Journal of Molecular Biomarkers and Clinical Trials
Nanotechnology for Biomarkers or Biomarkers for Nanotechnology in Medical Approaches: What Can We Anticipate?
*Dr. Michele Munk Pereira Nanosciences Nanotechnology, Nanotechnology Laboratory, Brazil
*Corresponding Author: Dr. Michele Munk Pereira
Nanosciences Nanotechnology, Nanotechnology Laboratory, Brazil Email:email@example.com
Published on: 2015-06-27
In recent years, there has been excitement about the ability to predict the future disease risk factor status. For this purpose, biomarkers have been used in pre-clinical research and clinical diagnosis. The National Institute of Health Biomarkers Definitions Working Group has defined a biomarker as a measurable indicator of some normal biological processes, pathogenic processes, or pharmacological responses and toxicological effects of a therapeutic intervention. Biomarkers can be of various molecular origins, including nucleic acid (DNA or RNA), protein (enzymes or antibodies), or a substance introduced into the body to assess how an organ, tissue, or system is functioning.
Recent advances in nanotechnology have led to the development of high-sensitivity Nanobiosensors that can be used in prognostic and diagnostic applications and to determine drug effectiveness at various target sites. Nanomaterials (NM) possess unique chemical, physical, electrical, optical, and magnetic properties that enable their use as sensors . Thus, the application of NM to the diagnosis refines molecular diagnostic approaches.Diverse types of nanostructured materials, including carbon nanotubes, gold nanoparticles, silicon nanowires, and quantum dots, are being used in the fabrication of sensors . When conjugated to a targeting ligand that can bind to a specific marker of interest, NM acts as a generator or a sensitive detector of a specific biological signal . Compared to most conventional sensors, such Nanobiosensors show enhanced sensitivity and specificity. Nanobiosensors can be precisely engineered to detect emerging biomarkers of diseases such as cancer, autoimmune diseases, infectious diseases, and metabolic diseases and to assess the risk of transplant rejection [2-5]. This approach could potentially produce point-ofcare diagnostic devices that could improve treatment effectiveness, reduce health care costs, and save lives .