How to Develop Assays to Measure Biomarkers

What Is a Biomarker?

Before measuring biomarkers, it is critical to understand what qualifies as a biomarker. The National Institute of Environmental Health Sciences (NIEHS), a subset of the National Institutes of Health (NIH), defines a biomarker as an “objective measure that captures what is happening in a cell or an organism at a given moment.”

Although the term biomarker often causes people to look for complex molecular components, such as gene variation during genomic sequencing, that can indicate disease, a biomarker can be any simple measurement. For example, high cholesterol detected in routine lab tests can be a biomarker for heart disease. Other examples of biomarkers include blood pressure and body weight.

While many biomarkers are simple quantitative measurements, others focus on molecular or cellular indications by analyzing genes or proteins. According to the NIEHS, biomarkers can provide insight into biological processes and inform medical and public health protocols.

The organization supports biomarker development that measures environmental exposure, biological responses to exposures, and susceptibility. The NIEHS has four primary goals when it comes to biomarker development:

• To identify and validate biomarkers that can be used to study environmental exposures and diseases.
• To develop biomarkers that provide insight into the connections between environmental exposures and biological processes
• To classify biomarker subgroups
• To discover biomarkers that explain why patient outcomes may vary

Biomarker in Drug Development

The United States Food and Drug Administration (FDA) notes that biomarkers play an integral role in drug development, as they are used to measure the impacts of drugs during clinical trials. Clinical researchers and regulatory organizations assess the role of investigational new drugs by evaluating how they impact biomarkers. Clinical studies often monitor biomarker changes as clinical endpoints.

However, researchers in Nature Reviews Neurology are careful to note that biomarkers differ from endpoints and clinical outcome assessments, saying, “An endpoint is a precisely defined variable designed to indicate an outcome of interest that is statistically analyzed to address a particular research question. A clinical outcome assessment is an evaluation of how an individual feels, functions, or survives.”

Beyond the implications of biomarkers in bioanalysis for drug development, biomarker research may also enhance precision medicine as researchers work backward from biomarkers that indicate disease. For example, many new oncology treatments have been discovered based on cancer biomarkers. Although the initial intended use of said biomarker may have been diagnostic, these measurements can provide researchers a starting point or benchmark during drug discovery and development.

Qualified Biomarkers

Although many measurements could be considered biomarkers for drug development and discovery, researchers must focus on qualified biomarkers.

Qualified biomarkers can be critical tools in the drug development process. According to the FDA, “When a biomarker is qualified, it means that it has undergone a formal regulatory process to ensure that we can rely on it to have a specific interpretation and application in medical product development and regulatory review within the stated context of use (COU). It is important to note that a biomarker is qualified, and not the biomarker measurement method.”

Biomarker qualification goes through the Biomarker Qualification Program, where the FDA collaborates with requestors or other interested parties to qualify biomarkers under the 21st Century Cures Act.

There are four primary parts of the biomarker qualification, including the following.

1. Letter of intent (LOI): interested parties will send in an LOI to initiate the qualification process for a certain COU in drug development. A letter of intent should include what the biomarker is meant to address, the biomarker information, COU, and how the biomarker will be measured. Upon receiving the LOI, the FDA will assess the LOI, and if it is accepted, the requestor will submit a qualification plan.
2. Qualification plan (QP): A QP provides insight into the biomarker development plan, including COU data, information on knowledge gaps, and ways to address these gaps. The QP is a precursor to the complete qualification package.
3. Full qualification package (FQP): If the QP is approved, the requestor will submit an FQP, a comprehensive compilation supporting biomarker qualification.
4. Qualification recommendation: the FDA will determine whether or not to qualify the biomarker after a comprehensive review of the FQP.

Steps for Biomarker Assay Development

Although the FDA does not approve biomarker measurement protocols, effective qualification packages incorporate accurate and validated biomarker tools. As a result, there is significant value in developing, validating, and continually improving biomarker assays.

Step 1: Defining Biomarkers and Purpose

Biomarker discovery and development can be a challenging endeavor that needs to be validated. The primary steps in defining a biomarker include the initial biomarker identification and preliminary proof-of-concept studies.

The FDA notes there are seven categories of biomarkers, including susceptibility or risk, diagnostic, monitoring, prognostic, predictive, pharmacodynamic or response, and safety biomarkers. The Biomarker Endpoints and Other Tools (BEST) glossary includes biomarker descriptions with the biomarker name, source/matrix, measurable characteristics, and analytic methods to measure it.

