Nanotechnology Principles in Drug Targeting and Diagnosis /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Rai, Mahendra, Khan, Shagufta, Belgamwar, Aarti
Formato: eBook
Idioma:Inglés
Publicado: San Diego : Elsevier, 2023.
Colección:Micro & nano technologies.
Temas:
Drug targeting.
Nanotechnology > Therapeutic use.
Drug Delivery Systems
M�edicaments > Ciblage.
Nanotechnologie > Emploi en th�erapeutique.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover
  • Nanotechnology Principles in Drug Targeting and Diagnosis
  • Copyright Page
  • Contents
  • List of contributors
  • Preface
  • 1 Drug targeting: general principles and strategies
  • 1 Drug targeting: nanotechnology principles, future perspectives, and challenges
  • 1.1 Introduction
  • 1.2 Nanotechnology-based drug targeting approaches
  • 1.2.1 Passive targeting
  • 1.2.2 Active targeting
  • 1.2.3 Physical targeting
  • 1.3 Targeted nanoparticulate systems for various disorders
  • 1.3.1 Nanotechnology in cancer
  • 1.3.2 Nanotechnology in infectious diseases
  • 1.3.3 Nanotechnology in cardiovascular diseases
  • 1.3.4 Nanotechnology in autoimmune diseases
  • 1.3.5 Nanotechnology in neurodegenerative diseases
  • 1.3.6 Nanotechnology in respiratory diseases
  • 1.3.7 Nanotechnology in ocular diseases
  • 1.3.8 Application of artificial intelligence in targeted drug delivery
  • 1.4 Future perspectives and challenges
  • 1.5. Conclusion
  • Acknowledgment
  • References
  • 2 Identifying nanocarrier-target interaction
  • 2.1 Introduction
  • 2.2 Potential targets for active targeting
  • 2.2.1 Transferrin receptors
  • 2.2.2 Human epidermal growth factor receptor 2
  • 2.2.3 CD19
  • 2.2.4 CD20
  • 2.2.5 Alpha beta 3 integrins
  • 2.2.6 Luteinizing hormone-releasing hormone receptor
  • 2.2.7 Folate
  • 2.3 Surface modification strategies of nanocarriers
  • 2.3.1 Tf-functionalized nanocarriers
  • 2.3.2 Epidermal growth factor receptor-functionalized nanocarriers
  • 2.3.3 CD19-functionalized nanocarriers
  • 2.3.4 CD20-targeted nanocarriers
  • 2.3.5 Alpha beta 3 integrin-targeted nanocarriers
  • 2.3.6 Folate receptor-targeted nanocarriers
  • 2.3.7 Luteinizing hormone-releasing hormone peptide-tagged nanocarriers
  • 2.4 Factors affecting nanocarrier-cell interaction
  • 2.5 Methods to confirm carrier target interaction
  • 2.5.1 Fluorescence microscopy
  • 2.5.2 Raman imaging
  • 2.5.3 Coherent anti-stokes Raman scattering microscopy
  • 2.5.4 Electron microscopy
  • 2.5.5 Correlative light-electron microscopy
  • 2.6 Conclusion and future perspectives
  • References
  • 3 Artificial neural network-based inference of drug-target interactions
  • 3.1 Introduction
  • 3.1.1 Drug discovery and development process
  • 3.1.1.1 Brief introduction
  • 3.1.1.2 Research and development and attrition rates
  • 3.2 Artificial neural networks
  • 3.2.1 Principle and topology
  • 3.2.2 Basic topology
  • 3.2.3 Machine learning
  • 3.2.3.1 Learning algorithms
  • 3.2.3.2 Deep learning
  • Convolutional neural networks
  • Recurrent neural networks
  • Graph neural networks
  • 3.3 Applications of artificial neural networks to drug-target interactions
  • 3.3.1 Target identification and validation
  • 3.3.2 Target compound synthesis
  • 3.3.3 Drug designing
  • 3.3.4 Drug pathway
  • 3.3.5 Protein-ligand affinity
  • 3.3.6 Pharmacological activities
  • 3.3.7 Structure-activity relationship
  • 3.3.8 Drug repurposing
  • 3.3.9 Drug-drug interactions
  • 3.3.9.1 Synergistic effect

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