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      APPROACHES FOR ENCEPHALIC DRUG DELIVERY USING NANOMATERIALS: THE CURRENT STATUS

      Brain Research Bulletin
      Elsevier BV

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          Abstract

          Nanotechnology, the investigation of little structures, ranging from the size of 1 nm-100 nm presents a breakthrough in the field of targeted drug delivery. The microvasculature in the human brain along with the blood brain barrier (BBB) offers high resistance to the entry of therapeutics agents and other substances in to the brain. Nanoparticles have certain advantages as high permeability, reactivity, surface area and quantum properties and it also meets various medical challenges which may include poor bioavailability, difficulty in targeting, organ toxicity etc. The use of nanoparticles in pharmaceuticals has been inspired by various natural nanomaterials found in the body, which includes proteins, lipids etc. A brief explanation of different types of pharmaceutical approaches used in brain drug delivery is discussed here. Nanotechnology is used treatment of many illnesses which also include diseases related to the brain such as gliomas, epilepsy, migraine, cerebrovascular disease, Parkinson's disease etc., Different type of nanoparticles are prepared, such as polymer-based nanoparticles, metallic nanoparticles, carbon-based nanoparticles, lipid-based nanoparticles, ceramic nanoparticles semiconductor nanoparticles and are studied for their usefulness in drug delivery. The primary function of nanoparticles is to deliver drug moiety to the desired targeted site by overcoming permeability issues. The shape, size and surface area nanoparticles help in increasing the bioavailability, drug retention and multiple drug delivery. Mechanisms of nanoparticles crossing BBB can be divided into passive and active transport, are briefly explained.

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          Author and article information

          Journal
          Brain Research Bulletin
          Brain Research Bulletin
          Elsevier BV
          03619230
          November 2019
          November 2019
          Article
          10.1016/j.brainresbull.2019.11.017
          31790722
          3d8268db-86b4-407e-ac1d-cd0a702cbcde
          © 2019

          https://www.elsevier.com/tdm/userlicense/1.0/

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