Artificial Intelligence (AI) is revolutionizing the landscape of drug discovery by accelerating the identification and optimization of therapeutic candidates. This book examines the applications of AI and machine learning in various stages of drug development, including target identification, virtual screening, predictive modeling, and clinical trial design. It explores the integration of big data, bioinformatics, and computational techniques to enhance decision-making processes and reduce development timelines. Aimed at pharmaceutical researchers, data scientists, and biotechnology professionals, the book highlights cutting-edge AI methodologies and their transformative impact on the future of drug discovery.
Ella Tran is a leading dermatologist specializing in the role of artificial intelligence (AI) in drug discovery, focusing on leveraging AI technologies to accelerate the identification and development of new dermatological medications. Her research explores the use of machine learning algorithms, predictive modeling, and data analytics to identify potential drug candidates, optimize drug design, and streamline the drug development process for skin conditions such as melanoma, psoriasis, and acne. Ella has authored numerous studies on the integration of AI in pharmacological research and its impact on enhancing the efficiency and success rates of dermatological drug discovery. She has developed comprehensive AI-driven drug discovery protocols that inform the rapid identification and optimization of new dermatological treatments.