What is a biomarker?
“any substance, structure, or process that can be measured in the body or its products and influence or predict the incidence of outcome or disease” — International Program on Chemical Safety (WHO), World Health Organization official definition, international authority on chemical safety and biomarkers
Biomarkers can take multiple forms, including molecular, histologic, radiographic, or physiologic characteristics [1]. They are typically measured in blood, urine, or tissues [3], although some biomarkers come from routine measurements taken at a doctor’s visit, such as blood pressure or body weight [3]. At the molecular level, biomarkers can be found in genes and proteins [3], while others manifest as specific cells, molecules, enzymes, or hormones [3].
For a biomarker to be considered reliable and valuable in clinical settings, it must possess several essential characteristics. A good biomarker demonstrates high sensitivity (ability to accurately detect true positives) and specificity (ability to accurately detect true negatives), minimizing both false negatives and false positives [4]. Additionally, reproducibility is vital, ensuring consistent results across different tests, various laboratories, and over time [4].
Other important attributes include easy measurement, even in small quantities; ideally using non-invasive or minimally invasive collection methods [4]. Cost-effectiveness increases accessibility, particularly in resource-limited settings [4]. Furthermore, effective biomarkers should correlate well with disease severity, reflect changes in response to treatment, and ideally provide sufficient lead time for early intervention before symptoms appear [4].
The concept of biomarkers has evolved significantly over time. The term ‘biological marker’ was introduced in the 1950s [5]. In 1998, the National Institutes of Health Biomarkers Definitions Working Group established one of the most widely accepted definitions, describing a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” [2].
Biomarkers serve distinct purposes across medicine and research. They help detect early-stage diseases, diagnose health conditions, predict disease progression, monitor responses to treatment, and determine appropriate therapeutic approaches [3]. Moreover, biomarkers play crucial roles in drug development, assessment of environmental exposures, and advancing personalized medicine.
Types of biomarkers
Biomarkers can be categorized into distinct types based on their clinical applications. The Food and Drug Administration’s Biomarker Qualification Program identifies seven major categories of biomarkers [6].
Diagnostic biomarkers
Diagnostic biomarkers detect or confirm the presence of a disease or condition, or identify individuals with a specific disease subtype. These biomarkers help determine diseases such as cardiac troponin for cardiac muscle injury diagnosis or glutamate for visceral obesity and altered metabolism [7].
Diagnostic biomarkers frequently represent patient characteristics, including molecular changes related to somatic and germline DNA, receptor proteins, or HLA type [2]. As precision medicine advances, diagnostic biomarkers increasingly drive molecular-based disease classification rather than purely organ-based classification schemes [3].
Monitoring biomarkers
Monitoring biomarkers are measured repeatedly to assess disease status, progression, or response to treatment [7]. These biomarkers track health conditions by screening and measuring internal precursors that may indicate disease development [7].
When assessed serially, monitoring biomarkers can detect signs of disease worsening, which might indicate deteriorating prognosis or need for intervention [7]. Furthermore, monitoring biomarkers are used throughout medical product development, particularly in therapeutic or prevention trials of new drugs, biologics, or devices [7].
Pharmacodynamic/response biomarkers
Pharmacodynamic/response biomarkers indicate biologic responses to a medical product or environmental agent [8]. PD biomarkers are indicators of a drug’s pharmacological effect on its target or targets [9]. For instance, changes in proteins along a signaling cascade could be considered pharmacodynamic responses [9].
Recent advances in proteomic technologies allow developers to simultaneously study changes in thousands of proteins after drug administration, revolutionizing biomarker research [9]. Importantly, correlation between the PD biomarker and clinical outcomes, while beneficial, is not necessary for biosimilar development [9].
Predictive biomarkers
Predictive biomarkers identify individuals more likely to experience favorable or unfavorable effects from exposure to a medical product or environmental agent [4]. These biomarkers are essential for personalizing treatment by selecting patients most likely to benefit from specific therapies [4]. For example, certain genotypes for the Serotonin Transporter gene are associated with different outcomes to treatments with psychiatric medicines [10].
