Trends in Biomarker Research: Make it Right-Sized

Not every patient responds to treatment the same way or benefits from the same treatment, which is why current biomarker research is focused on right-sized automation to achieve cost-efficiency and scalability of lab operations

Precision medicine relies on customizing medical treatments based on individual patient profiles, but the concept also has been criticed¹. For patient management and medical translation biomarkers are indispensable. Those measurable in blood or biofluids are easier to access than tissue sampling. They are central to understanding the pharmacodynamic/pharmacokinetic relationship of a drug candidate during development. Having deep understanding of a disease pathway comes before selecting the most pertinent biomarkers; relevant indicators or surrogate indicators tied to a patho-mechanism can also be studied simultaneously with disease origin and progression. Basic research continues to uncover new scientific insights that could lead to breakthrough discoveries in these explorations.

Biomarkers help determine not only whether a patient should receive treatment but also how it is progressing, thus informing clinicians to adjust dosages or even discontinue interventions. This adaptability is critical in avoiding one-size-fits-all approaches, thereby optimizing therapeutic outcomes while minimizing adverse reactions. Predictive biomarkers help decide whether a patient should undergo therapy, while pharmacodynamic markers provide mechanistic insights into how a treatment affects the body. For instance, the levels of functional CD8+ T-cells in the tumor microenvironment (TME) can indicate how well immunotherapies work in a patient. Most recently IL-23R has been linked to cell aging. Plasma levels of this analyte increase as cells stop dividing, providing a valuable marker for studying cellular senescence and age-related diseases². On the other hand, toxicity indicators enable clinicians to monitor adverse effects, ensuring that a treatment remains safe and tolerable.

Pharmacodynamic markers, particularly those identifying immune cells, are increasingly important during clinical trials. These markers offer a global or focused assessment of the patient's immune system, paving the way for tailored therapeutic strategies that maximize efficacy and reduce side effects.

Ligand Binding Assay Platforms

Bioanalytical readouts, for example via ligand binding assays (LBAs), are routinely used for biomarker development and translation. LBAs offer high sensitivity and specificity for detecting low-abundance soluble analytes. These formats are particularly well-suited for quantifying circulating proteins, such as cytokines, receptors and growth factors, for understanding disease mechanisms and therapeutic responses. Some platforms for running these assays allow for protocol automation and very low sample input requirements.

One area of precision medicine that benefits from these features is liquid biopsy testing. As detection technologies continually evolve, integrating LBAs into liquid biopsy workflows not only improves assay precision but also enables multiplexing for comprehensive biomarker panels. Therefore, selecting the right analytical tools proves relevant for maximizing the potential of liquid biopsy in clinical practice and research applications. This type of testing is becoming an essential tool for monitoring cancer treatment efficacy, for alerting to disease recurrance³ or transplant rejection⁴. Unlike traditional tissue biopsies, liquid biopsies use minimally invasive, low-cost methods to analyze blood or biofluids.

These tests can detect primary cancerous cells, tumor-modified platelets, or circulating nucleic acids (ctDNA or ctRNA) released from malignant cells. Biomarkers gained from this sampling offer diagnostic and prognostic information in real-time, often with greater clinical utility than traditional protein tumor markers. Furthermore, extracellular vesicles isolated from liquid biopsies are investigated as mediators of cell-to-cell communication within the TME to understand resistance rates to immune therapy⁵. As standardization of sample collection and analytical workflows continues, test results can direct treatment selection as well. Though applicability is still limited, liquid biopsies hold promise for oncologists and are actively being explored in patients suffering from autoimmune and central nervous system disorders.

Addressing Assay Design Inefficiencies and Scaling Biomarker Research Efficiently

Inefficient assay designs can lead to inflated costs, prolonged turnaround times, and less reliable data. Following an iterative process optimization is crucial, but laborious and not always straightforward⁶. Poorly optimized assay designs go along with diminished reproducibility hampering method transfers to other laboratories and upscaling of operations. Additionally, traditional workflows often struggle with variability issues pertaining to, for example, staining intensity and poor signal-to-noise ratios. Automation platforms can mitigate these inefficiencies by standardizing staining protocols and optimizing reagent use. For example:

• Enhanced Sensitivity: Precise staining ensures clear differentiation of expression levels of biomarkers.
• Reproducibility: Automated workflows reduce variability across samples and experiments.
• Cost Efficiency: Streamlined reagent usage minimizes waste, particularly for expensive antibodies and rare samples.

