Discovery is only the beginning
Identifying a promising biomarker is an important milestone, but it is rarely the point at which a clinical study can begin. Discovery experiments are designed to explore biology, generate hypotheses and identify molecular signals that may be associated with disease, treatment response or patient outcomes. Clinical studies have a different objective. They require biomarker data that are reproducible, well documented and appropriate for supporting development decisions.
Moving from discovery into a GCP-aligned study therefore involves more than selecting a different analytical platform. It requires refining the biological question, defining how the biomarker will be measured and ensuring the entire workflow can generate reliable data from real clinical samples.
Why promising biomarkers often fail to progress
Many biomarkers never reach clinical evaluation, not always because the underlying biology is incorrect, but because the transition from research to clinical application introduces new challenges.
A biomarker identified in an exploratory RNA sequencing study may perform well in carefully selected research samples but prove difficult to reproduce in routine FFPE tissue. Low RNA quality, heterogeneous tumour content and variability in sample collection between clinical sites can all affect whether the original finding remains reliably measurable.
Other biomarkers simply answer the wrong question. A statistically significant signal is not necessarily clinically relevant. Before progressing into a clinical study, researchers need confidence that the biomarker reflects a biological mechanism relevant to treatment response or disease progression.
Successful biomarker development therefore begins by filtering discoverables into deliverables. This requires sufficient insight into the disease mechanisms, biomarker related pathways and patient populations to tease translatable biomarkers or signatures from the discovery data.
From discovery to clinical studies: what changes?
The transition from discovery research to a GCP-aligned study is characterised by a shift in priorities.
The scientific question becomes more focused, while expectations for documentation, consistency and sample governance increase significantly.
Building a biomarker workflow that is fit for purpose
Once a biomarker has been prioritised, the analysis pipeline should be designed around its intended use rather than the available technology.
This starts by asking practical questions.
- What clinical decision will the biomarker support?
- Which sample/tissue type will be analysed?
- Are FFPE samples the primary source of material?
- How much tissue is available?
- Which assay can measure the biomarker consistently?
- How will data quality be assessed?
- What documentation will be required throughout the study?
Answering these questions early reduces methodological uncertainty later in the programme and helps ensure the assay is appropriate for the available clinical material.
Why pathology remains central
Biomarker development is often discussed in terms of molecular technologies, yet the sample availability itself frequently determines what results can practically be generated.
The next step is identifying the correct sample groups for baseline and comparison, in order that relevant effects can be clearly observed. Once collected, the samples from those groups must then be reviewed before inclusion in the study.
Two samples collected from the same tumour may differ considerably in tumour cellularity, necrosis, stromal composition, immune infiltration and even normal or adjacent tissue. These differences influence not only the quality of the molecular data but also the biological interpretation of the results. Comparing measurements across one or more of these differences may be part of the intended analysis, but others may be confounding.
Pathology review helps identify whether the region selected for analysis is appropriate for the biomarker under investigation. It also provides essential context for interpreting unexpected findings and ensuring samples meet predefined eligibility criteria before testing begins.
Rather than acting as a final quality check, understanding not only the patient but also sample pathology should form part of assay planning from the earliest stages of biomarker development.
Choosing the right analytical approach
Finally, once the question has been defined and sampling strategy is confirmed, the analysis may be selected to suit the experimental approach – what material is available and what measurements are needed from it.
Different stages of biomarker development ask different questions of different sample cohorts, often requiring different analytical technologies.
RNA sequencing
remains highly valuable during discovery, when researchers are exploring transcriptome-wide biology or identifying novel biomarkers and where single base resolution is required. It is best suited to high quality RNA from un-fixed tissue.
QPCR
is well suited to focused studies measuring a small number of predefined targets where rapid, targeted quantification is required.
nCounter Analysis
occupies the space between these approaches. When the broad tissue or pathway compartment is known, or when a biomarker signature has already been defined, targeted multiplex gene expression analysis enables multiple transcripts to be measured simultaneously while making efficient use of low-quality RNA from commonly collected FFPE samples and other challenging clinical material.
Reproducibility depends on more than the assay
Selecting the appropriate platform is only one part of generating reliable biomarker data.
Reproducibility is influenced by every stage of the workflow, including tissue selection, fixation, storage, RNA extraction, assay performance, quality control, data processing and interpretation. Clinical samples may also pass through multiple laboratories, introducing further opportunities for variation if procedures are not clearly defined.
Standardised sample collection, storage and transport pathways, and robust documentation at each analytical step helps ensure biomarker results can be interpreted with confidence and reproduced throughout the clinical development programme, and between modalities.
A successful transition requires planning, not just technology
Translating a biomarker from discovery into a GCP-aligned clinical study is fundamentally a process of refinement. Broad biological observations become focused hypotheses, exploratory workflows become standardised analytical methods and research data become evidence that supports clinical development.
Achieving that transition requires more than selecting an assay. The entire process must be developed as fit-for-purpose for each stage of development. This pathway incorporates every stage from pathology review, sample quality assessment, analytical planning and everything from hardware and reagents to software, decision planning, staff training and robust documentation into a workflow that is aligned with the intended clinical use.
At Propath UK, we support this transition through a multi-platform and pathology-led approach to biomarker development, helping researchers connect molecular analysis with tissue context and generate data that are appropriate from research to translational and clinical trials.
