Bioanalysis Zone

Biomarkers: discovery, development and assay validation


Biomarkers are increasingly being used to improve patient diagnosis and monitor therapeutic responses. Through using biomarkers, physicians can prescribe more effective treatments. During biomarker discovery ideal candidates – that are related to a disease or treatment mechanism – are monitored and measured from accessible samples such as body fluids. 

Keywords: biomarkers, cancer biomarkers, assay development, biomarker identification, biomarker candidates, biomarker discovery, biomarker validation

The importance of biomarkers

A biomarker is defined as a characteristic that can be objectively evaluated and measured as an indicator of either: a normal biological process, a pathogenic process or a pharmacologic response to a therapeutic [1]. Biomarkers are currently used to determine disease onset, progression and treatment efficacy. Protein biomarkers can be analyzed using a wide range of instrumentation and can be quantified from complex biological samples [2]. These complex biological samples include blood, urine, tissues and other body fluids. Biomarkers are increasingly being used to improve diagnosis, aid targeted molecular therapy and monitor a therapeutic response. Biomarkers are particularly important in the pharmaceutical industry to evaluate the safety and effectiveness of a drug and could also benefit the cost reduction of drug development by enabling early proof-of-concept studies for novel therapeutic targets, thus reducing costly drug attrition rates. Through using biomarkers, scientists and physicians can make more precise diagnoses and prescribe more effective and personalized treatments [3].

Personalized medicine and biomarkers

Over recent years there has been an increased focus on personalized medicine, with biomarkers being used commercially to discover new potential drugs, which can then be developed to enable patient treatments [1]. The use of personalized medicine has also had a big impact on the clinical management of individuals with cancer. It is believed that biomarkers hold real promise for advancing the way we treat certain diseases, in particular, cancer. A cancer biomarker can monitor an individual’s risk of developing cancer in a specific tissue or measure cancerous progression. It can also measure an individual’s response to treatment. Single or multiple gene ‘signature’ based assays have been used to measure specific molecular pathway deregulations that can be used as predictive biomarkers and help guide therapeutic treatment decisions. Furthermore, cancer biomarkers have also been used in clinical prognostic staging, enabling physicians to identify the severity of a disease. However, there is a gap between initial biomarker discovery in the laboratory and translating these findings into using biomarkers in a clinical setting [4].

Biomarker research and discovery

Drug development programs undertaken by pharmaceutical and biotechnology companies are very complex and costly. During biomarker discovery ideal candidates – that are related to a disease or treatment mechanism – are monitored and measured from accessible samples such as body fluids. Biomarker discovery starts with defining a target ‘normal’ biological process, pathogenic process or pharmacological response that the biomarker could highlight. As part of this process multiple candidates will be identified. Each candidate needs to be validated before it can progress into clinical studies. This involves assay development – requiring the assay to be sensitive and selective for monitoring specific candidate biomarkers [5].

In overview, the steps of biomarker development include: biomarker discovery, assay development and validation, clinical utility validation and clinical implementation [4]. Biomarker discovery and development is a lengthy process requiring hypothesis generation, sample collection, data collection, data analysis, assay development, assay validation and finally regulatory approval before it can be used clinically [6].

The lack of well-established validation methods for candidate biomarkers is a key challenge of biomarker discovery. A method that could help overcome this issue, is the use of affinity proteomics, which uses a pre-qualified antibody pool that is applied to the screening process as well as the verification and validation stages [7].

Technologies used for biomarker discovery

There are a plethora of technologies and methodologies that have been applied to study and discover biomarkers including: mass spectrometry, proteomic and epigenetic methods. High-throughput omics technologies allow thousands of individual molecules to be interrogated, enabling the identification of molecular markers for certain diseases. These datasets, however, are very complex and it is important to extract meaningful molecular signatures of biological processes [5].

Proteomic methods, based on mass spectrometry techniques, are also being used to identify novel biomarkers. Once identified, it is important to validate the method and technology to allow candidate discovery to move on to clinical validation and then commercialization [3].

Other technologies used in biomarker discovery include in vitro analyses of DNA/RNA expression, protein expression and metabolite quantification. Morphological and functional imaging technologies can also be used to take in vivo measurements of biological processes. Different methods can generate vast amounts of data, but it is important that scientists identify significant measurements that correlate to a clinically relevant endpoint (such as therapeutic response or prognosis of disease state).

Metabolomics, proteomics and epigenetics are all strategies that are used to discover biomarkers. Metabolomics refers to the study of changing metabolite levels over time in response to a stimulus – for example a drug or disease. For cancer, metabolic research aims to identify metabolic markers of a disease and tumor-specific pathways that could be used as druggable targets. Proteomics involves monitoring proteins of an organism or cellular system. Therapies can target a specific protein product associated with a cellular signalling pathway. In general, protein biomarkers are analyzed using assays such as fluorescent in situ hybridization (FISH), enzyme-linked immunosorbent assay (ELISA) and western blot. Lastly, epigenetics refers to the study of functional changes to DNA, for example methylation. In regard to cancer, methylation losses and gains happen simultaneously across the cancer genome, for example, some epigenetic changes turn off tumor suppressor genes and others change to maintain the genes that drive cancer growth [6].


Biomarker discovery and development is being enhanced by the use of new and complex technologies, giving hope that more clinical applications of biomarkers will be used to improve diagnosis, prognosis and disease monitoring. However, improvements can always be made to enhance biomarker discovery automation and validation for clinical use. Approval by regulatory agencies such as the FDA and EMEA of diagnostic tests based on the validated biomarker should always be at the forefront when making decisions [8]. Looking forward, it is important that identified biomarkers are propelled from the research setting into clinical use and to increase this more collaboration is required between scientists and policy makers.

  1. Fidock M, DeSilva B. Bioanalysis of biomarkers for drug development. Bioanalysis, 4(20), 2425–2426 (2012).
  2. European Pharmaceutical Review. Discovery and validation of protein biomarkers [Accessed on 25 March 2020]
  3. Proteome Sciences. Measuring proteins for better medicines [Accessed on 25 March 2020]
  4. Goossens N, Nakagawa S, Sun X, Hoshida Y. Cancer biomarker discovery and validation. Cancer Res. 4(3) 256–269 (2015).
  5. Rifai N, Gillette MA, Carr SA. Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nat Biotechnol.24, 971–983 (2006).
  6. Technologies behind biomarker discovery and development. [Accessed on 25 March 2020]
  7. McDermott JE, Wang J, Mitchell H et al. Challenges in biomarker discovery: combining expert insights with statistical analysis of complex omics data. Expert Opin. Med. Diagn. 7(1) 37–51 (2013).
  8. Scaros O, Fisler R. Biomarker technology roundup: from discovery to clinical applications, a broad set of tools is required to translate from the lab to the clinic. Biotechniques, 38(S30–S32) (2005).



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