Drug Delivery Systems using Quantum Computing

Released on by Rishabha Malviya
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  • Drug Delivery Systems using Quantum Computing Book Detail

  • Author : Rishabha Malviya
  • Release Date : 2024-07-30
  • Publisher : John Wiley & Sons
  • Genre : Science
  • Pages : 484
  • ISBN 13 : 1394159145
  • File Size : 85,85 MB
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Drug Delivery Systems using Quantum Computing by Rishabha Malviya PDF Summary

Book Description: The first book of its kind to show the potential of quantum computing in drug delivery. Drug delivery systems (DDS) are defined as methods by which drugs are delivered to desired tissues, organs, cells, and subcellular organs for drug release and absorption through a variety of drug carriers. By controlling the precise level and/or location of a given drug in the body, side effects are reduced, doses are lowered, and new therapies are possible. Nevertheless, there are still significant obstacles to delivering certain medications to particular cells. Drug delivery methods change pharmacokinetic, pharmacodynamic, and drug release patterns to enhance product efficacy and safety, as well as patient convenience and compliance. Computational approaches in drug development enable quick screening of a vast chemical library and identification of possible binders by using modeling, simulation, and visualization tools. Quantum computing (QC) is a fundamentally new computing paradigm based on quantum mechanics rules that enables certain computations to be conducted significantly more rapidly and effectively than regular computing, and hence this has huge promise for the pharmaceutical sector. Significant advances in computational simulation are making it easier to comprehend the process of drug delivery. This book explores an important biophysical component of DDSs, and how computer modeling may help with the logical design of DDSs with enhanced and optimized characteristics. The book concentrates on computational research for various important types of nanocarriers, including dendrimers and dendrons, polymers, peptides, nucleic acids, lipids, carbon-based DDSs, and gold nanoparticles. Audience Researchers and industry scientists working in clinical research and disease management; pharmacists, formulation and pharmaceutical scientists working in R&D; computer science engineers applying deep learning and quantum computing in healthcare.

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