• Susceptibility or risk biomarkers: These biomarkers assess a patient’s risk of getting a disease or condition in patients without any clinical manifestations of the target disease.
• Diagnostic biomarkers: These biomarkers are used to detect the disease or condition.
• Monitoring biomarkers: Monitoring biomarkers may be used to track disease progression and often overlap with other biomarker types.
• Prognostic biomarker: Prognostic biomarkers are measurements in patients with a disease diagnosis that can analyze the probability of a particular clinical event, disease recurrence, or disease progression.
• Predictive biomarkers: According to an article in Experimental Biology and Medicine, “A predictive biomarker is defined by the finding that the presence or change in the biomarker predicts an individual or group of individuals more likely to experience a favorable or unfavorable effect from the exposure to a medical product or environmental agent.”
• Pharmacodynamic or response biomarkers: Pharmacodynamic or response biomarkers measure a change in response to a therapy or environmental exposure.
• Safety biomarkers: Safety biomarkers measure the probability that a medical intervention may lead to an adverse event and the extent of the adverse event.

When defining a biomarker, it is crucial to consider its biological and clinical significance. For example, researchers may consider the biomarker’s role in physiology, its disease associations, and the potential of using it as a diagnostic or prognostic indicator.

Beyond defining a biomarker in clinical research and drug development, it is critical to understand how a biomarker connects to research or diagnostic goals. For example, would the new biomarker provide disease insight, diagnose a condition, monitor disease progression, and evaluate treatment response?

The biological significance and research or diagnostic goals can help contextualize a biomarker's role in healthcare. Context helps researchers, providers, and regulatory agencies understand how the measurement of this biomarker contributes to the overall objectives of a project or clinical practice.

Another factor to consider is how the identification and quantification of a biomarker may impact the patient population. It is vital to assess the relevance of biomarkers to patient outcomes, treatment decision-making, patient prognosis, and healthcare management.

Finally, the early stages of biomarker development should analyze how sample collection and biomarker data can have ethical and regulatory implications.

Step 2: Selecting Assay Type

Once a biomarker has been identified, researchers can begin assay development, which depends on the biomarker properties or type of analyte. Biomarkers can be proteins, nucleic acids, metabolites, or other molecules. Biomarker characterization is the first step in determining the appropriate assay.

In the early stages of biomarker strategy, studies focus on the accuracy and reliability of detection methods and hypothesizing the COU. According to a 2022 publication in the American Association of Pharmaceutical Scientists Open, COU impacts the type of assay and its validation plan.

Other factors to consider when selecting an assay type include assay sensitivity and specificity throughput and scalability, the available resources, available existing protocols, historical success and validation history, cost, time, and potential regulatory implications.

Step 3: Designing Reagents and Probes

Another critical step in biomarker assay development is designing the appropriate reagents or probes. For protein-based biomarkers, the primary goal is to select the proper antibody with a high affinity for the target biomarker. Probes or primers that bind to specific sequences are developed for nucleic acid biomarkers.

When designing reagents and probes, researchers must consider cross-reactivity and how that will impact test results. As reagent and probe specificity improves, testing accuracy is more likely. Enhancing the specificity and sensitivity of a particular probe requires researchers to optimize binding affinity.

Other factors to consider when designing a reagent or probe for biomarker assays include conjugation for detection, blocking agents or non-specific binding, sample optimization, and reagent validation.

Researchers and clinical developers should look at commercially available and validated reagents during this process. Those reagents or probes can save time during the research process.

Step 4: Optimization and Validation

There are multiple steps in biomarker assay validation, including analytical and clinical validation. According to an article published in Nature Reviews Neurology, “Analytical validation involves rigorous testing of the performance characteristics of the assay or detection technology in a manner that is appropriate for the purpose of the biomarker or biomarker signature.”

Researchers analyze precision, dynamic range, and assay sensitivity during the analytical validation process. More specifically, optimizing assay parameters, such as reagent concentrations, incubation times, temperatures, and pH, is done at this step. Additionally, sensitivity and specificity testing is critical at this stage of the biomarker assay development process.

Meanwhile, clinical validation examines the sensitivity and specificity of a biomarker in predicting a clinical outcome. Researchers should take time during the clinical validation phase to assess the limit of detection, the limit of quantification, reproducibility, and assay precision. They should also validate with known samples and compare the assay with the established standards.

Step 5: Documentation and Improving

The final step of developing biomarker assays is a dynamic and continual step involving documenting and improving the protocols. Once a process has been optimized and validated through documentation of the entire assay, including sample preparation, reagent concentrations, incubation times, and detection methods, it is critical to ensure the process is reproducible. Additionally, researchers are advised to document results, including raw data, calibration curves, controls, and more.

These documents can be used to develop standard operating procedures.

Aside from documenting the existing protocols, those developing the assays should continuously monitor the assay performance and make improvements based on feedback, collaboration, and newly available technologies.