In recent years, antibiotic therapy has encountered significant challenges due to the rapid
emergence of multidrug resistance among bacteria responsible for life‐threatening …

Machine learning is playing a very significant role to process voluminous data and its
classification in a variety of domains. Due to better performance and rapid development in …

Clinical trials are the essential assessment for safe, reliable, and effective drug
development. Data-related limitations, extensive manual efforts, remote patient monitoring …

This paper proposes a novel conceptual framework that integrates the advanced capabilities
of quantum computing to address the urgent need for responsible and inclusive Artificial …

Drug design and development (DDD) is a lengthy and timeconsuming process. The process
can take up to 14–15 years, and the cost ranges from US $944 million to US $2,826 million …

Drug discovery is a complex and iterative process, making it ideal for using artificial
intelligence (AI). This paper uses a bibliometric approach to reveal AI's trend and underlying …

The drug discovery process necessitates a significant investment of time and resources.
Typically, over a decade and billions of dollars are required to bring a single drug to market …

Traditional drug discovery is a long, expensive, and complex process. Advances in Artificial
Intelligence (AI) and Machine Learning (ML) are beginning to change this narrative. Here …

The latest breakthroughs in information technology and biotechnology have catalyzed a
revolutionary shift within the modern healthcare landscape, with notable impacts from …

Drug discovery is a complex and multifaceted process aimed at identifying new therapeutic
compounds with the potential to treat various diseases. Traditional methods of drug …