LAUSR

Inherent variability among patients significantly affects the outcomes of pharmacotherapy. Patients with apparently the same diagnosis often respond differently to the same pharmacological intervention, both with respect to efficacy and/or safety. Despite this knowledge, a large part of pharmacotherapy is still based on a ‘trial and error’ approach, which can have a severe negative impact on the patient [1]. The inability to predict which patients will respond to which drugs affects the efficacy and value of pharmacotherapy. However, the past 30 years of progress in molecular medicine has provided us with a better understanding of the underlying pathophysiology and mechanism of action of drugs, which is a prerequisite for making pharmacotherapy more predictable and efficient [2]. For some diseases and drugs, this understanding has led to the development of different types of predictive biomarkers, which can help to identify patients who are more likely to benefit from the drug in question and make pharmacotherapy more personalized. According to the FDA-NIH Biomarker Working Group, a predictive biomarker is defined as a biomarker used to identify individuals who are more likely than similar individuals without the biomarker to experience a favorable or unfavorable effect from exposure to a medical product or an environmental agent [2]. These biomarkers most often represent patient characteristics such as molecular changes related to somatic and germline DNA, receptor proteins, cytochrome P450 enzyme phenotype, HLA type, etc. If a biomarker is predictive for a specific drug, its presence will indicate that the patient will have a higher probability of a positive outcome. For the past couple of decades, two types of predictive biomarkers have found their way into the clinic: companion diagnostic (CDx) and pharmacogenetic (PGx) biomarkers. In this editorial, we briefly discuss different aspects related to these two types of predictive biomarkers and their role in patient care.