Your browser doesn't support javascript.
loading
Artificial Intelligence in Drug Formulation and Development: Applications and Future Prospects.
Srivastava, Varsha; Parveen, Bushra; Parveen, Rabea.
Afiliação
  • Noorain; Department of Pharmaceutics, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India.
  • Srivastava V; Department of Pharmacognosy and Phytochemistry, Centre of Excellence in Unani Medicine (Pharmacognosy and Pharmacology), School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India.
  • Parveen B; Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India.
  • Parveen R; Department of Pharmaceutics, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India.
Curr Drug Metab ; 24(9): 622-634, 2023.
Article em En | MEDLINE | ID: mdl-37779408
Artificial Intelligence (AI) has emerged as a powerful tool in various domains, and the field of drug formulation and development is no exception. This review article aims to provide an overview of the applications of AI in drug formulation and development and explore its future prospects. The article begins by introducing the fundamental concepts of AI, including machine learning, deep learning, and artificial neural networks and their relevance in the pharmaceutical industry. Furthermore, the article discusses the network and tools of AI and its applications in the pharmaceutical development process, including various areas, such as drug discovery, manufacturing, quality control, clinical trial management, and drug delivery. The utilization of AI in various conventional as well as modified dosage forms has been compiled. It also highlights the challenges and limitations associated with the implementation of AI in this field, including data availability, model interpretability, and regulatory considerations. Finally, the article presents the future prospects of AI in drug formulation and development, emphasizing the potential for personalized medicine, precision drug targeting, and rapid formulation optimization. It also discusses the ethical implications of AI in this context, including issues of privacy, bias, and accountability.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Aprendizado de Máquina Tipo de estudo: Clinical_trials Aspecto: Ethics Limite: Humans Idioma: En Revista: Curr Drug Metab Assunto da revista: METABOLISMO / QUIMICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Índia País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Aprendizado de Máquina Tipo de estudo: Clinical_trials Aspecto: Ethics Limite: Humans Idioma: En Revista: Curr Drug Metab Assunto da revista: METABOLISMO / QUIMICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Índia País de publicação: Holanda