Right-sized automation tailors solutions to the specific needs of laboratories, whether small research setups or large clinical facilities. Integrating scalable systems minimizes upfront costs and offers adaptability as laboratory demands grow. Researchers benefit from solutions that align with their workflow requirements without over-investment in unnecessary features. Therefore, a right-sized approach emphasizes:

• Cost Efficiency: Avoiding complex systems that inflate operational expenses.
• Scalability: Allowing laboratories to upgrade capabilities as their research evolves.
• Flexibility: Supporting diverse biomarker panels, from basic to highly multiplexed designs

Bioassay variance can be targeted through Design of Experiments (DoE) only for a single step during development (e.g. assessing robustness), or for a complete method establishment using the classical approach (SCOV/SCOR)⁷, which weighs on costs and capacities.
Though a common issue, variability can mean different challenges depending on the bioanalytical workflow. For flow and mass cytometry-based assays antibody cocktailing is a crucial experimental step. Recent innovations in automation for antibody master-mixing have led to:

• Reduced Reagent Wastage: Precise pipetting ensures minimal use of expensive reagents.
• Enhanced Consistency: Automation eliminates human error in manual cocktail preparation.
• Support for Complex Panels: High-dimensional multiplexing with accurate mixing of antibodies improves assay outcomes.

These approaches simplify manual pipetting routines by consolidating multiple antibodies into a single mix. Automation platforms focused on master-mixing address concerns on proper execution and ensure resources are used efficiently.

Global Standards and Quality Control

Since not every laboratory requires automation of the same type or degree, solutions should be as flexible as needed and limited to as few vendors as possible. Biomarker research reached an inflection point, driven by the dual imperatives of cost-efficiency and scalability. Laboratories striving to optimize their workflows aim to do so without sacrificing data quality or throughput. Launched in 2024, the Curiox Pluto C-Free technology tackles inefficiencies in cell-based assay designs while enabling precise, high-throughput analysis. Through partnering with end users each automation solution will be best tailored balancing standardization and customization.

As biomarker research becomes integral to clinical workflows, adherence to global standards such as CLSI and GCP is paramount. Right-sized concepts play a crucial role in maintaining quality control by ensuring:

• Consistent Reproducibility: Automated platforms reduce inter-user variability.
• Standardized Protocols: Predefined workflows streamline multi-site collaborations.
• Data Integrity: Built-in tracking features enhance compliance with regulatory guidelines.

Right-sizing automation introduces value-added platforms for biomarker discovery and fit-for-purpose validation. By optimizing existing processes and integrating scalable technologies, laboratories can achieve cost-efficiency and higher sample throughput without compromising data quality.

References:
1. Duffy, D J. Problems, challenges, and promises: Perspectives on precision medicine.
Briefings in Bioinformatics, 2016, 17(3):590-601. https://doi.org/10.1093/bib/bbv060

2. Carver, CM, Rodriguez, SL, Atkinson, EJ et al. IL-23R is a senescence-linked circulating and tissue biomarker of aging. Nat Aging, 2024. https://doi.org/10.1038/s43587-024-00752-7

3. Lone, SN, Nisar S, Masoodi, T. et al. Liquid biopsy: a step closer to transform diagnosis, prognosis and future of cancer treatments. Mol Cancer, 2022, 21:79. https://doi.org/10.1186/s12943-022-01543-7

4. Akifova A, Budde K, Oellrich M, Beck J, Bornemann-Kolatzki K, Schütz E, Osmanodja B. Perspective for Donor-Derived Cell-Free DNA in Antibody-Mediated Rejection After Kidney Transplantation: Defining Context of Use and Clinical Implications. Transpl Int, 2024, 37(11). https://doi.org/10.3389/ti.2024.13239

5. Asleh, K, Dery V., Taylor C. et al. Extracellular vesicle-based liquid biopsy biomarkers and their application in precision immuno-oncology. Biomark Res, 2023, 11:99. https://doi.org/10.1186/s40364-023-00540-2

6. Cronk, D, Oliver, T. Optimizing Assay Development. Biocompare, 2019. https://www.biocompare.com/Editorial-Articles/361409-Optimizing-Assay-Development/?utm_source=chatgpt.com

7. Solzin, J, Eppler K, Knapp B, Buchner H, Bluhmki E. Optimising cell-based bioassays via integrated design of experiments (ixDoE) - A practical guide. SLAS Discovery, 2023. 28(1):29-38. https://doi.org/10.1016/j.slasd.2022.10.004

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