Four Ways Biopharma Programs Are Using High-Plex Spatial Proteomics in Clinical Development

By Anna Green · Marketing Manager · RareCyte

Spatial biology is moving beyond exploratory research

High-plex spatial proteomics is rapidly moving beyond exploratory research and becoming an increasingly important component of translational research, biomarker development, and clinical trials.

As biopharma organizations seek better biomarkers, more precise patient stratification strategies, and deeper insight into therapeutic response, traditional tissue analysis approaches are increasingly showing their limitations. Measuring a single biomarker in isolation is often insufficient to explain why therapies succeed in some patients, fail in others, or generate unexpected resistance mechanisms over time.

Researchers increasingly need to understand biology within its native tissue context:

• Which immune cells are present?
• Where are they located?
• How are they interacting?
• How does tissue architecture influence therapeutic response?
• Which spatial patterns correlate with patient outcomes?

High-plex spatial proteomics tools address these questions by enabling simultaneous measurement of multiple proteins within intact tissue while preserving spatial relationships between cells and tissue structures.

With new technologies capable of biomarker depth and reproducible, scalable workflows, its role in drug development is expanding rapidly. What began primarily as a discovery research tool is increasingly being integrated into translational workflows, biomarker development programs, and clinical trials.

As adoption grows, researchers are evaluating spatial proteomics technologies on more than multiplex depth alone. Increasingly, the focus is expanding to include reproducibility, throughput, tissue preservation, workflow standardization, and the ability to support larger translational and clinical development programs.

Below are four major ways biopharma organizations are using spatial proteomics in clinical research today.

1. Enabling Biomarker Development and Tissue Analysis at Scale

One of the biggest challenges in translational research is bridging exploratory biology discoveries to clinically scalable biomarker workflows. Discovery research often prioritizes broad biological exploration. Clinical deployment, however, requires focused biomarker panels, reproducible assays, and scalable operational workflows. Biomarker development connects these two phases.

At this stage, researchers are often working to:

• Narrow broad exploratory panels into focused translational assays
• Validate biomarker reproducibility across larger cohorts
• Improve confidence in spatial signatures associated with response
• Standardize workflows for multi-site studies
• Generate clinically actionable tissue data

This process requires technologies capable of balancing multiplex depth with operational practicality. Traditional low-plex workflows may lack sufficient biological depth, while cyclic workflows may become difficult to scale operationally across large studies. Modern spatial proteomics approaches are increasingly helping bridge this gap by enabling:

• More comprehensive tissue characterization
• High-quality multiplex imaging
• Improved tissue preservation
• Reduced tissue consumption
• Reproducible spatial analysis
• More scalable translational workflows

For biopharma organizations, the ability to combine meaningful biological insight with reproducible and scalable biomarker workflows is becoming increasingly important. The spatial biology field is evolving from exploratory research toward clinical utility.

2. Understanding Mechanism of Action in Human Tissue

Preclinical models can help predict whether a therapy should work. Clinical tissue analysis helps determine whether and how it is actually working. As therapies enter clinical development, researchers need to understand how drugs are impacting the local tissue microenvironment and whether intended biological effects are occurring within patient tissue.

In a cancer tumor resection, the tissue may contain cytotoxic T cells, for example, but if those cells remain spatially excluded from tumor regions, therapeutic response may still be limited. Similarly, macrophages or stromal populations may influence response differently depending on their organization within tissue.

Spatial proteomics enables researchers to answer questions such as:

• Which cellular neighborhoods emerge during treatment?
• Are immune cells successfully infiltrating disease tissue?
• Are suppressive immune populations limiting response?
• How do spatial interactions change over time?

These insights are difficult or impossible to capture using bulk molecular assays or low-plex approaches. Thus, spatial context frequently matters as much as biomarker presence alone.

Edward Lo, PhD, RareCyte Principal Scientist, explains, “mechanism of action studies require panels in the 10-18 marker range, with enough markers to define cell types and capture functional states simultaneously, on the same tissue section, from the same cells”.

