359. https://doi.org/10.1038/s41392-023-01588-0.

(3) Weiner, H. L. Immune Mechanisms and Shared Immune Targets in Neurodegenerative Diseases. Nat. Rev. Neurol. 2025, 21 (2), 67–85. https://doi.org/10.1038/s41582-024-01046-7.

(4) Behmoaras, J.; Mulder, K.; Ginhoux, F.; Petretto, E. The Spatial and Temporal Activation of Macrophages during Fibrosis. Nat. Rev. Immunol. 2025, 25 (11), 816–830. https://doi.org/10.1038/s41577-025-01186-x.

(5) Feng, L.; Chen, X.; Huang, Y.; Zhang, X.; Zheng, S.; Xie, N. Immunometabolism Changes in Fibrosis: From Mechanisms to Therapeutic Strategies. Front. Pharmacol. 2023, 14. https://doi.org/10.3389/fphar.2023.1243675.

(6) Ma, H.; Gao, L.; Chang, R.; Zhai, L.; Zhao, Y. Crosstalk between Macrophages and Immunometabolism and Their Potential Roles in Tissue Repair and Regeneration. Heliyon 2024, 10 (18). https://doi.org/10.1016/j.heliyon.2024.e38018.

(7) Hu, T.; Liu, C.-H.; Lei, M.; Zeng, Q.; Li, L.; Tang, H.; Zhang, N. Metabolic Regulation of the Immune System in Health and Diseases: Mechanisms and Interventions. Signal Transduct. Target. Ther. 2024, 9 (1), 268. https://doi.org/10.1038/s41392-024-01954-6.

(8) Zhang M and Zhang S. T Cells in Fibrosis and Fibrotic Diseases. Front. Immunol. 2020, 11:1142. https://doi.org/10.3389/fimmu.2020.01142