Enhancing Drug Development Efficiency and Approval Success with Innovative Technologies and Precise Clinical Trial Data
Ali Mustafa
Zainab Khalil
Computer Science Department, American University of Beirut, Lebanon
Abstract
The drug development process is notorious for its high costs, extended timelines, and low success rates. Despite advancements in medical research, the journey from discovery to market approval remains fraught with challenges. Recent technological innovations and improvements in clinical trial methodologies offer promising solutions to these issues. This paper explores the role of novel technologies such as artificial intelligence (AI), machine learning (ML), and blockchain in enhancing drug development efficiency. Additionally, it examines the impact of accurate and robust clinical trial data on approval rates. By integrating these technologies, the pharmaceutical industry can potentially streamline drug development processes, reduce costs, and increase the likelihood of regulatory approval. This paper also discusses case studies where these technologies have been successfully implemented, demonstrating their practical benefits. The convergence of cutting-edge technology with rigorous data management practices holds the key to transforming the landscape of drug development, making it more efficient and reliable.
Author Biographies
Ali Mustafa
Ali Mustafa
Computer Science Department, King Fahd University of Petroleum and Minerals, Saudi Arabia
Zainab Khalil, Computer Science Department, American University of Beirut, Lebanon
Zainab Khalil
Computer Science Department, American University of Beirut, Lebanon