Predictive biomarkers require rigorous validation through clinical studies where patients with or without the biomarker are randomized to different treatments to demonstrate their predictive value [3].
Prognostic biomarkers
Prognostic biomarkers indicate the likelihood of clinical events, disease recurrence, or progression in patients who already have the disease [11]. Unlike predictive biomarkers, prognostic biomarkers forecast outcomes independent of specific treatments [12]. Common examples include BRCA1/2 mutations in breast cancer patients to assess the likelihood of a second breast cancer [11].
Clinical trials often use prognostic biomarkers as eligibility criteria to identify patients more likely to have disease progression, thereby increasing statistical power [11].
Safety biomarkers
Safety biomarkers measure potential toxicity before or after exposure to medical products or environmental agents [6]. These biomarkers help identify adverse effects from treatments, consequently allowing dose modification or interruption before toxicity becomes severe [6]. Examples include hepatic aminotransferases and bilirubin for evaluating potential hepatotoxicity, and serum creatinine for monitoring nephrotoxicity [6].
Susceptibility/risk biomarkers
Susceptibility/risk biomarkers indicate potential for developing a disease in individuals without current clinical disease [3]. Unlike prognostic biomarkers used after disease diagnosis, susceptibility biomarkers identify healthy individuals with increased disease likelihood [3]. Examples include BRCA1/2 mutations for breast cancer predisposition and Factor V Leiden for deep vein thrombosis risk [3]. Their primary utility lies in guiding preventive strategies and determining whether lifestyle or other preventive interventions are indicated [3].
How biomarkers are used in clinical research
“Biomarkers play an important role in illuminating relationships among environmental exposures, human biology, and disease.” — National Institute of Environmental Health Sciences, U.S. government health agency, authority on biomarker applications
Biomarkers as surrogate endpoints
Surrogate endpoints are biomarkers used instead of clinical outcomes in clinical trials where the actual outcomes might take considerable time to study [2]. They function as substitutes for direct clinical outcomes, often expediting research and decision-making processes [14]. For instance, hemoglobin A1c serves as a validated surrogate endpoint for diabetes-related microvascular complications, while reduced HIV-RNA levels indicate HIV disease control [15]. Between 2010 and 2012, the FDA approved 45% of new drugs based on surrogate endpoints [2]. Their implementation typically allows clinical studies to proceed with smaller participant groups over shorter periods [2].
Role in drug development
Throughout drug development, biomarkers help identify molecular pathways contributing to disease, determine mechanisms of action, and assist with dose selection [16]. During preclinical development, they support safety assessments and dose determination [16].
Biomarker-based strategies enable a more biology-targeted approach to drug development, potentially yielding time and cost savings through leaner, more focused clinical trials with higher probabilities of success regarding both efficacy and safety [16]. Recent analysis indicates trials employing biomarker preselection demonstrate a two-fold higher likelihood of approval, with nearly 50% Phase 2 success rates [17].
Use in early-phase trials
In early-phase clinical trials, biomarkers offer valuable insights into target engagement, monitor pharmacodynamic responses, and inform dose-exposure-response relationships [18]. Although fully validated biomarker tests may not be feasible in early phase settings, several factors warrant consideration when determining readiness for trial inclusion [13]. Early-phase trials commonly employ biomarkers for target validation, compound screening, pharmacodynamic studies, and as surrogate endpoints [13]. Specifically, biomarkers can be monitored to determine optimal dosing based on physiological responses rather than focusing solely on detecting adverse effects [15].
How biomarkers are evaluated and validated
Evaluating and validating biomarkers requires rigorous methodologies to ensure reliability across various applications. The process typically encompasses three interconnected components: analytical validation, clinical qualification, and context of use determination.
Analytical validation
Analytical validation assesses test performance characteristics to ensure reproducible and accurate data [7]. This phase examines whether the method measures the intended analyte, the variability of measurements, and the reliable measurement range [7]. Key parameters include accuracy, precision, sensitivity, selectivity, reproducibility, and stability [7]. For biomarker assays supporting regulatory decisions, full validation according to industry standards becomes necessary [7].
