A biomarker is a molecular, cellular, or biochemical change that can be precisely and repeatedly detected. Biomarker validation recognizes and tracks pathological and physiological processes and responses to therapeutic therapies.
So we can conclude from this that in addition to aiding in disease detection (diagnostic biomarkers), biomarker testing can be used to track disease development, regression, and outcomes following an intervention. Test biomarkers can be any substance that aids in diagnosing a condition, including metabolites, modifications to biological processes or structures, or distinguishing characteristics. Genes, DNA, RNA, platelets, enzymes, hormones, and other biomolecules like carbohydrates, proteins, and lipids are examples of biomarkers.. Best biomarker assay platforms should be used to test the assays.
There are numerous ways to categorize biomarkers.
The process of drug development is a massive undertaking
As much as 90% of new treatments fail during development and clinical testing, and these failure rates can even be higher for some disorders like Alzheimer’s.
Finding reliable biomarkers can help with drug discovery and possibly improve success rates.
Let us examine the significance of biomarkers in drug discovery and development in more detail.
Types Of Biomarkers
There are several categories in which biomarkers can be grouped.
It is essential to take this possibility of several forms for biomarkers with a grain of salt.
In the case of sporadic epithelial ovarian cancer, BRCA1 expression serves as both a prognostic and predictive biomarker for the response to chemotherapy.
Biomarkers of Type 0, Type 1, and Type 2
Biomarkers can be categorized in the following ways using genetic and molecular biology techniques.
Biomarkers of Type 0
They are likewise referred to as natural history biomarkers.
These biomarkers help track a disease’s development and develop a long-term relationship with recognized clinical signs.
A type 0 biomarker measures serum creatinine.
Biomarkers of Type 1
These biomarkers in the process of drug development show the impact of therapeutic intervention.
Examples of type 1 biomarkers are cytokines (mechanism biomarker) in autoimmune disorders like rheumatoid arthritis and blood glucose levels (efficacy biomarker) to track the effects of insulin therapy.
Biomarkers of type 2
These are surrogate indicators, sometimes referred to as surrogate endpoints, which stand-in for a disease’s clinical outcome and aid in predicting the result of a therapeutic intervention.
Although there may be a correlation between these indicators and clinical outcomes, it may not always be the case.
Since there are cases of heart disease with low cholesterol levels and some patients do not develop heart disease despite high cholesterol levels, cholesterol is an example of a Type 2 biomarker, where elevated levels are correlated with an increased risk of heart disease, but the relationship is not always present.
Prognostic, Predictive, Pharmacodynamic, and Surrogate Endpoint Biomarkers
Another classification of biomarkers groups them into the following four categories:
- Prognostic.
- Predictive.
- Pharmacodynamic.
- Surrogate endpoint
Biomarkers for prognosis
Greek for prognostic is “fore-knowing or foreseeing.” The biomarkers that predict a disease’s prognosis in an untreated person are known as prognostic biomarkers.
It has been discovered that people with mutant PIK3CA had worse odds of disease-free survival in cases of metastatic breast cancer that is HER-2 positive. It is an example of a prognostic biomarker.
Predictive Biomarkers
We use predictive biomarkers to identify patients most likely to respond favorably to a particular treatment. So it is possible to administer a specific therapy to the patients for whom it is most likely to help with predictive biomarkers.
The therapeutic approach used to treat advanced non-small-cell lung cancer is erlotinib maintenance therapy. Progression-free survival after erlotinib treatment is considerably poorer in individuals with an EGFR mutation in the tumor than in non-tumor patients with an EGFR mutation. As a result, the EGFR mutation status is a biomarker that predicts how well a patient will respond to erlotinib therapy.
Pharmacodynamic Biomarkers
These Biomarkers aid in determining a drug’s pharmacological effects and can reveal whether a treatment is having the desired impact or not.
Several malignancies use PI3K inhibitors. Numerous downstream targets of the PI3K signaling pathway, including AKT.
Surrogate Biomarkers
See above for more information on surrogate biomarkers, which are indeed type 2 biomarkers in all respects but name. Blood pressure is another illustration of a substitute biomarker for heart illness.
Surrogate indicators must accurately mimic clinical outcomes to be helpful, and changes to the substitute must forecast changes in clinical results.
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