Pedram Asadi Sarabi, Mahshid Shabanpouremam, Amir Reza Eghtedari, Mahsa Barat, Behzad Moshiri, Ali Zarrabi, Massoud Vosough
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引用次数: 0
Abstract
The emergence of Artificial Intelligence (AI) and its usage in regenerative medicine represents a significant opportunity that holds the promise of tackling critical challenges and improving therapeutic outcomes. This article examines the ways in which AI, including machine learning and data fusion techniques, can contribute to regenerative medicine, particularly in gene therapy, stem cell therapy, and tissue engineering. In gene therapy, AI tools can boost the accuracy and safety of treatments by analyzing extensive genomic datasets to target and modify genetic material in a precise manner. In cell therapy, AI improves the characterization and optimization of cell products like mesenchymal stem cells (MSCs) by predicting their function and potency. Additionally, AI enhances advanced microscopy techniques, enabling accurate, non-invasive and quantitative analyses of live cell cultures. AI enhances tissue engineering by optimizing biomaterial and scaffold designs, predicting interactions with tissues, and streamlining development. This leads to faster and more cost-effective innovations by decreasing trial and error. The convergence of AI and regenerative medicine holds great transformative potential, promising effective treatments and innovative therapeutic strategies. This review highlights the importance of interdisciplinary collaboration and the continued integration of AI-based technologies, such as data fusion methods, to overcome current challenges and advance regenerative medicine.
期刊介绍:
The European Journal of Pharmacology publishes research papers covering all aspects of experimental pharmacology with focus on the mechanism of action of structurally identified compounds affecting biological systems.
The scope includes:
Behavioural pharmacology
Neuropharmacology and analgesia
Cardiovascular pharmacology
Pulmonary, gastrointestinal and urogenital pharmacology
Endocrine pharmacology
Immunopharmacology and inflammation
Molecular and cellular pharmacology
Regenerative pharmacology
Biologicals and biotherapeutics
Translational pharmacology
Nutriceutical pharmacology.