These spatial insights are increasingly being used to support pharmacodynamic biomarker strategies and improve understanding of treatment response mechanisms during translational development.

3. Identifying Predictive Biomarkers for Patient Stratification

Patient response variability remains one of the biggest challenges in drug development. Two patients with seemingly similar disease profiles may respond very differently to the same therapy. Increasingly, researchers are discovering that the spatial organization of diverse cell types and states within tissue microenvironments can provide predictive information that is missed when measuring drug target biomarker expression alone.

Spatial proteomics allows researchers to analyze key components of the tissue microenvironment, including:

• Cellular composition
• Immune phenotypes
• Spatial interactions
• Lesion-stroma organization
• Functional marker expression
• Spatially-defined biomarker signatures

These multidimensional tissue features can help identify patient populations more likely to respond to specific therapies. Importantly, clinically useful biomarkers often require more than identifying whether a single biomarker is present.

Researchers increasingly need to understand:

• Which cells express the marker
• Where those cells are located
• Which neighboring cells are interacting with them
• Whether specific spatial arrangements correlate with outcomes

This has become especially important during biomarker development, where researchers must confidently narrow broad exploratory findings into smaller, clinically actionable biomarker panels capable of supporting translational and clinical decision-making.

At this stage, assay sensitivity, data quality, reproducibility, and accuracy become critically important. Researchers need sufficient multiplex depth to explore complex tissue biology, while also generating reproducible data that can support larger cohort validation and future clinical deployment. As biomarker strategies become more sophisticated, spatially resolved tissue analysis is becoming increasingly valuable for translational and clinical development programs.

4. Supporting Clinical Trial Decision-Making

Spatial proteomics is also being used to support critical clinical development decisions.

Drug development programs generate large amounts of biological data, but translating those data into actionable clinical insight remains challenging.

Researchers are increasingly applying spatial biology approaches to:

• Evaluate pharmacodynamic response
• Understand resistance mechanisms
• Compare responder versus non-responder populations
• Assess target engagement
• Refine enrollment strategies
• Prioritize combination therapies

In many cases, spatial data helps teams determine whether observed clinical outcomes align with the underlying biology of the therapy. This can be particularly valuable during early-stage clinical studies, where mechanistic understanding may influence decisions regarding trial expansion, biomarker strategies, or future development direction.

Spatial proteomics is also increasingly supporting biomarker-informed clinical trial strategies, including patient enrichment approaches and translational endpoint development. As clinical cohorts grow larger, however, operational considerations become increasingly important. Clinical research environments require workflows capable of delivering:

• Reproducible results
• Standardized assays
• Efficient turnaround times
• Scalable sample processing

These requirements are driving broader industry interest in spatial proteomics workflows designed not only for biological discovery, but also for translational scalability.

The future of spatial biology is increasingly clinical

Spatial proteomics is no longer limited to exploratory research environments. Across biopharma, researchers are using spatial biology to support critical clinical development decisions, from understanding mechanism of action and identifying predictive biomarkers to supporting stratification strategies and clinical trial design.

As adoption grows, the conversation is also evolving. The industry is moving beyond questions of multiplex depth alone toward broader considerations around:

• Reproducibility
• Throughput
• Workflow standardization
• Tissue preservation
• Scalability
• Clinical relevance
• Biomarker deployment readiness

These requirements reflect a broader shift occurring across translational and clinical research. Researchers need technologies capable of generating biologically meaningful insights while providing the operational performance necessary to support larger studies, biomarker validation efforts, and clinical development programs.

These evolving requirements directly drove the development of the Orion™ spatial proteomics platform.

By utilizing a high-plex single-round staining and imaging workflow, Orion delivers the biomarker depth, reproducibility, throughput, and data quality researchers need to translate spatial insights into confident clinical decisions. Explore Orion →

If you’re interested in incorporating spatial proteomics into your drug development process and have platform and workflow questions, RareCyte’s spatial biology team will walk you through the process. Book a scientific consultation →