Mekkanti Manasa Rekha,
Soumitra Das,
- Associate Professor, Department of Pharmacy Practice, Aditya Bangalore Institute of Pharmacy Education and Research, Bangalore, Karnataka, India
- Pharm.D V Year, Department of Pharmacy Practice, Aditya Bangalore Institute of Pharmacy Education and Research, Bangalore, Karnataka, India
Abstract
Artificial intelligence (AI) in pharmaceutical repurposing has become a game-changing tool that opens new avenues for the application of new drugs that have already been approved. Traditional drug discovery is a lengthy and expensive process, whereas AI can rapidly analyze vast datasets of biological, chemical, and clinical information to predict drug-disease interactions. AI-driven techniques, such as machine learning, natural language processing, and deep learning, enable the identification of potential repurposing candidates by analyzing molecular structures, gene expression profiles, and patient data. Recent success stories include AI models identifying drugs like Baricitinib for COVID-19 and different substances for uncommon illnesses, like Fragile X syndrome. AI’s capacity to streamline the process of discovering drugs speeds up therapy development, cuts costs, and improves the accuracy of matching drugs to diseases, proving to be a valuable tool in combating various illnesses. Nonetheless, issues like data quality, AI model interpretability, and the requirement for clinical validation continue to be crucial areas for additional study.
Keywords: Artificial intelligence (AI), COVID-19, Fragile X syndrome, Baricitinib, AI-driven techniques, etc,
[This article belongs to Trends in Drug Delivery (tdd)]
Mekkanti Manasa Rekha, Soumitra Das. Artificial Intelligence in Drug Repurposing: A Short Impact. Trends in Drug Delivery. 2024; 11(03):-.
Mekkanti Manasa Rekha, Soumitra Das. Artificial Intelligence in Drug Repurposing: A Short Impact. Trends in Drug Delivery. 2024; 11(03):-. Available from: https://journals.stmjournals.com/tdd/article=2024/view=180557
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Trends in Drug Delivery
Volume | 11 |
Issue | 03 |
Received | 27/09/2024 |
Accepted | 25/10/2024 |
Published | 30/10/2024 |