Clinical qualification
Clinical qualification involves systematic evidence evaluation linking the biomarker to clinical outcomes. This step requires evaluating evidence about whether the biomarker exists on a causal disease pathway and gathering data showing that interventions targeting the biomarker impact clinical endpoints [19]. The process uses probabilistic reasoning rather than deterministic reasoning, acknowledging that all contributing factors may not be fully understood [19].
Context of use
Context of use (COU) is a concise description of a biomarker’s specified application in drug development [20]. It combines the biomarker category and its intended use [20]. Defining COU involves articulating populations and conditions applicable to the assessment [19]. This framework ensures biomarkers undergo evaluation on a fit-for-purpose basis as knowledge evolves [19]. Regulatory agencies like FDA evaluate biomarkers differently depending on COU—a biomarker proposed as a surrogate endpoint undergoes intense scrutiny, whereas exploratory biomarkers face less rigorous evaluation [9].
The future of biomarkers in medicine
The future of biomarkers extends beyond traditional laboratory measurements into emerging technologies and methodologies that enhance diagnostic precision and treatment personalization.
Digital biomarkers
Digital biomarkers are consumer-generated physiological and behavioral measures collected through connected digital tools such as wearables, smartphones, and sensors [8]. These novel indicators offer continuous monitoring outside clinical settings with high temporal resolution [21]. Digital biomarkers typically measure physiological parameters (heart rate, blood pressure), behavioral patterns, or digital activities [22]. They enable passive data collection in patients’ natural environments, subsequently providing more accurate representations of day-to-day health status [8]. Currently, digital biomarkers have applications in cardiology, oncology, and neurology where traditional assessment methods face limitations [21].
Composite and complex biomarkers
Composite biomarkers combine multiple measurements into integrated signatures, offering greater sensitivity in tracking disease progression [23]. By merging several biomarker types, these multi-dimensional indicators provide more comprehensive understanding of disease pathology [23]. Research demonstrates that composite biomarkers often perform better than single biomarker assessments in conditions like chronic fatigue syndrome and major depression [23]. Essentially, they reflect the complex, heterogeneous nature of many diseases through non-linear combinations of multiple measurements [24].
Systems biology and AI integration
Artificial intelligence transforms biomarker identification by analyzing complex multi-omics datasets [4]. Machine learning algorithms help identify patterns in vast amounts of data that would be impossible to discern manually [25]. AI integration enables better correlation between visual patterns and molecular alterations, improving diagnostic accuracy and prognostic predictions [4]. Furthermore, deep learning models can predict spatial gene expression from histopathology slides with high accuracy [26]. The combination of AI with systems biology approaches allows researchers to move beyond single-biomarker strategies toward comprehensive analysis of entire biological pathways [4].
Key Takeaways
Understanding biomarkers is essential for anyone involved in healthcare, research, or personalized medicine, as these biological indicators are revolutionizing how we diagnose, treat, and prevent diseases.
• Biomarkers are measurable biological characteristics that indicate normal processes, diseases, or treatment responses – from simple blood pressure readings to complex genetic mutations.
• Seven distinct biomarker types serve specific purposes: diagnostic (detect disease), monitoring (track progression), predictive (identify treatment responders), prognostic (forecast outcomes), pharmacodynamic (measure drug effects), safety (detect toxicity), and susceptibility (assess disease risk).
• Rigorous validation through analytical testing, clinical qualification, and context-of-use definition ensures biomarkers provide reliable, reproducible results for clinical decision-making.
• Digital biomarkers from wearables and AI-powered composite biomarkers represent the future, enabling continuous monitoring and more precise disease understanding through multi-dimensional data analysis.
• Clinical trials using biomarker-guided patient selection show twice the approval success rate, demonstrating their power to accelerate drug development and improve treatment outcomes.
The integration of traditional biomarkers with emerging digital technologies and artificial intelligence is creating unprecedented opportunities for early disease detection, personalized treatment strategies, and improved patient outcomes across all areas of medicine.
FAQs
Q1. What exactly is a biomarker and why is it important? A biomarker is a measurable biological characteristic that indicates normal processes, diseases, or responses to treatments. It can be anything from simple measurements like blood pressure to complex genetic mutations. Biomarkers are crucial in healthcare for early disease detection, diagnosis, monitoring treatment responses, and developing personalized medicine approaches.
