Year: 2024
Type: article
Abstract: Background: Cardiovascular disease (CVD) is a major global health issue, contributing significantly to morbidity, mortality, and economic burden. Despite medical advancements, developing effective cardiovascular drugs remains challenging due to the complexity of these disorders and the high failure rates in clinical trials. Traditional drug discovery methods, reliant on empirical testing, are often slow and inefficient. Objective: This book examines the transformative potential of artificial intelligence (AI) in addressing the challenges of cardiovascular drug discovery. It aims to elucidate how AI can improve drug development processes and enhance personalized medicine. Methods: The book reviews AI's applications throughout the drug discovery process, from target identification to clinical trials. It integrates case studies, expert opinions, and real-world examples to illustrate AI's impact on improving drug design, predictive accuracy, and therapeutic outcomes. Results: AI has demonstrated significant promise in revolutionizing cardiovascular drug discovery. In analyzing extensive biomedical data, AI enables the identification of novel patterns and insights that traditional methods may overlook. This facilitates more effective target identification, drug design, and prediction of drug efficacy and safety. Conclusion: The integration of AI into cardiovascular drug discovery offers substantial potential to overcome existing limitations, streamline the development process, and improve patient outcomes. The book underscores the role of AI in reshaping cardiovascular healthcare and addressing the global burden of CVD.
DOI: 10.53555/8xp0p349
Author: Imesha Kalansuriya
Institution: Medical University of the Americas
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4403339370