Biomarkers are foundational to precision medicine, supporting diagnosis, disease monitoring and guiding treatment decisions. However, translating a biomarker from research into clinical practice is complex. Achieving translational readiness requires rigorous evidence and validation across the entire biomarker workflow.

Translational readiness is built across the full lifecycle

Five requirements help turn biomarker evidence into a clear, clinically relevant path to translation:

• Context of use: Define the intended application and the clinical decision the biomarker will support
• Evidence generation: Build reproducible, fit-for-purpose datasets across studies and cohorts
• Assay performance: Demonstrate robust, clinically deployable assays with appropriate sensitivity, specificity and reproducibility
• Clinical validation: Confirm clinical relevance, utility and impact on patient care
• Regulatory alignment: Support regulatory compliance through evidence, documentation and data standards such as data integrity

Where biomarker translation breaks down

Despite these defined requirements, biomarker translation remains limited by persistent barriers:

Building a connected path to biomarker translation

Overcoming these challenges requires an interconnected, end-to-end solution that combines analytical rigor, workflow standardization and data traceability. Connected capabilities across sample processing, validation, measurement, genomics and data management can reduce variability and strengthen biomarker evidence.

1. Standardized sample processing

Biomek i-Series liquid handlers and Echo acoustic liquid handlers automate sample preparation to reduce manual variability, standardize workflows and improve traceability from discovery through clinical research. By automating critical steps and enforcing standardized protocols, they strengthen chain-of-custody documentation, maintain sample integrity and support scalable execution across larger studies.

We See a Way to accelerate biomarker discovery by reducing hands-on sample preparation time by up to 2.5 hours

Beckman Coulter Life Sciences | Biomek i3, Biomek i5, Biomek i7 Automated Workstations

Learn More

2. Reproducible biological solutions

Validated recombinant antibodies, assay reagents, Cell DIVE™ multiplex imaging and the ATTOAuriga™ reagent ecosystem support workflows that deliver consistent biological specificity and sensitivity across biomarker studies. Validated staining, imaging and analysis protocols help support greater confidence in translational biomarker programs.

3. Robust analytical validation

The ZenoTOF 8600 system and SCIEX 7500+ system, paired with Phenomenex LC columns, deliver sensitive biomarker quantification and reproducible analytical performance. Standardized methods and validation practices support consistent results across laboratories and studies.

4. Genomic biomarker discovery and validation

xGen™ NGS solutions, Archer™ targeted research solutions and custom oligonucleotides enable sensitive genomic biomarker discovery, detection and validation through standardized sequencing workflows. These capabilities improve reproducibility and support the generation of translationally relevant genomic evidence.

5. Traceable data analytics and audit-ready data

The Genedata Biopharma Platform offers a centralized digital system to integrate and analyze biomarker data throughout the development lifecycle, maintain audit trails and enable regulatory-ready evidence. This supports compliance and clinical progress. Complementing it, Molecular Devices SoftMax® Pro GxP software ensures traceable data from acquisition to reporting, with secure audit trails, electronic signatures and validation for compliance workflows.

Connecting evidence across the biomarker lifecycle

Together, these capabilities create a connected biomarker workflow that reduces variability, improves reproducibility and maintains data traceability from discovery through clinical validation. By integrating workflows and evidence across the biomarker lifecycle, programs can advance toward clinical translation with greater confidence.

Explore how connected workflows can help improve reproducibility, traceability and confidence from discovery through clinical validation.