Q2. What are the main types of biomarkers used in medicine? There are seven primary types of biomarkers: diagnostic (for detecting diseases), monitoring (for tracking disease progression), predictive (for identifying treatment responders), prognostic (for forecasting outcomes), pharmacodynamic (for measuring drug effects), safety (for detecting toxicity), and susceptibility (for assessing disease risk).
Q3. How are biomarkers validated for clinical use? Biomarkers undergo a rigorous validation process that includes analytical validation (ensuring accurate and reproducible measurements), clinical qualification (linking the biomarker to clinical outcomes), and context of use determination (specifying the biomarker’s application in drug development or clinical practice).
Q4. What role do biomarkers play in clinical trials? In clinical trials, biomarkers are used to determine patient eligibility, assess primary endpoints, and serve as stratification factors. They can act as surrogate endpoints, potentially expediting research and decision-making processes. Trials using biomarker-guided patient selection have shown higher success rates in drug approvals.
Q5. What does the future hold for biomarkers in medicine? The future of biomarkers is moving towards digital biomarkers collected through wearables and smartphones, composite biomarkers that combine multiple measurements, and the integration of artificial intelligence for analyzing complex datasets. These advancements promise more precise disease understanding, continuous health monitoring, and improved personalized treatment strategies.
References
[1] – https://www.fda.gov/drugs/biomarker-qualification-program/about-biomarkers-and-qualification
[2] – https://www.fda.gov/about-fda/innovation-fda/fda-facts-biomarkers-and-surrogate-endpoints
[3] – https://www.ncbi.nlm.nih.gov/books/NBK402288/
[4] – https://pmc.ncbi.nlm.nih.gov/articles/PMC11906928/
[5] – https://en.wikipedia.org/wiki/Biomarker
[6] – https://www.ncbi.nlm.nih.gov/books/NBK402287/
[7] – https://www.hhs.gov/guidance/sites/default/files/hhs-guidance-documents/FDA/biomarkers-guidance-level-2.pdf
[8] – https://www.nature.com/articles/s41746-024-01023-w
[9] – https://www.tandfonline.com/doi/full/10.4155/bio-2023-0110
[10] – https://nanostring.com/blog/what-can-biomarkers-tell-us/
[11] – https://www.ncbi.nlm.nih.gov/books/NBK402289/
[12] – https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05143-0
[13] – https://pmc.ncbi.nlm.nih.gov/articles/PMC6123886/
[14] – https://www.jclinepi.com/article/S0895-4356(23)00340-2/fulltext
[15] – https://www.drugtargetreview.com/article/158249/the-rising-impact-of-biomarkers-in-early-clinical-development/
[16] – https://www.fda.gov/drugs/biomarker-qualification-program/biomarker-qualification-program-educational-module-series-module-2-how-biomarkers-can-improve-drug
[17] – https://www.precisionformedicine.com/blog/how-biomarkers-impact-clinical-trial-study-start-up/
[18] – https://www.worldwide.com/insights/how-biomarkers-transform-early-phase-clinical-trials/
[19] – https://www.ncbi.nlm.nih.gov/books/NBK220290/
[20] – https://www.fda.gov/drugs/biomarker-qualification-program/context-use
[21] – https://pmc.ncbi.nlm.nih.gov/articles/PMC11015196/
[22] – https://www.roche.com/stories/digital-biomarkers-in-personalized-healthcare
[23] – https://www.nature.com/articles/s41598-025-01047-6
[24] – https://pmc.ncbi.nlm.nih.gov/articles/PMC8521973/
[25] – https://rapm.bmj.com/content/50/2/110
[26] – https://www.technologynetworks.com/proteomics/articles/advances-in-biomarker-discovery-and-analysis-398108
Disclaimer
The information in this article is for general educational purposes only. It does not provide medical advice, diagnosis, or treatment. Always consult a licensed clinician before making decisions about testing, interpreting biomarkers, or starting any health program. Biomarkers require qualified clinical evaluation and should never replace a full medical assessment. HolistiCare does not claim to diagnose or treat medical conditions.
