"A REVIEW ON DIGITAL PHARMACEUTICS: INTEGRATION OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN DRUG DEVELOPMENT"

ABSTRACT: Digital pharmaceutics is a revolutionary paradigm that has been made possible by the merging of digital technologies and pharmaceutical sciences. The integration of artificial intelligence (AI) and machine learning (ML), which are transforming the processes of drug discovery, development, and delivery, lies at the heart of this progress. The use of AI and ML in drug development, including target identification, lead optimization, pharmacokinetic modeling, personalized medicine, and clinical trial design, is examined in this overview along with new developments. By using data-driven methodologies, AI algorithms greatly improve forecast accuracy, shorten development times, and cut related expenses. The R&D process is being streamlined by the growing use of machine learning models for biomarker identification, medication repurposing, and virtual screening. Additionally, digital pharmaceutics is making it possible to create adaptive therapies that are customized to each patient's unique profile and intelligent drug delivery systems. Notwithstanding its potential, issues like algorithm transparency, regulatory frameworks, and data privacy still exist. With a focus on their revolutionary potential in the pharmaceutical sector, this paper offers a thorough summary of the technological developments, important applications, and prospects for the future of AI and ML in digital pharmaceutics.