Abstract Background Clinical Trials (CTs) remain the foundation of safe and effective drug
development. Given the evolving data-driven and personalized medicine approach in …

Increased scrutiny of artificial intelligence (AI) applications in healthcare highlights the need
for real-world evaluations for effectiveness and unintended consequences. The complexity …

Background Artificial intelligence (AI) research in healthcare is accelerating rapidly, with
potential applications being demonstrated across various domains of medicine. However …

Clinical trials consume the latter half of the 10 to 15 year, 1.5–2.0 billion USD, development
cycle for bringing a single new drug to market. Hence, a failed trial sinks not only the …

With only a limited number of clinical trials of artificial intelligence in medicine thus far, the
first guidelines for protocols and reporting arrive at an opportune time. Better protocol …

Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug
discovery and development, clinical trials, personalized medicine, pharmacogenomics …

Abstract Purpose The Tufts Center for the Study of Drug Development (CSDD) and the Drug
Information Association (DIA) in collaboration with 8 pharmaceutical and biotechnology …

This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

Highlights•Artificial Intelligence (AI) has transformed many areas such as speech and image
recognition, but not yet drug discovery.•Approaches to AI in drug discovery need to take in …

Background The application of artificial intelligence (AI) in healthcare is an area of immense
interest. The high profile of 'AI in health'means that there are unusually strong drivers to …