Biomarkers

by www.big-data.tips · Published April 28, 2019 · Updated April 19, 2021

🔬 Biomarkers stand for any measurable quantity of big data or score that is used to stratify patients. In other words, stratifying patients mean in this context to arrange or classify them into well-defined risk groups. Examples of biomarkers are genomic alterations, molecular markers, disease severity scores, or even lifestyle characteristics. Molecular and behavioral biomarkers play a substantial role in the field of precision medicine. This, in turn, bases medical decisions on individual patient characteristics. Also, the ability to predict the transition of a developing disease before it happens is desirable. In this context, the medical field investigates on very valuable pre-disease biomarkers. Biomarkers enable a set of precision medicine benefits.

Above all, they are also called biological markers and are used in many scientific fields. In context of Research, they are used for patient selection and as outcome measures in clinical trials. In other words, biomarkers are a measurable indicator of some biological state or condition of patients. As a consequence, they are measured and evaluated to examine normal biological processes or pathogenic processes or pharmacologic responses to a therapeutic intervention. More details about their general definition are available here. They have a high potential to improve the diagnosis of patients and prognosis of diseases. Also, they guide clinical treatment decisions and medication.

One important example where pharmacogenomics biomarkers are used is in drug labeling. Pharmacogenomics can play an important role in identifying responders and non-responders to medications. Consequently, avoiding adverse events and optimizing drug dose. The US Food and Drug Administration (FDA) provides a list of more than 160 pharmacogenomic biomarkers (mostly genomic). The list can be found here. FDA approves this list for stratifying patients for drug response. But it is in many cases impossible to identify one single stratification factor or biomarker in data sets for patient populations. The reason is that diseases such as cancer, neurological, or immunological diseases affect a multitude of biological sub-systems.