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The term biomarker has been defined as “a characteristic that is measured and evaluated objectively as an indicator of normal biological processes pathogenic processes, or pharmacological response to a therapeutic intervention.” This definition was provided by the NIH Biomarkers Definition Working Group in 2001 in an attempt to provide a framework for discussion on what constitutes a biomarker. An alternative definition that takes a more pragmatic view of the drug discovery and development process was provided by Lathia in 2002. According to this definition, a “biomarker is a measurable property that reflects the mechanism of action of the molecule based on its pharmacology, pathophysiology of the disease, or an interaction between the two. A biomarker may or may not correlate perfectly with clinical efficacy/toxicity, but could be used for internal decision-making within a pharmaceutical company.” Both of these definitions encompass a wide range of methods and techniques that span the length of the drug discovery and development process.
Biomarkers are classified according to their use and the type of information provided, including target engagement biomarkers, mechanism biomarkers, outcome biomarkers, toxicity biomarkers, pharmacogenomics biomarkers, and diagnostic biomarkers.
As the name implies, target engagement biomarkers provide insight into whether or not a candidate compound is interacting with the macromolecular target of interest. This type of biomarker can be effectively used to validate or invalidate the relationship between a disease and a specific biomolecular target or explain why a compound fails to produce the expected result with a previously validated target. Consider, for example, a biomarker that definitively demonstrates that a candidate compound is interacting with a biomolecule that is hypothesized to be linked to the progression of a specific disease. If an in vivo response is also observed, then the biomarker has validated the link between the disease and the biomolecular target of interest. On the other hand, if the same candidate compound’s interaction with the targeted biomolecule fails to provide a physiological response, this suggests that the targeted biomolecule is not a suitable target for the treatment of the dis-ease or condition of interest.
Mechanism biomarkers provide information on the physiological impact of a candidate compound. They measure changes in specific events theorized to be associated with the targeted disease or condition that occurs as a result of target engagement. Exemplary physiological events that could be measured include changes in enzymatic activity, gene expression, protein expression, behavioral changes in the subject, or even plasma concentration of specific chemicals. Blood glucose levels, for example, are an established biomarker for candidate compound efficacy in the treatment of diabetes, while sleep induction is an easily detected indication of the efficacy of a candidate compound designed to treat insomnia. However, it is important to keep in mind that mechanism biomarkers are not necessarily tied to efficacy, especially if the link between the targeted mechanism and the disease/condition of interest has not been established.
Outcome biomarkers, on the other hand, are biomarkers with a defined link to the disease or condition of interest that can be used as an indication of compound candidate efficacy. In some cases, such as changes in viral load or CD4+ lymphocytes in HIV infection, biomarkers are biochemically assessed. There are, however, physiological outcomes, such as blood pressure reduction (cardiovascular disease) or sleep induction (insomnia) that can serve as outcome biomarkers. In many cases, there is an overlap between mechanism biomarkers and outcome biomarkers. It is also important to be aware that outcome biomarkers can also be used to screen out candidate compounds that have undesired side effects. A candidate compound designed to treat a migraine headache that also induces sleep or sedation may have limited commercial utility. The early application of an outcome biomarker to detect potential problems can be very effective in limiting the forward momentum of flawed candidate compounds.
Toxicity biomarkers are similar to outcome biomarkers, but as their name implies, these biomarkers are associated with negative outcomes. Data developed through the application of a toxicity biomarker are generally perceived to be a strong indication that the candidate compound has a serious flaw that must be considered before moving forward with further development efforts. QT prolongation and hERG channel blockade, for example, are well-known physiological and biochemical toxicity biomarkers associated with torsade de pointes and sudden cardiac death that are employed in almost every drug discovery and development program. Toxicity biomarkers that are associated with other forms of toxicity such as liver or kidney issues are also available, and their application early in a program via in vitro methods can provide an opportunity for a program to use medicinal chemistry tools to design out the toxicity. Identifying these kinds of issues before initiating advanced animal studies or human trials can be a very effective method of conserving resources and limiting patient exposure to potentially harmful candidate compounds.
Fig 1. Overview of toxicity biomarker discovery. (Kim, 2015)
Pharmacogenomic biomarkers are primarily used in clinical settings, and their main purpose is to provide an improved understanding of the target patient population, especially about predicting which patients are likely to respond. For example, a candidate compound that targets a specific variation of a biomolecule, such as a mutation that activates or eliminates a specific gene. Identifying patients with this particular mutation would increase the likelihood of demonstrating utility in a clinical trial. At the same time, patients without the desired trait (e.g., genetic mutation) would not be admitted into the clinical trials, as it would already be apparent that they would be unlikely to benefit from exposure to the candidate compound. In this manner, patient risk is limited, clinical trial sizes are diminished, and overall program costs are lowered.
Diagnostic biomarkers are also used primarily in the clinical setting, but can also be used in animal models where appropriate. This class of biomarkers can be used to identify patients that are at risk for developing a particular disease or condition, provide insight into disease progression or regression, and in some cases, identify patients before the clinical manifestation of symptoms or outwardly apparent physiological changes. Knowledge of this type can be used to simplify clinical measurements, ensure proper targeting of clinical trials, and even as a method of screening patients for entry into a clinical program. For example, the concentration of human chorionic gonadotropin can be used as a biomarker to gate the admission of women into clinical trials. This particular biomarker is almost certainly the most widely recognized biochemical diagnostic biomarker, although it is not recognized widely by this name. This particular diagnostic biomarker is more widely recognized as the diagnostic component of over-the-counter pregnancy tests and is capable of establishing pregnancy at a very early stage. Screening of female clinical trial participants using this diagnostic biomarker is a very effective method of limiting the likelihood that a pregnant woman and her unborn child might be exposed to a candidate compound with an unknown safety profile.
Fig 2. Current diagnostic biomarkers. (Meunier, 2019)
Creative Biolabs provides a comprehensive suite of customized Drug Discovery services in a timely and cost-effective manner to satisfy your specific needs. Whether you have any questions about our services or biomarkers, please contact us and we will provide you with a detailed explanation.
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